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Fanconi Anemia ( FA ) is a genomic instability syndrome resulting in aplastic anemia , developmental abnormalities , and predisposition to hematological and other solid organ malignancies . Mutations in genes that encode proteins of the FA pathway fail to orchestrate the repair of DNA damage caused by DNA interstrand crosslinks . Zebrafish harbor homologs for nearly all known FA genes . We used multiplexed CRISPR/Cas9-mediated mutagenesis to generate loss-of-function mutants for 17 FA genes: fanca , fancb , fancc , fancd1/brca2 , fancd2 , fance , fancf , fancg , fanci , fancj/brip1 , fancl , fancm , fancn/palb2 , fanco/rad51c , fancp/slx4 , fancq/ercc4 , fanct/ube2t , and two genes encoding FA-associated proteins: faap100 and faap24 . We selected two indel mutations predicted to cause premature truncations for all but two of the genes , and a total of 36 mutant lines were generated for 19 genes . Generating two independent mutant lines for each gene was important to validate their phenotypic consequences . RT-PCR from homozygous mutant fish confirmed the presence of transcripts with indels in all genes . Interestingly , 4 of the indel mutations led to aberrant splicing , which may produce a different protein than predicted from the genomic sequence . Analysis of RNA is thus critical in proper evaluation of the consequences of the mutations introduced in zebrafish genome . We used fluorescent reporter assay , and western blots to confirm loss-of-function for several mutants . Additionally , we developed a DEB treatment assay by evaluating morphological changes in embryos and confirmed that homozygous mutants from all the FA genes that could be tested ( 11/17 ) , displayed hypersensitivity and thus were indeed null alleles . Our multiplexing strategy helped us to evaluate 11 multiple gene knockout combinations without additional breeding . Homozygous zebrafish for all 19 single and 11 multi-gene knockouts were adult viable , indicating FA genes in zebrafish are generally not essential for early development . None of the mutant fish displayed gross developmental abnormalities except for fancp-/- fish , which were significantly smaller in length than their wildtype clutch mates . Complete female-to-male sex reversal was observed in knockouts for 12/17 FA genes , while partial sex reversal was seen for the other five gene knockouts . All adult females were fertile , and among the adult males , all were fertile except for the fancd1 mutants and one of the fancj mutants . We report here generation and characterization of zebrafish knockout mutants for 17 FA disease-causing genes , providing an integral resource for understanding the pathophysiology associated with the disrupted FA pathway .
Fanconi anemia ( FA ) is a rare , mostly recessive , DNA repair deficiency disorder characterized by progressive bone marrow failure ( BMF ) , predisposition to cancer and developmental anomalies including hypogonadism and infertility [1 , 2] . About 2/3 of patients display congenital abnormalities affecting multiple organ systems including the skin , kidney and urinary tract , ears , eyes , gastrointestinal , heart , and central nervous systems . Short stature , microcephaly , microphthalmia , hypogenitalia , supernumerary or hypoplastic/absent thumb with or without absence of radius , are often observed in FA patients [3] . BMF is an inevitable consequence of FA resulting in aplastic anemia due to the depletion of hematopoietic stem cells . The age of onset of anemia is variable but typically is in the first decade [4] . Patients also develop acute myeloid leukemia ( AML ) or myelodysplastic syndrome that ultimately progresses to AML [4] . An increased predisposition to solid tumors , particularly head and neck squamous cell carcinoma ( HNSCC ) , esophageal and gynecological tissues is associated with FA [1 , 5] . The incidence of HNSCC in FA patients is increased 700-fold , and the onset is much earlier ( in a patient’s 30s ) compared to sporadic HNSCC [6] . In about 25% of patients , the first clinical presentation is AML or solid tumors [7 , 8] . Thus , FA is phenotypically a heterogeneous disease [9] . Increased chromosomal instability from impaired DNA crosslinking repair upon exposure to DNA crosslinking agents such as Diepoxybutane ( DEB ) or Mitomycin C ( MMC ) , is a universal cellular phenotype of patient cells and serves as an unambiguous diagnostic test for FA [3] . In humans , mutations in 22 genes are known to cause FA: FANCA , FANCB , FANCC , FANCD1/BRCA2 , FANCD2 , FANCE , FANCF , FANCG , FANCI , FANCJ/BRIP1 , FANCL , FANCM , FANCN/PALB2 , FANCO/RAD51C , FANCP/SLX4 , FANCQ/ERCC4/XPF , FANCR/RAD51 , FANCS/BRCA1 , FANCT/UBE2T , FANCU/XRCC2 , FANCV/MAD2L2/REV7 , and FANCW/RFWD3 . Our understanding of the disease is continually evolving as three of these genes were reported within the last two years [10–12] . These genes encode proteins that participate in the FA pathway ( also known as FA/BRCA pathway ) , which orchestrates the repair of DNA interstrand crosslinks ( ICL ) [5 , 12] . Proper function of FA proteins has been shown to be important in maintaining hematopoietic stem cells , guarding genomic integrity , and preventing tumorigenesis [6 , 13] . Additional roles for FA proteins are emerging in aging [14] , telomere biology [15] , and selective autophagy and inflammation [16] . Animal models to help understand the molecular basis of FA clinical presentations and help explore the role of FA proteins in critical biological functions are needed . Biochemical and genetic studies have revealed to some extent the structural and functional components of the FA pathway [6 , 12 , 17–23] . In general , there are four protein complexes each performing a distinct function in accomplishing the repair of the damaged DNA: core complex ( FANCA , FANCB , FANCC , FANCE , FANCF , FANCG , FANCL , and FANCM ) , ID2 complex ( FANCD2-FANCI ) , nucleolytic processing ( FANCP and FANCQ ) , and homologous recombination ( FANCD1 , FANCJ , FANCN , FANCO , FANCR , FANCS , FANCU , and FANCW ) . Upon recognition of a signal of DNA damage the core complex along with FANCT and the FA-associated proteins ( FAAP ) ubiquitinates the ID2 complex . Subsequent nucleolytic processing leads to translesion synthesis by a DNA polymerase ( FANCV ) , and the repair process is completed by homologous recombination . Though distinct biochemical functions of most of the core complex proteins that perform ubiquitination is yet unknown , it appears that sub-complexes of FANCA-FANCG confer stability to the complex , FANCC-FANCE-FANCF offer specificity and efficiency , and FANCB-FAAP100-FANCL along with FANCT transfer ubiquitin moieties on to the ID2 complex . Only a fraction of FA gene homologs are present in any invertebrate model organism [24 , 25] , limiting the utility of these models . All are present in zebrafish with the exception of FANCS/BRCA1 [26 , 27] . Zebrafish provide an excellent opportunity to understand FA associated BMF and congenital anomalies , as hematopoiesis and embryonic development in zebrafish are well studied [28] and the ability to perform high throughput mutagenesis by CRISPR/Cas9 in zebrafish [29 , 30] allows us to generate targeted mutations readily in many genes . We generated loss-of-function ( frameshift ) mutants for these 17 FA genes: fanca , fancb , fancc , fancd1/brca2 , fancd2 , fance , fancf , fancg , fanci , fancj/brip1 , fancl , fancm , fancn/palb2 , fanco/rad51c , fancp/slx4 , fancq/ercc4 , fanct/ube2t . We also targeted two additional genes encoding FA-associated proteins ( faap100 and faap24 ) . Here , we present our data on the generation of mutant fish , evaluation of the consequences of genomic indels at the mRNA level , and characterization of mutant fish phenotypes such as growth , viability , sex differentiation , and fertility .
The goal of our study was to analyze the in vivo functions of all known FA genes . Therefore , we applied the CRISPR/Cas9 technology to generate loss-of-function mutations in zebrafish . We targeted 17 genes known to have disease-causing mutations in FA patients , and two genes encoding for FA-associated proteins ( S1 Table ) . To maximize the chances of generating loss-of-function mutations , we selected CRISPR target sites in the first half of the coding region ( S1 Fig ) . Based on recent studies that demonstrated efficient multiplexed mutagenesis in zebrafish using CRISPR/Cas9 [29 , 30] , we employed this approach to generate knockouts . Multiplexing was primarily based on the known interactions among the FA proteins and their specific roles in the FA pathway [18–21] , and therefore we also generated multi-gene knockouts to study their combined effect ( Table 1 ) . Seven groups of pooled sgRNAs , that were prescreened for activity , were injected to target these 19 genes , which included three groups each of two and three genes and a group of four genes . The injected fish ( mosaic founders ) were screened for germline transmitting mutations in each of the co-injected genes by genotyping of embryos from their outbred progeny . By screening a total of 75 founder fish , we identified 59 germline transmitting founders that passed multiple combinations of indel mutations in the co-injected genes . About three quarters of the germline transmitting founders showed mutations in two or more genes ( 46/59 = 78% ) ( Table 1 ) . Our data demonstrate that multiplexing of sgRNAs is an efficient approach to directly generate multi-gene mutant fish lines when using prescreened active sgRNA’s . We outbred the selected founder fish with germline transmitting mutations to generate F1 fish heterozygous for frameshift mutations in each targeted gene . These fish were genotyped at adulthood for each of the co-targeted genes . Our selection criteria for establishing mutant lines was to use either the F1 fish heterozygous for the desired mutant alleles in multiple genes or the F1 fish heterozygous for specific mutant alleles while carrying WT alleles at all other co-injected loci . We excluded any fish that were heterozygous for the desired allele but carried a non-desirable mutant allele , such as an in-frame indel mutation at the other co-injected loci , to avoid extensive genotyping in future generations . We selected two frameshift mutations for each gene , except one each for fancb and fancd1 , resulting in a total of 36 single gene mutant alleles for the follow-up phenotypic analyses ( S2 Fig , S2 Table ) . Through our multiplexing effort , we were able to generate nine multi-gene mutant allele combinations across all seven injection groups ( S3 Table ) . Details of the selected mutant alleles including the size of indel , predicted cDNA and protein changes , and their designation by The Zebrafish Information Network ( https://zfin . org/action/feature/line-designations ) are provided in S2 Table . In the subsequent sections , we refer to the mutant alleles by their “hg” nomenclature as listed in S2 Table . An indel in the genomic sequence that is not a multiple of three is predicted to cause a frameshift in translation , therefore we confirmed the presence of each predicted mutation in the mRNA transcripts . This effort would also reveal aberrant splicing caused by indel variants , if any . To this end , we performed RT-PCR for all mutant alleles using RNA extracted from adult WT and homozygous mutant fish . Our RNA analysis showed the following: 1 ) All 36 mutant alleles yielded an RT-PCR product ( S3A Fig ) . 2 ) Products of predicted size , one wild-type and one including the indel mutation , were observed in all but one mutant allele , hg58 ( Figs 1A and S3A ) . 3 ) An additional product was observed in three mutant alleles: hg41 , hg42 , and hg45 ( Fig 1B–1D ) . Details of splicing aberrations in these 4 cases are described below . The RT-PCR product from the fanclhg58/hg58 mutant was smaller than the expected size , based on the CRISPR/Cas9-induced 25 bp insertion mutation in exon 8 ( Fig 1A ) . Sequencing revealed that the 25 bp insertion created a cryptic splice acceptor site leading to the deletion of 23 bp in the mRNA , resulting in a different frameshift mutation than predicted , still likely to cause a loss-of-function ( Figs 1E and S3B ) . The RT-PCR products from fancahg41/hg41 , fancbhg42/hg42 , and fancd1hg45/hg45 revealed a second band , in addition to the expected band , indicating partial activation of a cryptic splice site near the indel mutation ( Fig 1B–1D ) . The intensity of the additional band in all three mutants was weaker , suggesting low abundance of the altered splice product . Nevertheless , it might be enough to have an effect on the phenotype by generating a low level of functional protein . To determine the effect of altered splicing on the reading frame and the encoded protein , we analyzed these RT-PCR products by cloning and sequencing . In the fancahg41/hg41 mutant , the additional product was missing exon 12 , which contained the 2bp deletion mutation , due to altered splicing ( Figs 1B and S3C ) . The altered splice product still generated a frameshift mutant protein ( p . E378Afs*12 ) ( Fig 1E ) . In the fancbhg42/hg42 mutant , the additional product had an insertion of 31 bp from intron 1 ( Figs 1C and S3D ) , due to aberrant splicing caused by a cryptic splice donor in intron 1 . The combined effect of a 4 bp deletion mutation near the end of exon 1 and the retention of 31 bp in the region adjacent to intron 1 generated an in-frame mutant protein with a deletion of 2 amino acids and an insertion of 11 unrelated amino acids ( p . F278_Q279delinsRSVMLPQVFLR ) . The additional product in the fancd1hg45/hg45 mutant had a deletion of 92 bp in exon 10 ( includes 87 bp from WT sequence and a 5 bp insertion mutation ) ( Figs 1D and S3E ) . The aberrant splice product generated an in-frame mutant protein with a deletion of 29 amino acids ( p . G346_S374del ) . The in-frame mutant proteins generated by fancbhg42/hg42 and fancd1hg45/hg45 could potentially maintain their function ( Fig 1E ) . The unintended consequences of CRISPR/Cas9-induced indel mutations such as aberrant splicing , that we observed in our zebrafish mutants , highlight the importance of analyzing the RNA , rather than relying on genomic DNA analysis alone . This is particularly important if the mutant fish do not display any phenotype . It is important to validate that the frameshift mutant alleles lead to generation of truncated proteins as predicted and are therefore true loss-of-function alleles . However , due to the absence of zebrafish antibodies or cross-species reacting antibodies for nearly all FA proteins , we could not evaluate protein expression in our mutants , except for Fancd2 . Finding that a human FANCD2 antibody recognized its zebrafish counterpart , allowed us to confirm that the Fancd2 is not expressed in both fancd2 knockout lines , indicating that these are indeed null alleles ( S4 Fig ) . As an alternate method , we used a recently described functional fluorescent mutation reporter assay [31] to test mutant alleles for a subset of genes: fance ( hg48 ) , fancf ( hg50 ) , fancg ( hg52 ) , fancl ( hg59 ) and fanct ( hg70 ) . Despite robust control RFP expression , lack of GFP expression driven by the mutant allele , when compared to the WT allele , indicated that these frameshift mutations indeed introduce a premature stop codon ( S5 Fig ) . These data show that the mutant alleles for all five genes tested are true loss-of-function frameshift mutations . In addition , as described below , we demonstrated hypersensitivity of nearly all frameshift mutant alleles to DEB treatment indicating that these are indeed null alleles . FA patient cells show hypersensitivity to DNA cross-linking agents such as DEB and MMC resulting in chromosomal breakage [3] . To determine if our mutants also exhibit similar hypersensitivity , the embryos from inbred heterozygous mutants were treated with DEB . The homozygous knockouts from fancd1 ( hg45 ) , fancd2 ( hg47 ) , fanci ( hg54 ) , fancj ( hg56 and hg57 ) , fancn ( hg62 ) , fancp ( hg66 ) and fanct ( hg70 ) mutant lines showed severe morphological changes compared to their WT and heterozygote clutch mates , indicating their hypersensitivity to DEB ( Fig 2A ) . However , similar hypersensitivity was not distinct for the remaining mutants , possibly due to the protection provided by wildtype maternal transcript . To test this , we set up fanca ( hg41 ) homozygous mutant incross , as both male and female were available , and also outcross with wildtype counterparts . Untreated embryos from all three crosses looked normal . Hypersensitivity to DEB treatment was observed among all the embryos from incross , and most embryos from female mutant outcross despite all being heterozygotes . But , none of the embryos from male mutant outcross were affected indicating that the presence of wildtype fanca maternal transcript rescues embryos from hypersensitivity to DEB treatment ( Fig 2B ) . Additionally , we incrossed homozygous knockout mutant fish for fancb ( hg42 ) , fanco ( hg65 ) and fancq ( hg69 ) , and observed similar hypersensitivity of the embryos to DEB treatment ( Fig 2C ) . The lack of null females due to sex reversal phenotypes ( described later ) prevented us from preforming inbreeding experiments for other alleles . Overall , we demonstrate homozygous mutant embryo specific DEB sensitivity for 11 out of 17 FA gene mutants either by heterozygote or homozygote inbreeding . Nevertheless , our DEB test results further validate all the tested knockout mutants indeed have lost function of the targeted gene . To determine if the homozygous knockouts survive to adulthood , we grew progenies from pairwise heterozygous crosses of all mutations to adulthood and determined the genotypes of the surviving fish . Homozygous knockout fish were observed among the surviving adults for all genes , indicating no lethality at earlier developmental stages for the generated alleles . Furthermore , the survival was at the expected Mendelian ratios for the majority of the targeted genes . In fancp , fance , and faap24 , however , we observed discordant results between the survival of homozygous fish for the two different mutant alleles , where survival of one of the two knockout alleles was consistent with a Mendelian ratio while in the other allele it was not ( Figs 3 , S6 and S7 ) . Reduced survival was statistically significant for fancphg66/hg66 ( p = 0 . 0003 ) but not for fancphg67/hg67 ( p = 0 . 0875 ) fish . Genotyping at one month post fertilization ( mpf ) revealed that the number of fancphg66/hg66 homozygous fish at this age were consistent with Mendelian ratio ( Fig 4A ( i ) ) , indicating that some of the fancphg66/hg66 fish die between 1 mpf and adulthood . Similarly , fancehg48/hg48 ( p = 0 . 011 ) and faap24hg75/hg75 ( p = 0 . 027 ) fish showed reduced survival , while fancehg49/hg49 fish ( p = 0 . 077 ) and faap24hg74/hg74 ( p = 0 . 079 ) survived in expected numbers ( S7 Fig ) . Overall , our data suggest knockouts of individual genes from FA pathway in zebrafish are not lethal . Multiplexing enabled us to obtain fish with mutations in multiple genes directly from founder fish outcrosses . Theoretically , twenty-six combinations of double , triple , and quadruple gene F1 heterozygous knockouts were possible from the seven injection groups ( S3 Table ) . However , our selection criteria were to retain and analyze only those carrying the mutant alleles described for single gene knockouts ( S2 Table ) . Nevertheless , we obtained nine combinations of multi-gene F1 heterozygous mutants . Six of these were inbred to generate multi-gene homozygous knockouts , while the remaining three were not inbred due to the absence of either male or female carriers . Our data showed that all 11 possible multi-gene homozygous knockout fish were adult viable , suggesting absence of epistasis in the knockouts for tested gene combinations ( S3 Table ) . During the adult survival experiment , we observed that the fancp-/- adult fish for both mutations were smaller in size than their WT and heterozygous clutch mates . To follow up on this observation , inbreedings for fancphg66/+ and fancphg67/+ were done in duplicate and their progeny’s body length were measured at juvenile ( 1 mpf ) and adult stages ( 4 mpf ) . The homozygous knockout fish with both alleles were significantly smaller in body length than their clutch mates at 1 and 4 mpf ( Figs 4A and 4B , S8A and S8B ) . The observed smaller body length phenotype in fancp-/- appears to reflect the short stature frequently observed in FA patients . To examine the effect of fancq mutant alleles on smaller body length of fancp mutant alleles , we inbred double heterozygotes ( fancphg66/+;fancqhg68/+ ) and measured body lengths of their progenies . All fancp homozygous knockout fish , irrespective of fancq genotype , were significantly smaller , indicating the fancq mutation has no role in expression of this phenotype ( S9 Fig ) . Zebrafish have high developmental plasticity for sex determination and they lack the sex-determining chromosome ( s ) of mammals [32] . The plasticity of sex determination in zebrafish can help us to study mechanisms and factors that are associated with gonadogenesis and hypogonadism . We raised progeny from inbred heterozygous fish from one allele for each FA gene ( alleles shown in Fig 3 ) and sexed them after genotyping at 3–4 mpf . Surprisingly , for 12 FA genes ( fancc , fancd1 , fancd2 , fance , fancf , fancg , fanci , fancj , fancl , fancn , fancp , and fanct ) , no females were observed among surviving homozygous knockouts , and for the remaining five FA genes ( fanca , fancb , fancm , fanco , and fancq ) , homozygous knockout females were in greatly reduced numbers ( Fig 5 ) . The presence of only males , or significantly increased number of males , in adult knockouts ( Fig 5 ) and the absence of reduced survival of adult knockouts ( except for fancphg66/hg66 ) ( Figs 3 and S6 ) suggests a female-to-male sex reversal phenotype among FA gene knockout fish . We tested both alleles for fancp due to reduced body length , and allele specific discrepancy in their survival . The female-to-male sex reversal phenotype was observed in both fancp lines ( Fig 5 ) . We also tested both fancj alleles as they displayed a different male fertility phenotype ( as described in the section below ) . Interestingly , the fancjhg56/hg56 showed a complete female-to-male sex reversal , whereas the fancjhg57/hg57 allele showed a partial sex reversal phenotype ( Fig 5 ) . It is possible that the partial sex reversal phenotypes observed for fanca , fancb , fancm , fanco , and fancq may also be allele specific . To test this , we checked other mutant allele lines for these genes except for fancb , for which we only had one mutant allele . Second mutant alleles for fanca , fanco and fancq also revealed the partial sex reversal phenotype , whereas no females were observed in the second fancm mutant line indicating complete sex reversal phenotype ( S10 Fig ) . Overall , our data show that the FA genes are important for gonadogenesis in zebrafish , which may reflect the commonly observed hypogonadism among FA patients [2 , 3] . To determine the stage at which FA gene mutations affects sex differentiation , we examined histological sections of larval ( 21 dpf ) and juvenile ( 45 dpf ) stage gonads of fancc_hg43 mutant fish as a representative mutant allele . At 21 dpf , the gonads of both homozygous knockout and heterozygous fish were undifferentiated and contained gonocytes . By 45 dpf , a definitive testicular differentiation was apparent among homozygotes , whereas both ovarian or testicular differentiation was apparent among heterozygotes ( S11 Fig ) . To examine if loss of tp53 can rescue the sex reversal phenotypes as previously demonstrated for fancd1 , fancl and fancr [33–36] , we introduced tp53 knockout mutation into fancp mutant fish as a representative of FA gene mutants with complete female to male sex reversal . First , tp53 mutant ( hg91: c . 368_374delCCGTGGT; p . S123Ffs*38 ) fish were generated using CRISPR-Cas9 method to target exon 5 . We deliberately targeted exon 5 to generate a frameshift indel mutant that should result in premature termination in all known tp53 transcript isoforms [37 , 38] . RT-PCR and fluorescent mutation reporter assay confirmed that the frameshift caused by 7bp deletion results in premature termination ( Fig 6A and 6B ) . Furthermore , the availability of zebrafish Tp53 antibody allowed us to confirm that our tp53 mutant allele is indeed a null mutant ( Fig 6C ) . To test the effect of the tp53 null mutation on fancp sex reversal phenotype , we crossed fancphg67/+;tp53hg91/h91 mutant fish with fancphg67/+;tp53hg91/+ fish . The resulting progenies were grown to adulthood to determine the correlation between the sex and genotype of the fish . Both male and female fish were observed with fancphg67/hg67;tp53hg91/hg91 genotype ( Fig 6D ) , indicating that Tp53-mediated apoptosis of germ cells causes the sex reversal in fancp homozygous knockouts and may be a common mechanism of sex reversal phenotype in FA knockout fish . A critical role played by FA proteins in zebrafish gonadogenesis led us to test whether FA proteins were also required for gametogenesis . Many FA patients experience impaired gametogenesis , defective meiosis and sterility [3 , 39] . To this end , we outbred all available FA gene knockout males ( all 17 genes ) and females ( 5 genes ) with WT fish and checked the embryo viability at 24 hours post fertilization ( hpf ) to evaluate the fertility of the mutant fish . Surprisingly , the embryos from all but fancd1hg45/hg45 and fancjhg56/hg56 male knockout outbreeding were found viable , indicating knockout male fish for 15 out of 17 FA genes were fertile ( Fig 7A ) . It appears that , but for fancd1 and fancj , all other FA genes may not be necessary for spermatogenesis in zebrafish . Similarly , viable embryos were observed in all five FA gene knockout female outcrosses ( fanca , fancb , fancm , fanco , and fancq ) indicating these FA genes are not needed for oogenesis in zebrafish ( Fig 7A ) . In fancd1hg45/hg45 male outbreeding , only a small fraction of embryos ( <5% ) were found viable at 24 hpf , indicating a partial sterility phenotype in these fish . With respect to fancjhg56/hg56 male outbreeding , no viable embryos were observed among 25 clutches indicating its essential role in spermatogenesis . To understand the cellular basis for infertility in fancd1hg45/hg45 and fancjhg56/hg56 males , we analyzed their testes by histology . The homozygous knockouts lacked mature spermatozoa in testes , whereas the heterozygous males had normal testes with mature spermatozoa ( Fig 7B and 7C ) . Presence of complete sterility in fancjhg56/hg56 knockout males prompted us to test the fertility of fancjhg57/hg57 males . Surprisingly , the embryos produced by fancjhg57/hg57 males were viable . The observed contrasting phenotypes between the two fancj mutations suggest that one of them may be hypomorphic . The fancjhg56/hg56 fish showed female-to-male sex reversal , the phenotype typical of most FA gene knockouts . The defective fertility phenotype in this line could reflect a critical role of fancj in meiotic homologous recombination . This is in contrast to the fancjhg57/hg57 fish that were both fertile and displayed partial sex reversal phenotype , suggesting a potential hypomorphic variant . At the molecular level both alleles are generated from the same sgRNA and are predicted to cause frameshift mutations with premature truncation of the protein , and both alleles display hypersensitivity to DEB treatment ( Fig 2A ) . Thus , our data demonstrate how phenotypes for knockout lines generated from the same CRISPR/Cas9 target site of a gene can vary , emphasizing the importance of testing multiple mutant lines to identify the phenotypic consequences of a gene knockout .
FA is a genetically and phenotypically heterogeneous disorder with mutations in 22 genes known to cause the disease so far . Here , we report generation and characterization of zebrafish knockouts for all recessively inherited FA genes known at the start of this study , except for FANCS/BRCA1 as its zebrafish homolog has not been identified . Three new FA genes ( FANCU , FANCV , FANCW ) were identified after initiation of our study . A knockout zebrafish model for the only autosomal dominant FA gene ( FANCR/RAD51 ) was also reported recently [36] . In addition to the 17 FA genes , our study targeted zebrafish homologs for two genes encoding FA-associated proteins ( FAAP24 and FAAP100 ) , which are components of the FA core complex that facilitates the ID2 ubiquitination step of the DNA repair pathway . We generated two loss-of-function alleles for nearly all targeted genes ( 17/19 ) enabling evaluation of resulting phenotypes in a reliable manner . In addition , we generated and confirmed viability of eleven combinations of double and triple knockouts , while founder lines to generate many other combinations for multiple gene knockouts are established . This study serves as an integral resource for exploring the FA pathway , and will aid future studies focused on understanding the disease process and the biological processes that become compromised in FA patients , including DNA repair , stem cell maintenance , differentiation of hematopoietic lineages , tumor suppression and aging , among others [1 , 6 , 14–16 , 40] . The ability to perform high throughput CRISPR/Cas9-mediated mutagenesis in zebrafish by a ) targeting multiple genes in groups [29 , 30] , b ) utilizing the CRISPR-STAT method to screen for functional guide RNAs [41] , and c ) adopting a sensitive fluorescent PCR assay for genotyping [42] , prompted us to undertake this large effort . We injected seven pools of sgRNA to generate mutant alleles in 19 FA pathway genes . Our data demonstrate that multiplexing of sgRNAs is an efficient approach to generate both individual and multi-gene mutant fish lines . Multiplexing , instead of independent injections , significantly reduced the fish husbandry costs and space needed to establish mutant lines . To date , zebrafish knockouts for three FA genes , fancd1 , fancl and fancr/rad51 have been reported , however , none of these employed a targeted mutagenesis approach with one exception . Two independent fancd1 mutant lines were identified , one caused by retroviral insertion [34] and another by the ENU ( N-ethyl-N-nitrosourea ) -mediated chemical mutagenesis method [35] , both residing in the large exon 11 . A recent study reported a fancd1 mutant line generated by targeting of exon 8 by CRISPR-Cas9 [43] . A fancl mutant [33] was identified from an insertion-mutagenesis in a Tol2 transposon-mediated enhancer trap screen . Recently , a knockout for the autosomal dominant FA gene , fancr/rad51 , was generated using the ENU-mediated method [36] . The emergence of highly efficient CRISPR/Cas9 technology made it possible for us to efficiently test 19 genes . Our RNA analysis revealed presence of an mRNA carrying the frameshift indel variant in all 36 mutant lines , which is expected to generate truncated proteins . Introducing indel variants in the genomic DNA to create mutant lines can sometime affect splicing by altering the conserved splicing signals such as exonic/intronic splicing enhancers/silencers [44] activating cryptic splice sites . We did observe aberrant splicing in 4/36 mutations , two of which would still result in truncated proteins , while the other two would generate an indel but maintain the reading frame ( Fig 1 ) . Often , close proximity of mutations to the natural splice site could affect canonical splicing . Indeed , one of these four ( fancb_hg42 ) was located 2bp from the nearest natural splice donor site ( S2 Table ) . Two recent reports also evaluated mRNA expression associated with CRISPR/Cas9-induced indel frameshift mutations in zebrafish and did observe a fraction of aberrantly spliced RNA . Specifically , a 7 bp insertion in pycr1a caused exon-skipping leading to 71 bp deletion at the cDNA level [31] , and a 7 bp deletion in exon 3 of smyd1a resulted in utilization of cryptic splice sites in the adjacent exon [45] . The latter study also identified splicing errors associated with zebrafish missense and nonsense variants resulting in frameshift mutants [45] . Sequence variants in genomic DNA causing aberrant splicing , and thus pathogenesis , are increasingly becoming apparent in genetic diseases [46] . In fact , we have reported instances of aberrant splicing in RNA from FA patients carrying sequence variants in the coding ( nonsense , missense , synonymous ) and intronic ( indel , SNP ) [47 , 48] regions . Thus , it is important that the consequences of the putative genomic mutations are characterized at the RNA level , which is critical for proper interpretation of the cause and effect of the variants ( genotype-to-phenotype ) . An ideal way to validate whether a frameshift mutant is indeed null is to demonstrate the absence of the encoded protein . Due to lack of zebrafish antibodies or cross-species reacting antibodies , we could test and show the absence of protein expression in only fancd2 mutants ( S4 Fig ) . However , adopting a recently reported fluorescent mutation reporter assay [31] , we were able to validate several other indel variants , as predicted , did result in premature termination of the reading frame ( S5 Fig ) . Cellular hypersensitivity to DEB treatment is a hallmark of FA patients . We tested the response of homozygous knockout mutant embryos for all FA genes to DEB treatment by inbreeding heterozygous fish . We could clearly demonstrate the homozygous knockout specific deformed phenotype for seven genes ( Fig 2A ) . Presence of FA genes transcripts as early as one hpf has been reported earlier [27] , and the relevance of maternal mRNA and protein in zebrafish embryos has been well documented [49] . This prompted us to speculate that the presence of maternal mRNA may have protected the embryos for some FA gene mutants from displaying the DEB-treatment associated severe malformations . In fact , by incrossing homozygous knockout fish , we did observe the sensitivity of the embryos to DEB treatment . However , this could only be performed for four mutant lines , as female knockout fish were not available for the rest of the FA genes due to female to male sex reversal phenotype ( Fig 5 ) . It is interesting to note that malformations were milder for fancb mutants ( Fig 2C ) , probably due to a transcript variant that would result in an in-frame protein albeit with insertion of nine amino acids ( Fig 1 ) . Altogether , we could test mutant lines for 11/17 FA genes , and demonstrate they are indeed nulls as they all showed DEB hypersensitivity . Among the FA gene mouse models , embryonic lethality was reported for Fancd1 , Fancn , and Fanco knockouts , and for Fancl in a specific strain background [50 , 51] . This is consistent with FA patients carrying pathogenic mutations in FANCD1 and FANCN , which present with severe phenotype and often die at a young age [52 , 53] . All four zebrafish fancd1 mutant lines [34 , 35 , 43] , including the one in this study , have been found to be viable . A fifth fancd1 mutant , zeppelin ( zep ) , has been reported recently , which shows lethality between 6 and 10 dpf . The zep was isolated in a forward screen for kidney mutants in zebrafish and identified as a homozygous recessive lethal allele that causes reduced podocyte numbers , deficient filtration , and fluid imbalance [54] . The zep phenotype was found to be due to a mutation located in a splice acceptor site between exons 20 and 21 resulting in aberrant splicing , and encoding a truncated protein lacking the last 451 amino acids . Unlike the zep mutation in intron 20 , the mutations in the other four fancd1 knockouts , including ours , are located in exons 8 , 10 or 11 . It is tempting to speculate that the larval stage lethality in zep may be due to the toxic effects of a truncated protein that lacks the C-terminal DNA binding domain . Alternatively , the non-lethal phenotype in the other three fancd1 mutants may be due to genetic compensation , hypomorphic alleles , and/or partial complementation by the proteins encoded by the splice variants [55 , 56] . We did observe a small fraction of in-frame deletion transcripts in our fancd1 mutant fish . Only a true fancd1 null lacking complete expression of RNA would provide an unambiguous reliable null phenotype . Except for the fancp-/- fish , where both alleles show smaller body length , visible gross developmental abnormalities were not observed in any other FA gene mutant fish . Co-mutation in fancq did not alter this fancp phenotype . Incidentally , Fancp null mice show similar reduced growth and are born at sub-Mendelian ratios [57] . Growth retardation was observed in mice null for Fanca , Fancc and Fancd2 in certain genetic backgrounds [50] . Reduced body size of knockouts of FANCP orthologs in both zebrafish and mice models may mimic the short stature observed in ~65% of FA patients [58] . Patients with FANCP mutations are rare , however , all seven patients from five FANCP families reported so far do present with growth retardation [59–61] . It is intriguing that loss-of-function in other FA genes does not result in this phenotype in zebrafish . The lack of other gross developmental changes in FA knockout zebrafish models in our study , or by the other groups , could be due to several reasons: redundancy of the pathway , residual function of the mutant proteins , requirement for concomitant loss-of-function mutation in modifier genes , or lack of environmental challenges in a laboratory setting . Using a DNA damaging chemical challenge to induce gene knockout phenotypes in animal models is often necessary and increasingly adopted in various knockout model studies [62] . Most of the FA mouse KO models , do show genomic instability represented by chromosomal breakage only when the knockouts are exposed to DNA crosslinking agents [50 , 51] . Requirement of inactivation of modifier genes was illustrated in mouse Fancd2 mutants that develop severe phenotype when there is a concomitant loss of genes encoding aldehyde catabolism enzymes , ADH and ALDH [63] . Our FA gene knockouts should serve well in future studies in evaluating the effect of modifier genes . We found that female-to-male sex reversal was a common phenotype in FA gene knockouts ( Fig 5 ) , which suggests that FA pathway plays an important role in zebrafish gonadogenesis . Interestingly , complete female-to-male sex reversal was reported in fancd1 , fancl and fancr knockout fish , and concomitant knockout of tp53 rescued the sex reversal phenotype in all three FA gene knockouts [33–36] . In fact , the sex reversal was demonstrated to be due to increased Tp53-mediated germ cell apoptosis at the critical time during sexual fate determination [33] . We also observed rescue of female-to-male sex reversal phenotype when tp53 null mutation was introduced into fancp knockout fish ( Fig 6 ) . Hence , it is tempting to speculate that the sex reversal we observed in all FA gene knockouts may also be due to Tp53-mediated apoptosis of germ cells . Since the sex reversal phenotype was present in all of our mutant lines suggests that the mutants are significantly affecting gene function , consistent with the demonstration that these mutants are indeed null alleles . In FA patients , problems associated with gonadogenesis such as hypogonadism , and infertility are common , particularly male infertility [3 , 64] , and a recent study identified biallelic loss-of-function FANCM mutations as cause of non-obstructive azoospermia [3 , 64] . Previous reports in zebrafish have shown that the homozygous knockouts of fancd1 [34 , 35] and fancr [36] develop as infertile males with meiotic arrest in spermatocytes . It is surprising that infertility is not a common phenotype in many other FA gene knockout fish . Our fancd1 mutants confirm the findings from other two mutants but the male infertility phenotype was incomplete . Unlike the complete sterility observed in previously reported fancd1-/- males , the partial sterility phenotype in our fancd1hg45/hg45 male fish could be due to limited complementation by the less abundant cryptic splice variant predicted to encode a protein lacking 29 amino acids ( Fig 1D and 1E ) . Differences in the level of sterility in fancd1 knockouts could also result from different target mutation sites ( exon 10 in our study vs exons 8 and 11 in others ) . We also report infertility in fancj-/- males but in only one of the two alleles , and the molecular basis for this allelic discrepancy is not clear . Our data clearly demonstrate how phenotypes for a gene knockout can vary for different mutant alleles located at a target site . Hence , caution in interpreting any phenotype obtained from a single mutant allele is warranted , underscoring the importance of testing multiple mutant alleles , ideally at different target sites , to identify a legitimate phenotype for a gene knockout . Based on our data and others , it appears that three FA gene knockouts in zebrafish ( fancd1 , fancj , and fancr ) lead to male infertility phenotypes [33 , 34 , 36] . Interestingly , all three genes participate in the homologous recombination process of the FA pathway , suggesting the recombination repair process mediated by the FANC proteins is active during germ cell development , particularly during meiosis , and defects in this activity can lead to infertility . Our study showed that FA pathway genes play a major role in zebrafish gonadogenesis rather than in gametogenesis , suggesting that hypogonadism among FA patients may lead to the observed increased infertility . CRISPR/Cas9 mediated genome editing is a double strand break repair process , either by non-homologous end joining ( NHEJ ) or by homologous recombination . The former is exploited for mutagenesis , while the latter has a higher potential for therapeutic intervention . A very recent report demonstrates that homologous recombination repair by single-strand template requires FA pathway genes [65] . Our mutants can be used for further characterization of this process , and hence can play a role in developing genome-editing based therapeutic approaches . Taken together , our study adds 32 zebrafish mutant alleles for 17 FA genes using the efficient CRISPR/cas9 technology and extends to encompass nearly all of the known FA genes . These mutant alleles would serve well in the future for exploration of hematopoietic deficiency to understand the bone marrow failure in FA patients . Viability to adult stage observed for all genes enables us to explore biological processes that otherwise would not have been possible as illustrated by the sex reversal and fertility phenotypes . The FA pathway is critical for maintenance of genome integrity , stem cell maintenance and tumor suppression , among others , and we provide resources to study FA pathogenesis as well as to a better understanding of the underlying basic biological functions .
All zebrafish experiments were performed in compliance with the National Institutes of Health guidelines for animal handling and research under NHGRI Animal Care and Use Committee ( ACUC ) approved protocol G-05-5 assigned to RS and G-17-3 assigned to SCC . Wild-type ( WT ) zebrafish strain TAB5 was used for all experiments . Zebrafish husbandry , embryo staging and microinjections were performed as described previously [66] . Two single guide RNAs ( sgRNAs ) per gene , using the criteria indicated in S1 Fig legend , were designed using the ‘ZebrafishGenomics’ track on the UCSC Genome Browser . Synthesis of target oligonucleotides ( Integrated DNA Technologies ) , preparation of mRNA , microinjections , and mutant generation were carried out as described previously [30 , 67] . First , CRISPR-STAT was performed to evaluate target-specific activity of one sgRNA per gene as described previously [41] . Next , second sgRNA was tested for the four genes where the first one showed low to no activity . Mutants were generated by microinjections of pooled sgRNAs to multiple genes ( 1sgRNA/gene chosen based on the CRISPR-STAT data , two to four genes/injection group ) based on their known interactions into the yolk of one cell stage embryos [17–19] . The multiplexing scheme along with the targeted exon and sgRNA sequences for each gene are described in Tables 1 and S1 . Injected fish were grown to adulthood and screened for germline transmission of indel mutations by breeding with WT fish . High throughput founder screening was performed by analysis of eight embryos per founder fish for indel mutations by fluorescent PCR for each of the genes in the injection group . Sequence of primers used for fluorescent PCR is given in S1 Table . M13F adapter sequence ( 5’-TGTAAAACGACGGCCAGT ) was added to the 5’ end of each forward primer , and PIG-tail sequence ( 5’-GTGTCTT ) was added to the 5’ end of each reverse primer as described [42] . Fluorescent PCR ( fPCR ) was performed using the gene specific primer pair and a universal FAM-labeled M13F primer ( 5’-TGTAAAACGACGGCCAGT ) as described previously [42 , 67] . Same primers were used for CRISPR-STAT , founder screening , identification of heterozygous adult fish from the progeny of selected founders , and for subsequent genotyping to perform genotype-phenotype correlations for all experiments . The RT-PCR primers were designed to amplify the exon containing indel mutation along with its flanking exons ( S1 Table ) . The only exception was fancf , which is a single exon gene and therefore , as a control we performed no-RT reactions during cDNA synthesis to rule out genomic DNA contamination . Caudal fin tissues from adult WT and homozygous knockout fish for each gene were obtained by ACUC approved fin clip method . RNA was extracted using standard TRI Reagent ( Ambion ) protocol following tissue homogenization with a Ribolyzer ( MP Biomedicals ) . RNA purification was performed using isopropanol precipitation followed by DNase ( Qiagen ) treatment . RNA was then passed through Zymo clean and concentrator columns ( Zymo Research ) . Random hexamer primer and 1 μg of total RNA were used to synthesize cDNA using Superscript IV First-Strand Synthesis system for RT-PCR ( Invitrogen ) . Upon completion , the reaction mixture was diluted 1:1 with DEPC water , and 4μl of diluted reaction mixture was used as template for RT- PCR reactions using primers for each of the genes ( S1 Table ) . Amplification of actb2 ( Forward primer– 5’-GTATCCTGACCCTGAAGTACCC-3’; Reverse primer– 5’-AGCACAGCCTGGATGGCAACG-3’ ) using 2 μl of diluted reaction mixture was performed as control for cDNA quality . The RT-PCR reactions were performed using KAPA2G Fast HotStart ReadyMix PCR Kit ( KAPABIOSYSTEMS ) as per manufacturer’s instructions , and the products were analyzed on 2% agarose gels . The RT-PCR products were either sequenced directly in case of single band or sequenced after cloning in case of multiple bands . For Sanger sequencing , the PCR products were treated with USB ExoSAP-IT ( Affymetrix ) , and sequencing reactions were carried out with RT-PCR primers using the Bigdye Terminator v3 . 1 Cycle Sequencing Kit ( Applied Biosystems ) and run on ABI3730XL sequencer . The sequencing data was evaluated by aligning it to Danio rerio reference sequence using Sequencher software ( Gene Codes Corporation ) . This assay was performed as described in a recent report [31] . Briefly , primers were designed to amplify the 5’ UTR and a part of coding sequence that includes the mutation site as recommended ( S4 Table ) . RNA was extracted from heterozygous fish and RT-PCR was performed using the SuperScript III One-Step RT-PCR System ( Thermo Fisher Scientific ) with the following conditions: 50 oC for 30 min , 94 oC for 2 min; 40 cycles of 94 oC for 15 sec , 57 oC for 30 sec , 72 oC for 2 min; 72 oC for 10 min . RT-PCR products were then cloned into the GFP reporter vector and sequence verified to identify WT and mutant clones . As a control , we used the RFP reporter plasmid , pCS2-TagRFPT . zf1 [68] . RNA encoding for GFP and RFP reporters were synthesized using the T3 and SP6 mMessage mMachine kit ( Thermo Fisher Scientific ) respectively , according to manufacture instructions with LiCl precipitation . For each mutation , we injected a mix of RNA for the WT-GFP or mutant-GFP reporter ( 200pg ) with the control RFP reporter ( 100pg ) into 1 cell embryos . Embryos were imaged at 1dpf on a Leica M205 with a Leica DFC7000GT camera and LAS X Imaging Software Suite . The embryos generated from pairwise breeding of single gene and multi-gene heterozygote mutant fish were grown to adulthood ( 3–6 months ) . Fin clips from adult fish were processed for DNA extraction using the “Extract-N-Amp” kit ( Sigma-Aldrich ) and used for genotyping by fluorescent PCR method as described [67] . The genotyping data were used to analyze for Mendelian ratios of surviving homozygous knockout fish compared to the homozygote WT and heterozygous fish . Under the null hypothesis of no viability selection , progeny genotypes should conform to an expected Mendelian ratio of 1:2:1 . Deviations from expected number of homozygous knockouts ( 25% ) were tested with goodness-of-fit Chi-square statistical analysis . If the parent fish were heterozygote for mutations in more than one gene , data were analyzed for survival of all possible genotypes expected from these breeding . To get sufficient number of fish genotyped , we analyzed progenies from two breeding for most alleles . To determine the presence of both sexes among surviving adults , all genotyped fish were categorized as males and females and counted . The fertility of homozygous knockout fish for each gene was assessed by breeding them with WT fish . The embryo viability was determined at 24 hpf . If the embryos were viable , 7 embryos were collected to confirm their genotype . Progenies from inbred single or double heterozygote mutant fish were grown to perform standard body length measurements at indicated time period as described [69] . The juvenile fish at 1 mpf were euthanized to perform standard body length measurements and tissue collection for genotyping as described earlier . Adult fish ( 4 mpf ) were genotyped by fin clipping and measured . Standard body length data was grouped based on their genotype and subjected to one-way ANOVA analysis . Zebrafish were euthanized and fixed in 4% formaldehyde at 4°C for a minimum of 24 hours followed by dehydration in 70% ethanol . Specimens were processed for paraffin embedding and preparation of 5 μm H&E-stained sections ( Histoserv ) . Histological section images were captured with an AxioPlan-2 microscope with AxioCam CCD camera ( Zeiss ) using ZEN imaging software ( Zeiss ) . The embryos obtained from indicated breeding crosses were treated with DEB ( Sigma Aldrich ) at indicated concentrations in egg water with methylene blue between 4 and 72 hpf . The embryos obtained from heterozygous mutant crosses were separated at the end of treatment into three groups based on the severity of the observed morphological changes ( normal , moderate and severe ) and genotyped using fPCR as described earlier . Representative images of DEB treated embryos obtained from homozygous mutant inbreeding or outbreeding were taken using LAS X Imaging software on a Leica M205 microscope with a DFC7000 color camera . For Tp53 samples , about twenty-five embryos collected at 24 hpf were dechorionated , deyolked and homogenized in RIPA buffer containing protease inhibitor cocktail ( Thermo Fisher Scientific ) . For Fancd2 samples , soft tissue such as heart , liver , kidney and testis from adult fish were homogenized using TissueRuptor ( Qiagen ) in cell lysis buffer ( Cell Signaling Technology ) containing protease inhibitor cocktail ( Thermo Fisher Scientific ) . The homogenates were centrifuged to pellet and remove cellular debris . The samples were resolved on SDS-PAGE ( 4–15% TGX gels , Bio-Rad ) and transferred onto nitrocellulose membrane ( Invitrogen ) . The antibodies for zebrafish Tp53 ( Abcam; ab77813 ) , human FANCD2 ( Novus Biologicals; NB100-182 ) and β-actin ( Abcam; ab6276 ) were used at a 1:200 , 1:2000 and 1:300 dilutions , respectively . | Deficiencies in repair of DNA damage can cause diseases such as Fanconi anemia ( FA ) , which is characterized by birth defects , bone marrow failure , anemia , leukemia and other cancers . A set of proteins constitute the FA pathway and together orchestrate the DNA repair process . Inactivation of one or more gene ( s ) encoding the proteins of the DNA repair pathway in an animal model would enable us to study the functions of these proteins in maintenance of normal cellular functions and the overall health of an individual in the absence of function . We systematically targeted the FA pathway in zebrafish using CRISPR/Cas9 . We generated 36 fish lines with loss-of-function mutations in 19 FA pathway genes and showed that all survive to adulthood . We did not notice obvious morphological changes except in fancp gene-inactivated fish , which were smaller in length . However , all mutant fish were either exclusively or in majority male . Unlike reduced fertility among FA patients , all adult mutant fish were fertile , except for the fancd1 and fancj knockout males . These mutant zebrafish will serve as a huge resource for the scientific community to study the role of FA proteins in fish development , DNA repair , and as models for FA disease . | [
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] | 2018 | Multiplexed CRISPR/Cas9-mediated knockout of 19 Fanconi anemia pathway genes in zebrafish revealed their roles in growth, sexual development and fertility |
Bruton’s tyrosine kinase ( Btk ) is a Tec family non-receptor tyrosine kinase that plays a critical role in immune signaling and is associated with the immunological disorder X-linked agammaglobulinemia ( XLA ) . Our previous findings showed that the Tec kinases are allosterically activated by the adjacent N-terminal linker . A single tryptophan residue in the N-terminal 17-residue linker mediates allosteric activation , and its mutation to alanine leads to the complete loss of activity . Guided by hydrogen/deuterium exchange mass spectrometry results , we have employed Molecular Dynamics simulations , Principal Component Analysis , Community Analysis and measures of node centrality to understand the details of how a single tryptophan mediates allostery in Btk . A specific tryptophan side chain rotamer promotes the functional dynamic allostery by inducing coordinated motions that spread across the kinase domain . Either a shift in the rotamer population , or a loss of the tryptophan side chain by mutation , drastically changes the coordinated motions and dynamically isolates catalytically important regions of the kinase domain . This work also identifies a new set of residues in the Btk kinase domain with high node centrality values indicating their importance in transmission of dynamics essential for kinase activation . Structurally , these node residues appear in both lobes of the kinase domain . In the N-lobe , high centrality residues wrap around the ATP binding pocket connecting previously described Catalytic-spine residues . In the C-lobe , two high centrality node residues connect the base of the R- and C-spines on the αF-helix . We suggest that the bridging residues that connect the catalytic and regulatory architecture within the kinase domain may be a crucial element in transmitting information about regulatory spine assembly to the catalytic machinery of the catalytic spine and active site .
Kinase domains consist of a bi-lobal structure , the N- and C-lobes , which together create the catalytic site to transfer a phosphate from ATP to a substrate hydroxyl ( Fig 1A ) [1 , 2] . Transition between active and inactive kinase structures involves concerted motions of specific regions of secondary structure . For example , the αC-helix in the N-lobe adopts a ‘C-out’ conformation in the inactive state and shifts to a ‘C-in’ conformation when the kinase is activated . This transition is triggered by phosphorylation of specific residues in the activation loop that cause a switch in a number of electrostatic interactions . Moreover , the αF-helix in the C-lobe supports two separate regulatory motifs ( the Catalytic ( C ) -spine and Regulatory ( R ) -spine ) [3–5] ( Fig 1B ) . The residues that make up these spines are conserved and their proper assembly is required for kinase activation . Identification of these spines has provided a model for kinase activation that explains how phosphorylation at regulatory sites on the activation loop triggers subsequent conformational rearrangements that stabilize the active kinase domain [3–5] . The Tec family of non-receptor tyrosine kinases , Btk , Itk , Tec , Bmx and Rlk , are regulators of immune cell function [6 , 7] . Tec kinase mutations have been linked to immunodeficiencies and lymphoproliferative diseases [8 , 9] . For example , genetic defects leading to single amino acid changes in Btk cause X-linked agammaglobulinemia or XLA , a condition characterized by a lack of mature B cells and hence a complete lack of circulating antibodies . A clear understanding of Tec family regulation is a critical step needed prior to developing improved immunotherapies . Consistent with the R-spine model , we have found that individual mutation of each of the R-spine residues in Itk disrupts catalytic activity [10] . However , we have also found that the isolated Itk and Btk kinase domains have reduced activities compared to the corresponding full-length enzymes [11] . This suggests that even when these kinase domains are requisitely phosphorylated at the regulatory tyrosine , the active conformation ( containing an assembled R-spine ) is not sufficiently stable . Indeed , crystal structures of the phosphorylated Itk kinase domain reveal a disassembled R-spine [12] . Stabilization of the catalytically competent conformation must require specific contacts between residues outside of the kinase domain and the kinase domain itself to overcome the innate conformational preference of the isolated Tec family kinase domain for the inactive state [11 , 13] . Mutagenesis experiments identified a conserved tryptophan ( W395 in Btk ) in the region preceding the kinase domain that is absolutely required for kinase activity ( Fig 1C ) . This tryptophan plays the opposite role in the Src family kinases where it instead functions as a wedge , preventing the inward motion of αC-helix to the active ‘C-in’ state , thus stabilizing the inactive conformation of the kinase domain . Quite unlike the Tec family kinases ( Fig 1C ) , mutation of this conserved tryptophan in Src kinases relieves the steric hindrance imposed by its side-chain resulting in a shift in the conformational equilibrium to the active state [11 , 14] . In our earlier work , we proposed that the tryptophan ‘caps’ the top of the regulatory spine of the Tec family kinases providing essential contacts that stabilize the assembled R-spine structure [11] . Here , we combine results from hydrogen-deuterium exchange mass spectrometry ( HDXMS ) and Molecular Dynamic ( MD ) simulations to develop a more detailed mechanistic understanding for how the linker tryptophan drives the conformational equilibrium and dynamic sampling of the Btk kinase domain toward the active state .
To probe the role of W395 in stabilizing the active form of the Btk kinase domain , we first assessed the effect of the W395A mutation within the fragment of Btk containing the kinase domain and N-terminal linker , residues 382–659 ( Fig 2A ) . The wild type sequence is referred to as the Btk linker-kinase and was compared throughout this work to the same Btk fragment bearing the single tryptophan to alanine mutation: Btk ( W395A ) linker-kinase . The loss of activity observed upon mutation of W395 to alanine in the context of the Btk linker-kinase fragment ( Fig 2B ) mirrored that of full length Btk ( Fig 1C ) , making this fragment a reasonable model for studies to investigate the role of W395 in controlling Btk catalytic activity . HDXMS allows detection of backbone amide hydrogens for each amino acid in the protein ( except proline ) permitting direct comparison of the combined effects of solvent accessibility and hydrogen-bonding of amide N-H groups between two proteins . Btk linker-kinase and Btk ( W395A ) linker-kinase were subjected to identical experimental conditions allowing for exchange of deuterium with the labile amide hydrogens [15] . The H/D exchange reaction was quenched and the proteins were proteolyzed to yield peptides for analysis by mass spectrometry . Differences in deuterium exchange between wild type and the W395A mutant of Btk linker-kinase localize to the αC-helix and the N-terminal region of the activation segment ( Fig 2C ) with no significant differences throughout the rest of the kinase domain ( see Fig A in S1 Text ) . For the peptides derived from the αC-helix and activation segment , deuterium uptake was greater for the wild type Btk linker-kinase protein compared to the W395A mutant ( Fig 2D and 2E ) . This observation is consistent with previous H/D exchange data showing that a more active kinase undergoes greater conformational sampling and thus greater exchange with bulk solvent [16 , 17] . HDXMS data for wild type Btk linker-kinase and Btk ( W395A ) linker-kinase also suggest that the linker and N-terminal region of the kinase domain are not perturbed by the W395A mutation ( Fig 2F ) . The sequence adjacent to W395 ( E396IDPKDLT403 ) was protected from exchange at early time points suggesting that this region associates with the N-lobe regardless of the presence or absence of the tryptophan side chain . Crystal structures of active and inactive Btk kinase domain containing the linker region indicate a single structural difference in this region; the W395 side chain adopts distinct chi1 rotamers in each structure ( Fig 2G ) . These data suggest that in one rotameric configuration , W395 might regulate catalytic activity by increasing the dynamic motions of the adjacent kinase domain and specifically promoting more frequent conformational sampling of the αC-helix and activation segment near the active conformation , while the other rotamer moves the W395 side-chain away from the kinase domain thereby altering the environment of the αC-helix and thus the kinase domain dynamics . Mutation of W395 to alanine mimics the inactive state by removing the large side chain from the proximity of the αC-helix . To gain further insight into the allosteric role of Btk W395 , we next compared all-atom MD simulations between the active Btk linker-kinase domain fragment and the inactive mutant Btk ( W395A ) linker-kinase domain . MD simulations are widely used to investigate the differences in conformational dynamics of mutant and wild type protein structures [14 , 18 , 19] . The application of MD simulations in this study aims to capture the effect of a single point mutation on the active state of the Btk linker-kinase domain . PDB ID 3K54 [20] was used to derive the starting active conformation of Btk linker-kinase domain . A detailed description of model building and mutation of W395 to alanine is provided in Methods . Three replicates of MD simulations were carried out for 200 ns for each protein model and , guided by the HDX data , we compared the RMSD changes for the αC-helix and the activation segment ( Fig 3 ) . The αC-helix remained in the active “C-in” conformation for the duration of the simulation of wild type Btk linker-kinase ( Fig 3A and 3E ) but transitioned from the active “C-in” to inactive “C-out” conformation at early time points in the simulation of inactive Btk ( W395A ) linker-kinase ( Fig 3B–3D and 3F ) . The αC-helix transition captured in the Btk ( W395A ) linker-kinase simulation led to loss of the K430/E445 salt bridge and concomitant changes in the electrostatic contacts between R544 and pY551 ( Fig 3F ) . In contrast , the distance between the K430/E445 and R544/pY551 side chains remained constant throughout the wild type Btk linker-kinase domain simulations ( Fig 3E ) . Consistent with conformational changes localized to the regulatory regions in the N-lobe , the RMSD of total backbone atoms of Btk linker-kinase domain and Btk ( W395A ) linker-kinase showed only small changes throughout the simulation time ( Fig 3A–3D ) . The N-terminal region of the activation segment ( residues 540–547 ) also behaved differently in simulations of wild type Btk linker-kinase versus ( W395A ) linker-kinase domain ( Fig 3A–3D ) . The activation segment sampled conformations near the active state during the simulation of the Btk linker-kinase domain ( Fig 3A ) . In contrast , the activation segment in Btk ( W395A ) linker-kinase drifted to a greater extent from the starting active conformation as indicated by the greater RMSD from its starting active conformation ( Fig 3B–3D ) . The DFG motif at the N-terminal end of the activation segment retained its active conformation during the simulation of the Btk linker-kinase domain but reverted to the conformation seen in the crystal structure of inactive Btk in simulations of Btk ( W395A ) linker-kinase ( Fig 3F ) . The activation loop as a whole , however , did not transition into the inactive conformation seen in the crystal structure of inactive Btk ( 3GEN ) likely due to the length of simulation time and the fact that the activation loop tyrosine , Y551 , is phosphorylated in the simulations ( Fig 3F ) . Overall , the conformational changes observed in the simulations of Btk ( W395A ) linker-kinase domains suggest that the mutant kinase is not stable in the active conformation , consistent with the experimental observation that the side-chain of W395 plays a critical role in maintaining the active conformation of the Btk kinase domain . Principal Component ( PC ) Analysis ( Fig 4 , see Figs B and C in S1 Text ) reveals the important motions in the system that might otherwise be obscured by the small fluctuations within a trajectory [21] . The first few PCs can capture a large fraction of the variance in the data and thus represent the dominant motions . We calculated the root mean-square inner product ( RMSIP ) between the first 10 PCs from each of the trajectories for Btk linker-kinase and of trajectories for Btk ( W395A ) linker-kinase domain to determine how well the PC subspace overlaps between the different replicates . Large RMSIP values were seen between the subspaces covered by first 10 PCs from each of the replicates for both Btk linker-kinase and Btk ( W395A ) linker-kinase domain simulations ( Btk linker-kinase domain , rep1 vs rep2: 0 . 73 , rep1 vs rep3: 0 . 7 , rep2 vs rep3: 0 . 68 . Btk ( W395A ) linker-kinase domain , rep1 vs rep2: 0 . 68 , rep1 vs rep3: 0 . 66 , rep2 vs rep3: 0 . 64 ) , indicating that there is high similarity between the sets of PCs derived from each of the individual replicates . The first three PCs in Btk linker-kinase and Btk ( W395A ) linker-kinase domain simulations captured 43 . 37% and 79 . 8% , respectively , of the total variance observed in the simulation data ( Fig 4A and 4C ) . The dominant motion within Btk linker-kinase domain , as captured by the first three dominant principal components include an opening-closing motion of the N- and C-lobes around a hinge ( Fig 4B , PC2 ) . A similar ‘breathing’ motion was described for other active kinases [4 , 22 , 23] , suggesting this is a shared feature of catalytically competent kinases and may be responsible for the greater amide NH accessibility observed for the active protein with HD exchange methods . Indeed , this ‘breathing’ motion is considered important for the structural rearrangement of the αC-helix and activation segment to assemble the active site and is considered necessary for the release of ADP after the reaction is complete [4 , 24] . Overlap between PCs derived from the three replicates of each Btk linker-kinase shows that high overlap exists between PCs capturing the ‘breathing’ motion ( see Fig D in S1 Text ) . In contrast , the dominant mode in the Btk ( W395A ) linker-kinase domain simulation , captured almost entirely by its PC1 , shows a combination of twisting and translation motion of the N- and C-lobes ( Fig 4D ) quite similar to that seen in simulations of other inactive kinases [22 , 23] . Overall , differences in PCs are consistent with the conclusion that W395A alters the global motions of the Btk kinase domain . PCA was also performed by combining the three simulation replicates of Btk linker-kinase together with the Btk ( W395A ) linker-kinase domain by aligning to the same reference structure to compare the overlaps between the simulation trajectories along the PC1-PC2-PC3 of this collective subspace ( see Fig D in S1 Text ) . It is clear from the distribution of the trajectories that the mutant Btk ( W395A ) linker-kinase domain ( see Fig D in S1 Text ) samples a sub-space that is mostly different from that sampled by the wild-type Btk linker-kinase domain ( see Fig D in S1 Text ) but does include sampling of a part of the sub-space similar to the wild-type Btk linker-kinase . PCA provided a broad picture of the relative motions of the N- and C-lobes for the wild type structure and for the mutant W395A . To identify dynamic sub-segments within each lobe of the Btk kinase domain , we next examined the correlation of motions of residue pairs within the kinase domain of Btk linker-kinase and the ( W395A ) linker-kinase mutant . Cα coordinates were used for this analysis , as coarse-grained models have proven valuable in capturing the intrinsic dynamics of proteins [25 , 26] . The cross-correlation coefficients for Btk linker-kinase and Btk ( W395A ) linker-kinase were used to build dynamic cross-correlation maps to examine the differences in the correlated motions that remain within 10 Å for 75% of the simulation time ( see Fig E in S1 Text ) . The 10 Å cutoff was chosen as it has been found to be the optimal cutoff for modeling interactions in coarse grained models as well as for comparison of our results with community analysis results of other active kinases such as PKA [27] . The cross-correlations were then used to build a correlated network of residues; represented as a set of connected circles ( communities ) with the weight of the lines connecting each community proportional to the degree of their correlation ( Fig 5 , see Fig F in S1 Text ) . The residues of wild type Btk linker-kinase and Btk ( W395A ) linker-kinase clustered into distinct communities ( Fig 5A and 5B ) , reflecting difference in the dynamic sub-segments of the active versus inactive kinase domain . Detailed summaries of the communities are provided in Fig G in S1 Text . Where possible , we have labeled the communities ( Com ) in Btk linker-kinase in a manner similar to those described by McClendon and co-workers in their community analysis of PKA [27] . Community clustering based on cross-correlations identified two major communities , ComA , and ComC , in the Btk linker-kinase domain N-lobe ( Fig 5A ) . All of the linker residues including W395 are part of ComA , which also contains beta strands β1 , β2 , β3 , β4 and β5 , regulatory spine residue L460 and the Gly-rich loop . ComC includes the important αC-helix and the R-spine residue M449 . Separate from the αC-helix , the αC- β4 loop segregates with ComD , which extends into the C-lobe and includes the hinge region of the kinase domain . The catalytic loop HRD motif including the R-spine residue H519 and the N-terminus of the activation segment , which includes the regulatory spine residue F540 ( part of the DFG motif ) are clustered in ComP . The grouping of disparate regions of the kinase domain into communities A , C , D and P points to dynamic coordination in the active Btk linker-kinase domain . Indeed , the assembled R-spine residues reside in four different communities demonstrating the correlation of this structure to different regions in the active kinase domain . It is immediately evident that there are fewer communities within Btk ( W395A ) linker-kinase domain and the correlations between these communities are weaker compared to those of the wild type Btk linker-kinase protein ( Fig 5B ) . This result suggests that a mutation that inactivates the kinase domain may do so by reducing as well as dampening correlated motions within the protein . The integrity of ComC was lost in the Btk ( W395A ) linker-kinase domain , where the αC-helix itself is divided into two dynamically distinct communities ComL and ComE . The αC- β4 loop in the inactive Btk ( W395A ) linker-kinase is in ComE , which is separated from the hinge region in ComI . The R-spine residues within Btk ( W395A ) linker-kinase are dynamically isolated in ComE , which is only weakly linked to other structurally significant regions of the kinase domain ( Fig 5B ) . Comparing community analysis of the wild type and mutant Btk kinases indicates that loss of the single W395 side-chain results in a breakdown of the “signal integration” function [27] [28] of the αC-helix across the two lobes of the kinase with R-spine assembly and dynamics being adversely affected . To identify specific residues responsible for the allosteric communication between W395 and the rest of the kinase domain , we next computed the node-betweenness centrality index for each residue within both the wild type Btk linker-kinase ( Fig 6A ) and the Btk ( W395A ) linker-kinase ( Fig 6B ) . Centrality index is a measure of the number of shortest paths that pass through a node , which is a direct measure of the contribution of the node to the total communication flow in the system [29 , 30] . High centrality values correlate with the importance of these nodes in the transmission of information through the network . This analysis therefore identifies residues that act as hubs in the allosteric communication pathway transmitting the activating effect of W395 throughout the Btk kinase domain . Four residues , Y476 , M477 , L522 and F583 within the active Btk linker-kinase domain exhibit high centrality while in Btk ( W395A ) linker-kinase domain only two residues , Y476 and G480 , are above the same threshold centrality value ( Fig 6A and 6B ) . In wild type active Btk the hub residues are located in two regions , Y476 and M477 appear to complete the C-spine and wrap around ATP pocket in the N-lobe ( Fig 6D and 6E ) and L522 and F583 are situated between the base of the C- and R-spines in the C-lobe ( Fig 6D and 6E ) . The location of L522 and F583 , in particular , suggest a bridging role where these residues might function to communicate R-spine assembly to the C-spine and the ATP bound active site . Along these lines it is interesting to note that while M477 and L522 are 14Å apart and are located in different lobes of the kinase domain , they both belong to ComD ( Fig 5A ) suggesting a central , and correlated , role in the allosteric dynamics of kinase activation . The now well recognized C- and R-spines are a shared feature of the kinase family and so we wished to assess whether similar bridging residues would be detected in another active kinase domain . Simulation data acquired previously for the Src family tyrosine kinase , Lck [17] were used to compute the centrality index values for each residue of the active Lck kinase domain . A set of Lck residues with high centrality values emerged ( Fig 6C ) that are quite similar to those found for Btk ( Fig 6A ) . The high centrality Lck residues include Y318 and M319 that correspond exactly to Y476 and M477 in Btk ( Fig 6F ) . As well , Lck residues R366 and S425 are located between the base of the C- and R-spines in a manner similar to L522 and F583 in Btk . Two additional Lck residues in the C-lobe , W424 and W477 , reach the high centrality threshold and the C-spine residues I370 and L371 exhibit high centrality in Lck . The fact that a similar arrangement of high centrality residues are identified in two different active kinases and that a subset of these residues bridge the R- and C-spines provides further support for a mechanistic model for activation whereby regulatory spine assembly may be dynamically communicated to the catalytic apparatus of the active site .
Tryptophan 395 is a positive regulator of Btk kinase activity [11] . In contrast to the negative regulatory role of the same tryptophan in the Src family kinases [14 , 31] , mutation of this single residue abolishes the catalytic activity of the 70 KDa full-length Btk kinase . Our experimental and computational findings provide an explanation for the positive allostery observed for the Tec family and suggest that a particular conformation of the W395 side-chain promotes long range correlated dynamic motions throughout the kinase domain that are essential for catalytic activity . MD simulations indicate that the Btk αC-helix samples the ‘C-in’ state for the majority of the trajectories when W395 adopts the rotameric conformation observed in the crystal structures of active Btk . In contrast , the absence of the W395 side-chain , achieved either by a rotameric shift or by mutation to alanine , favors the ‘C-out’ state . The conformational preferences of the αC-helix are linked to the overall motions of the N- and C-lobes of the kinase domain , as well as to the degree of correlation between residues throughout the kinase domain . Based on the computational work presented here and by others [27 , 32 , 33] , and previous analyses of active and inactive kinases by NMR spectroscopy [34–36] , it is becoming clear that the active state of a kinase domain requires a specific highly dynamic , interconnected structure . The inactive kinase exhibits substantially less cohesion , with fewer correlated motions throughout the kinase domain when motions are compared with those of the active form . Moreover , the hydrogen/deuterium exchange data indicate that specific regions of the wild type Btk linker-kinase domain sample more open conformations compared to the Btk ( W395A ) linker-kinase mutant , consistent with the view that inactivating mutations suppress the dynamics required for catalytic activity . While it may be tempting to explain allostery in terms of a simple pathway leading from the W395 side-chain to the kinase active site , our findings , as well as the work of others [27 , 32 , 37] , argue against a simple linear allosteric pathway . In a recent review focusing on dynamics and allostery within the protein kinases [38] , Kornev and Taylor drew an elegant analogy between the kinase domain and the violin , invoking the vibrations responsible for the tone and pitch emanating from a violin as a way to think about the role of molecular dynamics in controlling the catalytic activity of the enzyme [38] . Small , localized changes on the violin , such as placing a finger on a string , can have a dramatic effect on the resulting pitch by altering the vibrations of the entire instrument . Amino acid mutations are similarly likely to affect protein function by altering the long range correlated motions throughout a structure , and changes at particular positions may critically affect function . Indeed , our data suggest that the inactivating W395A mutation substantially dampens the dynamics of the Btk kinase domain in much the same way that muting restricts vibrations throughout a violin by reducing the volume of the notes . Community analysis [39] provides insight into changes in correlated motions that result from ligand binding and/or amino acid mutation [27 , 32 , 33 , 40 , 41] . The set of communities identified within Btk are similar to those defined previously for PKA [27] . In both , the communities contain residues from distant regions of the primary structure and connections between certain communities are strong , indicating that correlations within an active kinase are spread throughout the kinase domain . Analyses of inactive Btk mutants reveal fewer communities that are less coherent indicating that the correlated motions typical of an active kinase are absent in the inactive state . We have extended our analysis separately to the Btk linker-kinase and the Btk ( W395A ) linker-kinase to include computation of the residue specific node-betweenness centrality index [42] . A higher centrality indicates that a residue serves as a node or hub , playing a greater role in information flow in the network . In the active Btk linker-kinase and Lck kinase domains , specific residues across the primary structure are characterized by high centrality values suggesting their involvement in the flow and transmission of dynamical information in the active state . The similarity in tertiary structural arrangement of these residues in both kinases is compelling and two of the high centrality residues in each active kinase are perfectly positioned between the two well-characterized C- and R-spines suggesting a bridging role . In terms of kinase activation , the dynamical consequences of the R-spine assembly ( triggered by activation loop phosphorylation and a shift to the ‘C-in’ state ) may be transmitted to the catalytic machinery of the kinase domain via these bridging residues , thereby integrating assembly and catalysis within the active kinase . Sequence conservation within each kinase family underscores the importance of the bridging residues and for Btk it is noteworthy that all four high centrality residues are sites of XLA mutations . Whether these XLA mutations specifically disrupt communication between the R- and C-spines to prevent kinase activation or simply alter the overall fold and stability of the Btk kinase domain remains to be determined . As was the case with the R- and C-spines , the true importance of the high centrality residues in each kinase must be tested experimentally . It is generally challenging to clearly delineate the structural consequences of deleterious point mutations . Yet understanding precisely how specific mutations disable enzymes can provide the information necessary to pursue new strategies toward modulating protein functions for therapeutic applications . Here , by combining experiment with pertinent simulations we establish the detailed requirements for a particular rotameric conformation of a native tryptophan for activity and relate this small region of the structure to the dynamics of the entire catalytic unit . We have seen how a single point mutation can destroy a protein’s activity by modifying its dynamics and allostery . The results found here are consistent with the growing realization of the importance of conservation for functional dynamics [1 , 38 , 43 , 44] , and the present case provides strong support for this view .
Baculoviral and bacterial constructs , protein expression and purification conditions are described elsewhere [11 , 45] . The W395A mutation was introduced using site-directed mutagenesis ( Stratagene ) and verified by sequencing . In vitro kinase assays were performed as previously described [35] . Duplicate deuterium labeling experiments were initiated with an 18-fold dilution of an aliquot ( 63 pmoles ) of Btk linker-kinase or Btk ( W395A ) linker-kinase into a buffer containing 99 . 9% D2O , 20 mM Tris , 150mM NaCl , 10% glycerol , pD 8 . 01 . The labeling reaction was quenched by addition of quench buffer ( 150 mM potassium phosphate ( pH 2 . 47 ) ) at 10 secs , 1 min , 10 mins , 1 hour , and 4 hours . Quenched samples were immediately injected into a Waters nanoACQUITY with HDX technology [46] for online pepsin digestion and ultra-performance liquid chromatography ( UPLC ) separation of the resulting peptic peptides , and analyzed as reported previously [17] . All mass spectra were acquired with a WATERS SYNAPT G2si HDMS mass spectrometer . The data were analyzed with DynamX 3 . 0 software . Relative deuterium amounts for peptides covering 97 . 9% of the protein backbone were calculated by subtracting the average mass of the undeuterated control sample from that of the deuterium-labeled sample for isotopic distributions corresponding to the +1 , +2 , +3 , or +4 charge state of each peptide . Data were not corrected for back exchange and are reported as relative values [15] . Differences larger than 0 . 7 Da are considered obvious , according to the statistical criteria for relative HDXMS measurements previously described [47] . The coordinates of Btk linker-kinase ( PDB ID: 3K54 , amino acids: 392–659 ) were obtained from the RCSB PDB databank [20] . The coordinates of the bound inhibitor were deleted from the PDB file . The regions missing from the electron density maps of 3K54 were modeled with the Loop Model module in MODELLER as follows [17]: amino acids 435–441 , which include the β3- αC loop and the N-terminus of the αC-helix , were modeled using Csk ( PDB ID: 1K9A , chain B ) [48] and Lck ( PDB ID:3LCK ) [49] as templates; amino acids 542–558 which form the activation loop are modeled based on Btk ( PDB ID:1K2P ) [50] since 1K2P contains the activation loop resolved in the open conformation . Finally , none of the available crystal structures of Btk contain the DFG motif in the active conformation and so we used the structure of the active Lck kinase domain ( PDB ID:3LCK ) to model the active DFG-in conformation into Btk 3K54 . The mutate_model module in Modeller was used to mutate W395 to alanine in Btk linker-kinase domain model to derive Btk ( W395A ) linker-kinase domain . Phospho-Tyrosine patch TP2 was used to introduce phosphorylation of Y551 in both models . The NAMD 2 . 8 [51] program with CHARMM27 [52] force field was used to initiate all-atom MD simulations of Btk linker-kinase and Btk ( W395A ) linker-kinase . The proteins were solvated in a periodic water box with 15 Å buffering distance between protein surface and the box , using the TIP3P explicit water model . 150 mM concentration of ions ( Na+ and Cl- ) was added to charge neutralize the system . The systems were equilibrated and simulated in the NPT ( Normal Pressure Temperature ) ensemble at 310 K and 1 atm , using Particle-Mesh Ewald for long-range electrostatics . The cutoff used for the van der Waals and short-range electrostatics calculations was 12 Å and hydrogen bonds were kept rigid using the ShakeH algorithm . The timestep used was 2 fs . The prepared simulation systems were minimized according to the following steps: ( a ) 20 picoseconds ( ps ) minimization of the entire system followed by 50 ps of equilibration by holding the protein rigid , allowing only water molecules and Na+ and Cl- ions to move . ( b ) The modeled loops which included the Gly-rich loop and the activation segment as well as the β3-αC-helix loop were subjected to a very short minimization of 2 ps to remove any steric clashes . ( c ) The entire system was minimized , gradually releasing harmonic constraints on all protein heavy-atoms . The temperature of the system was then gradually raised from 200 K to 310 K with harmonic constraints on all protein heavy-atoms , in 5 K increments over a total of 90 ps . Subsequently , the harmonic constraints were gradually released and the system was equilibrated for a total time of approximately 1 ns . The production MD was run for 200 ns each . The simulations were run in triplicates . VMD [53] was used to visualize the simulations trajectory and calculate Root Mean Square Deviation ( RMSD ) as well as salt-bridge and hydrogen-bonding distances . For RMSD calculations , superposition is based on the C-lobe ( N479-S659 ) using the energy-minimized structure as a reference . MATLAB ( The Mathworks , Inc . ) was used to plot RMSD and distances obtained from VMD . Figures were generated with PyMOL[54] . Cα coordinates of Btk linker-kinase and Btk ( W395A ) linker-kinase domain from 200ns MD trajectory are the input for PCA . PC analysis was carried out as described before [21] . MATLAB was used for the above calculations . Directions of motion in PC1-PC3 were mapped onto the structure using the modevectors script in pymol [54] . To compare the overlap between the simulation trajectories , the PC scores were projected along the PC1-PC2-PC3 subspace using MATLAB , after combining all the simulation trajectories and aligning them to the same reference structure . Root Mean Square Inner Products ( RMSIP ) between the first 10 PCs in each of the replicate of Btk linker-kinase and Btk ( W395A ) linker-kinase domains were calculated using the Bio3d [55] in R [56] as described before [21] . Cross-correlation coefficients indicate whether points in a system move in the same or opposite direction and are correlated or move in orthogonal directions , in which case the method does not pick up correlations . The Cα atoms of each protein were aligned to the first frame of the trajectory . The dot products of the displacements Δr of Cα atoms are used in the correlation coefficients ( Cij ) as follows: Ci , j=<Δri•Δrj> ( |Δri|2|Δrj|2 ) 1/2 where Δri denotes the displacement of residue i from the mean . The pairwise cross-correlation coefficients between pairs of residues form the elements of the cross-correlation matrix . The values of the cross-correlation coefficients range between -1 and 1 , with -1 denoting negative-correlation , +1 denoting positive-correlation and 0 denoting no-correlation . The matrix is depicted as a dynamic cross-correlation map ( DCCM ) . The Girvan-Newman clustering algorithm [39] was used to identify communities of residues from the set of correlated residues obtained above . Cross correlation coefficients ( Cij ) whose absolute values are below the set cutoff of 0 . 5 were ignored in building the unfiltered DCCM . A proximity/contact map filter was applied for building the correlation network of residues for those within 10 Å of one another for at least 75% of simulation time [27] . A network is the interconnected set of amino acid residues or nodes . Communities are identified using the edge “betweenness” approach , which is defined as the number of shortest paths between a pair of nodes ( amino acid residues ) . The size of the community is the number of amino acids that have a high degree of correlated motion ( depicted by size of circle ) , while the thickness of the edges/links connecting the communities denotes the extent of correlation . The middle 100 ns ( from 50ns-150ns of total of 200ns ) of simulation data was used to calculate the centrality in both Btk linker and Btk ( W395A ) linker-kinase domains . Our rationale in using this time-window is that we wished to pick up the communication hubs ( amino acids ) , which mediate the conformational change from the active to inactive state as the most prominent conformational change in RMSD is observed in the Btk ( W395A ) linker-kinase domain simulation during this time interval . The corresponding simulation time-scale ( 50ns-150ns ) for Btk linker-kinase domain was also analyzed . We decided to not include simulation trajectory beyond 150 ns as it introduced noise in the node-betweenness calculations . Node-betweenness is an approach complementary to edge-betweenness , wherein the number of unique shortest paths passing through a node are counted . The cross-correlation analysis , community clustering and node-betweenness calculations , were carried out using the dccm and cna functions in Bio3d package [55] in R [56] . | Bruton’s tyrosine kinase ( Btk ) belongs to the Tec family of protein tyrosine kinases , and plays a crucial role in the signaling pathway in B-cells . Alteration of Btk activity results in the serious immunological disorder , X-linked agammaglobulinemia . Btk is a multi-domain protein and the activity of the kinase domain is regulated by the adjacent non-catalytic domains , which mediate their effect by means of a conserved tryptophan residue . In this work , we have investigated the mechanism of regulation by this tryptophan residue , W395 , in the linker preceding the Btk kinase domain . Using hydrogen-deuterium exchange mass spectrometry and molecular dynamics simulations we identify structural elements within the kinase domain that are required for function by transmitting the allosteric effects of W395 . Molecular Dynamics simulations further guided us to delineate the kinase domain into dynamically correlated sets of residues using community analysis , thereby identifying the important communication nodes that connect the various elements of the kinase domain required for function . The analyses performed indicate clearly how the W395A mutant changes the communication pathway required for function . | [
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] | 2016 | Dynamic Allostery Mediated by a Conserved Tryptophan in the Tec Family Kinases |
Fas-associated factor 1 is a death-promoting protein that induces apoptosis by interacting with the Fas receptor . Until now , FAF1 was reported to interact potentially with diverse proteins and to function as a negative and/or positive regulator of several cellular possesses . However , the role of FAF1 in defense against bacterial infection remains unclear . Here , we show that FAF1 plays a pivotal role in activating NADPH oxidase in macrophages during Listeria monocytogenes infection . Upon infection by L . monocytogenes , FAF1 interacts with p67phox ( an activator of the NADPH oxidase complex ) , thereby facilitating its stabilization and increasing the activity of NADPH oxidase . Consequently , knockdown or ectopic expression of FAF1 had a marked effect on production of ROS , proinflammatory cytokines , and antibacterial activity , in macrophages upon stimulation of TLR2 or after infection with L . monocytogenes . Consistent with this , FAF1gt/gt mice , which are knocked down in FAF1 , showed weaker inflammatory responses than wild-type mice; these weaker responses led to increased replication of L . monocytogenes . Collectively , these findings suggest that FAF1 positively regulates NADPH oxidase-mediated ROS production and antibacterial defenses .
Innate immune cells are the first barrier encountered by invading microbial pathogens . Among these cells , phagocytes such as macrophages and neutrophils play key roles in host protection against bacterial infection . Upon recognition and phagocytosis of bacteria , phagocytes produce reactive oxygen species ( ROS ) that kill and inactivate bacteria directly . This mechanism is known as the respiratory burst . NADPH oxidase , one of several ROS sources , is critical for this process [1 , 2] . The redox center of phagocytic NADPH oxidase is a heterodimer comprising transmembrane-associated protein subunits p22phox and gp91phox ( Nox2 ) . This heterodimer , also known as flavocytochrome b588 , forms a phagocytic NADPH oxidase complex together with the cytosolic regulatory subunits p67phox , p47phox , p40phox , and the small GTPase Rac [1 , 3 , 4] . The ROS generated by the NADPH oxidase complex are not only toxic to the cell but also participate in host defense responses such as NF-kB activation and release of proinflammatory cytokines [5] . A life-threatening genetic disorder called chronic granulomatous disease ( CGD ) , in which the phagocytic NADPH oxidase is dysfunctional , leads to life-threatening bacterial and fungal infections . CGD is caused by mutations in any one of the genes that encode subunits of the phagocytic NADPH oxidase complex [6–8] . Upon phagocytosis of bacteria , toll-like receptors ( TLRs ) , which are transmembrane receptors that play a critical role in innate immune recognition of pathogens , act as a first line of host defense [9 , 10] . The TLR family in humans and mice includes more than ten different members , all of which have been studied extensively with respect to infection . Phagocytes express all TLR members , stimulation of which induces diverse biological processes , including inflammation , antigen presentation , and direct bactericidal effects [10 , 11] . The interplay between these TLR recognition and activation of NADPH oxidase during phagocytosis of bacteria is well characterized . Especially , interaction between Nox2 and TLR2 is required for ROS production and inflammatory responses during mycobacteria infection [12–14] . Moreover , TLR2 mediates expression of Nox2 in microglia during peripheral nerve injury [15] . Nox4 is also required for TLR4-mediated ROS production in response to lipopolysaccharide ( LPS ) [16] . Except for bacterial infection , Nox4 is necessary for generation of macrophage migration inhibitory factor during parasite infection [17] . Recent studies show that the TLR4-Nox1 redox signaling axis plays a role in metastasis of colon cancer and lung cancer cells [18 , 19] . Fas-associated factor 1 ( FAF1 ) was identified initially in a yeast two-hybrid assay using the cytoplasmic domain of Fas protein as bait [20] . FAF1 , which contains a Fas-interacting domain ( FID ) , a death effector domain-interacting domain ( DEDID ) , and a C-terminal domain [21] potentiates Fas-mediated apoptosis as a member of the death-inducing signaling complex [22 , 23] . FAF1 interacts with different molecules and is involved in a variety of biological processes; it plays a role in regulating cell death and/or tumor progression , ubiquitination-mediated proteosomal degradation , chaperones , NF-kB signaling , and interferon signaling [24–29] . To better understand the biological role of FAF1 , we examined the relationship between NADPH oxidase and FAF1 in host defense against bacterial infection . We show that FAF1 is a crucial positive regulator of the phagocytic NADPH oxidase complex , which promotes ROS production by macrophages in response to L . monocytogenes infection . FAF1 controls phagocytic NADPH oxidase-mediated inflammatory responses upon L . monocytogenes infection by interacting with p67phox , thereby inhibiting bacterial growth .
Based on a previous study of the role of FAF1 in antiviral responses against infection by RNA virus [27] , we asked whether FAF1 is also involved in responses to bacterial infection . To examine in vivo host responses to infection by L . monocytogenes , FAF1+/+ and FAF1gt/gt mice were infected intraperitoneally with L . monocytogenes ( 5 × 105 CFU per mouse ) and serum cytokine levels , bacterial load , and proinflammatory gene expression in the spleen and liver were measured at 24 h post-infection ( hpi ) . The bacterial load in the spleen and liver of FAF1gt/gt mice was approximately 10-fold and 3-fold higher , respectively , than that in FAF1+/+ mice ( Fig 1 , panel A ) . Serum cytokine levels were also reduced markedly in FAF1gt/gt mice ( Fig 1 , panel B ) . Expression of proinflammatory genes in the spleen and liver of FAF1gt/gt mice was also lower than that in FAF1+/+ mice ( Fig 1 , panels C-D ) . To determine whether these effects were mediated by peritoneal macrophages in response to L . monocytogenes infection , FAF1+/+ and FAF1gt/gt mice were infected with L . monocytogenes intraperitoneally and peritoneal macrophages ( PMs ) were isolated at 24 hpi . Expression of proinflammatory cytokines and chemokines by these cells was measured by quantitative real-time PCR . Expression of mRNA encoding IL-6 , CXCL10 , and RANTES was significantly lower in PMs from FAF1gt/gt mice than in those from FAF1+/+ mice ( S1 Fig ) . These data suggest that FAF1 plays an important role in host defense against L . monocytogenes infection in vivo . Next , to determine whether FAF1 is involved in inflammatory responses , we examined induction of FAF1 in macrophages exposed to L . monocytogenes . Importantly , mRNA expression of FAF1 was induced with 2–3 folds at 15 or 60 m post-infection ( mpi ) with L . monocytogenes in Raw264 . 7 cells , suggesting that FAF1 responds to bacterial infection at early time ( S2 Fig , panel A ) . Also , FAF1 responded to high MOI of bacterial infection in mouse bone marrow-derived macrophages ( BMDMs ) and Raw264 . 7 cells ( S2 Fig , panels B-C ) . At early time points after L . monocytogenes infection , host defense is regulated by secretion of several cytokines and chemokines , including IL-6 , IL-12 , and RANTES [30 , 31] . Therefore , we examined the effect of FAF1 on proinflammatory cytokine secretion by BMDMs and resident PMs against L . monocytogenes infection or TLR2 ligands . First , expression of FAF1 was confirmed by immunoblotting of extracts from BMDMs or PMs isolated from FAF1+/+ and FAF1gt/gt mice ( S3 Fig , panels A-B ) . Next , cells were infected with L . monocytogenes or treated with zymosan or bacterial lipoprotein ( BLP ) . The supernatants were harvested at 12 or 24 hpi to measure IL-6 and IL-12 by ELISA . As results , FAF1 knockdown reduced cytokine production by both BMDMs ( Fig 1 , panels E-F ) and PMs ( S3 Fig , panels C-D ) . Next , we generated control and FAF1-knockdown murine macrophage cells ( Raw264 . 7 ) using lentiviruses harboring non-specific or FAF1-specific small hairpin RNA ( shRNA ) . Expression of FAF1 was then determined by immunoblot analysis ( S4 Fig , panel A ) . Next , cells were infected with L . monocytogenes or treated with zymosan or BLP and supernatants harvested at 12 or 24 hpi to measure cytokine secretion . Consistent with the results obtained from primary cells , shRNA-mediated knockdown of FAF1 led to a marked reduction in secretion of proinflammatory cytokines IL-6 and IL-12 upon stimulation via TLR2 ( Fig 1 , panels G-H ) . Additionally , production of chemokines regulated upon activation ( i . e . , normal T cell expressed and secreted ( RANTES ) and monocyte chemoattractant protein ( MCP ) -1 ) was lower in FAF1-knockdown cells than in control cells ( S4 Fig , panels B-C ) . Collectively , these results suggest that FAF1 expression has a marked effect on host defense responses against L . monocytogenes . To determine whether FAF1 activates proinflammatory signaling pathways , we performed immunoblot analysis to examine expression of activated forms of molecules related to the NF-κB and MAPK signaling pathways in BMDMs isolated from FAF1+/+ and FAF1gt/gt mice infected with L . monocytogenes . The result showed that knockdown of FAF1 leads to a marked reduction in phosphorylation of p65 ( NF-κB ) , IκBα , and SAPK/JNK , but had no effect on activation of p38 MAPK or Erk1/2 ( Fig 2 , panel A ) . In agreement with this , knockdown of FAF1 in Raw264 . 7 cells suppressed activation of p65 ( NF-κB ) , IκBα , and SAPK/JNK , but not p38 or Erk1/2 MAPK ( Fig 2 , panel B ) . Furthermore , to measure expression of proinflammatory genes , BMDMs and resident PMs isolated from FAF1+/+ and FAF1gt/gt mice were infected with L . monocytogenes and subjected to real-time PCR at 12 hpi to detect Il6 , Nos2 ( iNOS ) , Ptgs2 ( COX-2 ) , Cxcl10 , and RANTES . The expression of these genes in FAF1-knockdown BMDMs cells were lower than those in wild-type cells ( Fig 2 , panel C ) or resident PMs ( S5 Fig ) . Consistent with this , similar results were obtained from FAF1-knockdown Raw264 . 7 cells ( Fig 2 , panel D ) . Taken together , these data suggest that FAF1 plays a role in inflammatory responses against L . monocytogenes infection . To identify the target protein of FAF1 , large-scale cultured HEK293 cells were used for immunoprecipitation with an anti-FAF1 antibody , followed by mass spectrometry analysis . The result identified NADPH oxidase activator 1 ( NoxA1 ) ( S6 Fig ) . NoxA1 regulates activation of Nox1 , which can generate ROS and is expressed at high levels in colon cancer cells [3] . As a homolog of NoxA1 , p67phox acts mainly as an activator of Nox2 in phagocytes . Moreover , there is a high degree of domain homology between NoxA1 and p67phox , although the proteins show only 28% amino acid identity [3 , 32 , 33] . Based on these reports , we asked whether FAF1 interacts with p67phox to regulate ROS production in phagocytes . Mock- or L . monocytogenes-infected Raw264 . 7 cells were harvested at various time points and cell lysates were immunoprecipitated with an anti-FAF1 antibody , followed by immunoblotting with antibodies against components of the phagocytic NADPH oxidase complex ( Fig 3 , panel A ) . The result indicated that FAF1 transiently interacts with p67phox , p47phox , and p40phox at 30 mpi with L . monocytogenes ( Fig 3 , panel A ) . To test whether FAF1 expression affects those interaction , efficiency of FAF1-specific siRNA was priorly determined in Raw264 . 7 cells or BMDMs for further experiments ( S7 Fig , panels A-B ) . FAF1 knockdown-BMDMs showed a weak interaction between both molecules as well as lower expression of p67phox compared with control BMDMs upon L . monocytogenes infection ( S8 Fig , panel A ) . Similar result was obtained following siRNA-mediated knockdown of FAF1 in Raw264 . 7 ( S8 Fig , panel B ) . Moreover , confocal microscopy analysis exhibited that FAF1 is translocated to phagosomal membranes upon zymosan treatment in BMDMs where it co-localizes with p67phox ( Fig 3 , panel B ) . Additionally , immunoprecipitation with an anti-V5 antibody using FAF1-overexpressing Raw264 . 7 cells showed strong interaction between ectopic FAF1 and endogenous p67phox without stimulation , suggesting that FAF1 might present high affinity to p67phox ( Fig 3 , panel C ) . Next , we performed CFU assay to examine the growth rate of intracellular L . monocytogenes in BMDMs following siRNA-mediated knockdown of FAF1 . Knockdown of FAF1 showed a significant increase of bacterial growth compared to control BMDMs ( Fig 3 , panel D ) . This result encouraged us to verify that reduced ROS production and inflammation in FAF1-knockdown cells might result in a more favorable environment for L . monocytogenes replication . To investigate whether FAF1 affects ROS production upon L . monocytogenes infection , we used fluorescence absorbance to measure ROS production following siRNA-mediated knockdown of FAF1 in BMDMs . As expected , H2O2 and O2-produced by FAF1-knockdown BMDMs were significantly lower than those produced by control BMDMs in response to L . monocytogenes infection ( Fig 3 , panel E ) . Similar results were obtained from Raw264 . 7 cells following siRNA-mediated knockdown of FAF1 ( Fig 3 , panel F ) . Moreover , knockdown of FAF1 exhibited lower ROS production upon stimulation with zymosan in BMDMs , Raw264 . 7 , and PMs compared to control cells . ( S9 Fig , panels A-C ) . ROS acts as a signal transduction mediator in response to diverse stimuli [5] . To determine further whether proinflammatory cytokine production in response to L . monocytogenes infection or TLR2 signaling correlated directly with ROS generation in the presence or absence of FAF1 , we measured NO and IL-6 levels in supernatants from BMDMs ( Fig 3 , panel G ) and Raw264 . 7 cells ( Fig 3 , panel H ) stimulated with L . monocytogenes or zymosan in the presence/absence of ROS inhibitors [N-acetyl-L-cysteine and diphenyleneiodonium] . As expected , treatment with ROS inhibitors reduced NO production toward nearly basal level despite of stimulation with L . monocytogenes or zymosan . Secretion of IL-6 by these cells also fell markedly , regardless of FAF1 expression . In other words , impaired ROS production resulted in no significant difference in cytokine secretion by wild-type and FAF1-knockdown macrophages . Knockdown of FAF1 attenuates IκBα degradation and NF-κB activation , but not phosphorylation of IKKs , suggesting that FAF1 indirectly regulates the inflammatory responses via ROS production on TLR2 signaling ( S10 Fig ) . It was also supported by evidences that FAF1 augments inflammatory responses depending on NADPH oxidase complex ( S11 Fig , panels A-B ) . Likewise , knockdown of FAF1 led to increased bacterial growth than control in BMDMs . However , there was no differences under DPI or NAC treatment , which suggests that FAF1 inhibits bacterial growth by mediating ROS production ( Fig 3 , panel I ) . Taken together , these findings demonstrate that FAF1 enhances inflammatory responses and intracellular bacterial clearance via ROS generation by interacting with p67phox upon infection by L . monocytogenes . FAF1 contains three well characterized domains , the FID , DEDID , and C-terminal domains [21 , 24 , 29] . To define which domain of FAF1 interacts with p67phox , we generated GST-tagged domain constructs and performed GST pull-down assays in HEK293T cells . p67phox bound strongly to both the DEDID and C-terminal domains of FAF1 ( Fig 4 , panel A ) . The region of FAF1 responsible for interaction with p67phox was narrowed down to amino acids 330–489 ( Fig 4 , panel B ) . In the reverse experiment , GST-tagged domain constructs of p67phox were generated , and GST pull-down assays were performed in HEK293T cells to determine which domain of p67phox interacts with FAF1 . FAF1 bound to the 4X tetratricopeptide repeat ( TPR ) domain of p67phox ( Fig 4 , panel C ) . A diagram of the domains mediating binding between FAF1 and p67phox is shown in panel D ( Fig 4 , panel D ) . Next , a mutant construct of FAF1 with a deletion in amino acids 330–489 was generated ( Δ330–489 ) . This mutant showed weak binding to endogenous p67phox and p47phox compared with wild-type FAF1 by immunoprecipitation with an anti-V5 antibody in Raw264 . 7 cells ( Fig 4 , panel E ) . Furthermore , ectopically expressed p67phox co-localized with wild-type FAF1 but not FAF1 Δ330–489 in HEK293T cells ( Fig 4 , panel F ) . Taken together , these data indicate that amino acids 330–489 of FAF1 comprise the critical region that mediates interaction with the 4X TPR domain of p67phox . As described above , we identified the binding site through which FAF1 interacts with p67phox and found that a deletion mutant of this region ( FAF1 Δ330–489 ) was unable to bind to p67phox . To determine whether FAF1 Δ330–489 lost the ability to promote inflammatory responses due to the weak interaction with p67phox , we generated Raw264 . 7 cells stably overexpressing a control vector , wild-type FAF1 , or FAF1 Δ330–489 . The expression level of FAF1 in each stable cell line was determined by western blotting ( S12 Fig , panel A ) . The cells were then stimulated with TLR2 ligands , including L . monocytogenes , zymosan , and BLP , and levels of proinflammatory cytokines and chemokines in the supernatants were measured . As expected , cells expressing FAF1 Δ330–489 showed reduced secretion of proinflammatory cytokines and chemokines in response to TLR2 signaling compared with cells expressing wild-type FAF1 ( Fig 5 , panels A-B and S12 Fig , panels B-C ) . We next evaluated the activation of molecules involved in NF-κB and MAPK signaling in L . monocytogenes-infected Raw264 . 7 cells . Cells expressing wild-type FAF1 showed enhanced activation of the NF-κB and SAPK/JNK pathways upon L . monocytogenes infection , as previously observed ( Fig 2 , panels A-B ) , while activation of these signaling molecules was not altered in cells overexpressing FAF1 Δ330–489 compared with control cells ( Fig 5 , panel C ) . In addition , IL-6 , O2 , and NO production were impaired in cells overexpressing FAF1 Δ330–489 compared with cells overexpressing wild-type FAF1 . Cytokine secretion was not induced in the presence of ROS inhibitors , with no significant difference between individual cell lines ( Fig 5 , panels D-E ) . While the growth of intracellular bacteria in cells overexpressing wild-type FAF1 was lower than in control cells , cells overexpressing FAF1 Δ330–489 exhibited a similar level of bacterial growth as control cells ( Fig 5 , panel F ) . These findings indicate that the effects of FAF1 on inflammatory responses , and intracellular bacterial clearance through ROS generation are dependent on its interaction with p67phox . Among NADPH oxidase regulatory proteins , p67phox has a critical role in the activation of NADPH oxidase [4 , 34] . To determine whether FAF1 affects phagocytic NADPH oxidase activity , Raw264 . 7 cells overexpressing control vector , wild-type FAF1 , or FAF1 Δ330–489 were infected with L . monocytogenes , and a chemiluminescence assay was performed to measure NADPH oxidase activity . The result showed that overexpression of wild-type FAF1 augments the phagocytic NADPH oxidase activity , whereas overexpression of FAF1 Δ330–489 doesn`t ( Fig 6 , panel A ) . This finding suggested that amino acids 330–489 is the critical region for the interaction with p67phox , which results in increased ROS production in response to L . monocytogenes infection . We also found that expression of FAF1 leads to higher and persistent expression of p67phox in a binding-specific manner ( Fig 6 , panel B ) . Overexpression of FAF1 induces a bit more mRNA expression of p67phox and p47phox without stimulation ( S13 Fig ) . Additionally , Raw264 . 7 cells overexpressing control vector , wild-type FAF1 were treated with mock or zymosan/cycloheximide and used for immunoblot analysis for expression levels of p67phox and p47phox over time . This result showed that overexpression of FAF1 increases the stability of p67phox and p47phox upon zymosan treatment ( Fig 6 , panel C ) . The intensity of the protein bands on the blot shown in Fig 6 , panel D is quantitated ( Fig 6 , panel D ) . Furthermore , to check the localization of p67phox around phagosomes depending on expression level of FAF1 , BMDMs were treated with zymosan particles for 30 min following siRNA-mediated knockdown of FAF1 , then followed by confocal microscopy using anti-p67phox antibody ( Fig 6 , panel E ) . As correlated with prior data , knockdown of FAF1 exhibited considerable decrease of p67phox localized to phagosomal membranes compared to control , which supports evidently that FAF1 potentiates the stability of p67phox in phagosomes . Collectively , these results suggest that FAF1 in macrophages effectively augments p67phox stability in response to infection with L . monocytogenes , resulting in increased phagocytosis-mediated NADPH oxidase activity .
FAF1 ( Fas-associated factor 1 ) , a member of the Fas death-inducing signal complex , modulates a variety of biological processes by interacting with diverse molecules [24–26] . However , the role of FAF1 in host defense against bacterial infection remains unclear . Here , we report that FAF1 is a positive regulator that increases activity of the phagocytic NADPH oxidase complex , resulting in production of ROS and in activation of NF-κB signaling , inflammatory responses , and antibacterial activity upon L . monocytogenes infection . First , FAF1gt/gt mice exhibited reduced serum cytokine levels , reduced inflammatory gene expression , and increased bacterial burden during L . monocytogenes infection . Second , primary macrophages ( BMDMs and PMs ) isolated from FAF1gt/gt mice showed decreased ROS production and inflammatory responses as well as bacterial clearance than macrophages from FAF1+/+ mice upon L . monocytogenes infection or TLR2 stimulation . Consistent with these data , knockdown of FAF1 in Raw264 . 7 cells also showed significantly reduced ROS production , NF-κB activation and inflammatory responses , upon L . monocytogenes infection . Third , FAF1 transiently interacted strongly with the p67phox-p47phox-p40phox complex at early time points after L . monocytogenes infection in macrophages , and FAF1 region comprising amino acids 330–489 was responsible for interaction with the TPR domain of p67phox . Finally , interaction between FAF1 and p67phox stabilized p67phox and increased activity of phagocytic NADPH oxidase upon L . monocytogenes infection . Collectively , these findings strongly suggest that FAF1 plays a crucial role in promoting antibacterial responses by interacting with p67phox in macrophages during intracellular microbial infection . NADPH oxidase and dual oxidase induce ROS production by various cells and tissues in response to growth factors , cytokines , and pathogen-mediated signals [1] . Among these , the phagocyte NADPH oxidase is a multi-component complex in which the membrane glycoprotein gp91phox ( known as NOX2 ) is tightly associated with p22phox; this complex is activated via association with cytosolic regulatory proteins such as p67phox , p47phox , p40phox , and the small GTPase Rac , resulting in ROS generation [1 , 3 , 4] . Based on homology to gp91phox ( Nox2 ) , the Nox family of NADPH enzymes comprises seven members: Nox1 through Nox5 , plus Duox1 and Duox2 [35] . All gp91phox-related enzymes ( except gp91phox ( Nox2 ) ) belonging to the Nox family are non-phagocytic enzymes expressed in epithelial or endothelial cells within diverse tissues and organs [1] . ROS generated by these NADPH oxidases take part in biological processes such as cell signaling , hormone biosynthesis , and host innate immune responses [5 , 36] . In particular , ROS play essential roles in phagocyte-mediated defense against bacterial infection; ROS kill engulfed pathogens directly , or indirectly by activating intracellular signaling pathways related to inflammatory responses , which then protect the host . ROS are necessary to eliminate intracellular bacteria such as mycobacteria , Listeria , and Salmonella , efficiently [37] . Recognition of pathogens by TLRs is the first line of host innate defense; indeed , interaction between TLRs and NADPH oxidase in phagocytes has been well studied . For example , Yang et . al . , report that Nox2 is essential for TLR2-dependent inflammatory responses and for intracellular control during mycobacterial infection . They showed that Nox2 and TLR2 interact directly during mycobacterial infection [13 , 14] . Moreover , the interplay between TLR4 and NADPH oxidases such as Nox4 or Nox1 was studied in non-phagocytic cells [16 , 38] . However , lipopolysaccharide ( LPS; a TLR4 agonist ) also activates NADPH oxidase in phagocytes indirectly by increasing association of gp91phox ( Nox2 ) with regulatory proteins in plasma membrane [39] . Here , we demonstrated that FAF1 is a crucial regulator of the phagocytic NADPH oxidase ( Nox2 ) complex required for ROS production by macrophages in response to L . monocytogenes infection as well as TLR2 stimulation . We also examined whether FAF1 regulates inflammatory responses in macrophages stimulated by TLR4 . As results , TLR4-mediated cytokine secretion by BMDMs isolated from FAF1gt/gt mice was lower than that by cells from FAF1+/+ mice ( S14 Fig , panels A-B ) . These results suggest that FAF1 also activates signaling pathways related to TLR4 stimulation , as proposed by DeLeo et . al . However , further studies demonstrating a detailed mechanism of how FAF1 controls TLR4 signaling pathway are needed . Nox2 in resting phagocytes is inactive; however , it is activated by phagocytosis of invading bacteria , leading to ROS production and their subsequent effects on host defense ( e . g . , killing bacteria and regulating intracellular signaling ) . Once bacteria are recognized by host TLRs , NADPH oxidase Nox2 ( gp91phox ) heterodimerizes with p22phox at the phagocyte membrane and is rapidly activated by cytosolic regulatory proteins [1 , 3 , 4] . These p22phox and cytosolic regulatory proteins ( p67phox , p47phox , p40phox , and the small GTPase Rac ) are indispensable for regulation of NADPH oxidase; indeed , increasing evidence suggests that it is important to control NADPH oxidase subunits to ensure appropriate ROS generation . For example , RUBICON interacts with p22phox , thereby increasing ROS production in response to infection by Gram-positive bacteria [12] . Moreover , Nox-dependent ROS production occurs in Parkinson’s disease ( autosomal recessive , early onset ) 7 ( Park7 ) -p47phox [40] . Our findings suggest that FAF1 is a key molecule that regulates activation of NADPH oxidase via strong interaction with p67phox . As noted above , mass spectrometry analysis identified the NoxA1 protein as an interacting protein of FAF1 . NoxA1 is expressed at high levels by colon epithelial cells and is responsible for activation of Nox1 ( and thereby for subsequent ROS production ) [1 , 3 , 33] . p67phox is a homolog of NoxA1 expressed by phagocytes . Thus , we hypothesized that FAF1 interacts with p67phox to regulate ROS generation in macrophages . In this study , we found that FAF1 interacts with p67phox at an early time point after L . monocytogenes infection . Moreover , amino acids 330–489 of FAF1 are required for interaction with p67phox . Conversely , FAF1 interacted with the TPR domain ( amino acids 1–155 ) of p67phox . This domain , which comprises four 34 amino acid-long TPR motifs , is involved in a variety of protein-protein interactions [4 , 32 , 41 , 42] . In macrophage cell lines stably overexpressing wild-type FAF1 or FAF1 Δ330–489 , we found that overexpression of wild-type FAF1 but not FAF1 Δ330–489 increased NADPH oxidase activity , ROS production , proinflammatory cytokine production , and antimicrobial activity . Ultimately , interaction between FAF1 and p67phox facilitated stabilization of p67phox and increased activity of NADPH oxidase upon L . monocytogenes infection . These results suggest that regulation of phagocytic NADPH oxidase by FAF1 is dependent on binding to p67phox . Consequently , we demonstrated that FAF1 positively regulates the NADPH oxidase 2 complex via stabilization of p67phox . FAF1 interacts potentially with many different proteins and functions as a negative and/or positive regulator in a variety of biological possesses [25 , 26 , 43] . Previous studies report that FAF1 homologs suppress antibacterial immunity in Drosophila and Locusta migratoria [44 , 45] . In addition , Park et al . showed that FAF1 suppresses IKK activation and nuclear translocation of NF-κB in fibroblasts [29 , 46] . However , we clearly demonstrate that FAF1 acts as a positive regulator of antibacterial responses by regulating ROS production . In particular , we identified the physiological role of FAF1 in defense responses against L . monocytogenes infection in FAF1+/+ and FAF1gt/gt mice . FAF1gt/gt mice attenuates bacterial clearance due to reduced inflammatory responses . We also have focused on the role of FAF1 in phagocytes such as macrophages in vitro . Raw264 . 7 cells in which FAF1 was knocked down , as well as BMDMs and resident PMs isolated from FAF1gt/gt mice , showed lower ROS production , proinflammatory responses , and bacterial killing activity than FAF1+/+ mice upon L . monocytogenes infection . In addition , activation of molecules involved in NF-κB signaling was markedly reduced in FAF1-knockdown cells when exposed to L . monocytogenes . However , the upstream molecules responsible for FAF1 activation upon L . monocytogenes infection or TLR2 stimulation remain unclear . To assess this , further studies are necessary to examine the detailed molecular mechanisms ( e . g . , phosphorylation of FAF1 ) that operate in macrophages under infectious conditions . In summary , we demonstrated that FAF1 is a critical positive regulator of the phagocytic NADPH oxidase ( Nox2 ) complex responsible for ROS generation by phagocytes upon L . monocytogenes infection or TLR2 stimulation . FAF1 interacts directly with p67phox and stabilizes p67phox , thereby triggering NADPH oxidase-mediated ROS production , release of proinflammatory cytokines , and bacterial clearance in response to infection by L . monocytogenes . Taken together , the results suggest a plausible mechanism involving interaction between p67phox and FAF1 and increases our understanding of molecules that control ROS signaling and antibacterial defense responses against L . monocytogenes infection or TLR2 stimulation .
All animal experiments were managed in strict accordance with the Guide for the Care and Use of Laboratory Animals ( National Research Council , 2011 ) and performed in BSL-2 and BSL-3 laboratory facilities with the approval of the Institutional Animal Care and Use Committee of Bioleaders Corporation ( Reference No . , BLS-ABSL-16-002 ) and Chungnam National University ( Reference No . , CNU-00763 ) . Zymosan ( tlrl-zyn ) , Pam3CSK4 ( tlrl-pms ) were purchased from Invivogen . DPI ( D2926 ) , NAC ( A9165 ) , Cycloheximide ( C7698 ) , DHE ( D7008 ) , Amplex red and peroxidase were purchased from Sigma . DCFH-DA and pHrodo Red Zymosan A Bioparticles conjugate ( P35364 ) were obtained from Molecular probe . For western blot analysis , specific antibodies for p-IKKα/β ( 2697 ) , IKKβ ( 8943 ) , p-JNK ( 4668 ) , JNK ( 9258 ) , p-NF-κB p65 ( 3033 ) , NF-κB p65 ( 4764 ) , p-Erk1/2 ( 9101 ) , Erk1/2 ( 9102 ) , p-p38 ( 4631 ) , p38 ( 9212 ) , p-IκBα ( 2859 ) , IκBα ( 4812 ) and p67phox ( 3923 ) were purchased from Cell Signaling Technology . Antibodies for FAF1 ( sc-393965 ) , p47phox ( sc-14015 ) , IKKα ( sc-7606 ) , β-actin ( sc-47778 ) , GST ( sc-138 ) were purchased from Santa Cruz Biotechnology . Anti-p67phox antibody ( ab109366 ) was purchased from abcam . Anti-V5 antibody ( 46–0705 ) was purchased from Invitrogen life technology . The anti-FAF1 monoclonal antibody was kindly provided by Dr . Eunhee Kim ( Chungnam National University , Daejeon , Korea ) . L . monocytogenes ( KVCC-BA0000087 ) was from Korean Veterinary Culture Collection ( KVCC ) , and grown at 37°C in Brain Heart Infusion ( BHI ) broth medium ( BD 237500 ) . Log phase bacteria ( O . D . value , 0 . 6–0 . 8 ) were used for all assay . Cultures were aliquoted and stored at -80°C . To determine bacterial titer ( Colony-forming unit , CFU ) , bacteria thawed was diluted 10-fold . Each diluent was plated on BHI agar ( BD 241830 ) and incubated at 37°C for one day . FAF1+/+ and FAF1gt/gt mice on a C57BL/6 background were kindly provided by Dr . Eunhee Kim ( Chungnam National University , Daejeon , Korea ) . A hypomorphic allele , designated FAF1gt/gt , was generated by a gene-trap insertion in intron 8 [47] . All mice were bred in pathogen-free condition . Offspring were genotyped by PCR as previously described [27] . Sex-matched mice ( six-week-old ) were intraperitoneally infected with L . monocytogenes ( 5 × 105 CFU/mouse ) . Liver , spleen , peritoneal macrophage and serum were collected to determine the bacterial load , cytokines or chemokines levels or mRNA levels of cytokines or chemokines as described below . FAF1 plasmid was kindly provided by Dr . Eunhee Kim ( Chungnam National University , Daejeon , Korea ) . To generate plasmid constructs with GST expressing vector , FAF1 and its mutants or p67phox and its mutants were amplified by PCR and inserted into pEBG vector . For construction of V5-tagged expression plasmid , FAF1 , FAF1 Δ330–489 and p67phox were amplified by PCR and inserted into pIRES-V5 . Raw264 . 7 cells , HEK293T cells , BMDMs and PMs were maintained in Dulbecco’s Modified Eagle’s medium ( Gibco ) supplemented with 10% FBS ( Thermo-Hyclone ) and antibiotic-antimycotic ( Gibco ) at 37°C in 5% CO2 . To establish stable expressing cell line , Raw264 . 7 cells were transfected with empty vector or V5-tagged FAF1 wild-type or V5-tagged FAF1 Δ330–489 using Lipofectamine 2000 ( Invitrogen ) , then selected with 2μg/ml puromycin ( Gibco ) containing culture media for 2 weeks . To generate FAF1 knockdown cell lines , Raw264 . 7 were infected with lentivirus containing non-specific shRNA or FAF1-specific shRNA in the presence of 8μg/ml polybrene ( Sigma AL118 ) , and then selected with 2μg/ml puromycin for 2 weeks as previously described [27] . Resident peritoneal macrophages were obtained by flushing peritoneal cavity of FAF1+/+ and FAF1gt/gt mice with HBSS w/o phenol red as previously described [48] . BMDMs were isolated from FAF1+/+ or FAF1gt/gt mice and cultured for 6 days in medium containing 20 ng/ml recombinant mGM-CSF ( Creagen ) as previously described [27] . For silencing of FAF1 gene expression , the pGIPZ lentiviral vector , which contains FAF1-specific shRNA sequences was purchased from Open Biosystems . ( http://www . openbiosystems . com ) . Lentiviruses were produced as previously described [27] . In brief , HEK293T cells were transiently transfected with packaging plasmids ( psPAX2 and pMD2 . VSV-G ) and pGIPZ containing non-specific shRNA or FAF1-specific shRNA sequences using Lipofectamine 2000 . At 48–72 hr post-transfection , virus-containing media was collected and filtrated ( 0 . 45 μm filter , Millipore ) . The sequence of the mouse FAF1-specific siRNA #1 ( duplex ) were as follow , 5`-CCG CCU UCA UCA UCC AGC C-3`and 5`-GGC UGG AUG AUG AAG GCG G-3` . The mouse FAF1-specific siRNA duplex #2–4 ( 14084–1 , 14084–2 , and 14084–3 ) were purchased from Bioneer Corp . The mouse p47phox-specific siRNA ( sc-36157 ) was purchased from Santa Cruz Biotechnology . A non-targeting siRNA was used as a control . Cells were transfected with duplex siRNA using Lipofectamine RNAiMAX ( Invitrogen ) , according to the manufacturer`s protocol , then incubated for 36 hrs before stimulation . For immunoprecipitation , Raw264 . 7 cells or BMDMs were lysed with RIPA buffer containing protease inhibitor cocktail ( Roche ) . Lysates were incubated with a primary antibody overnight at 4°C , followed by incubation with protein A/G agarose ( Santa Cruz Biotechnology ) for 3hrs at 4°C . Then immunoprecipitates were washed with 1% nonidet P-40 for 3 times . For GST-pull down assay , HEK293T cells were transiently transfected with the indicated plasmids , and at 36hr post-transfection , were lysed with RIPA buffer containing protease inhibitor cocktail ( Roche ) . Lysates were pre-cleared by sepharose 6B ( GE Healthcare ) for 3hrs at 4°C , followed by incubation with glutathione ( GSH ) sepharose 4B ( GE Healthcare ) overnight at 4°C . Precipitated beads were washed with 1% nonidet P-40 for 3 times . Whole cell lysates ( WCLs ) were prepared using Radio-immunoprecipitation assay ( RIPA ) lysis buffer ( 50mM Tris-HCl , 150mM NaCl , 0 . 5% sodium deoxycholate , 1% IGEPAL , 1mM NaF , 1mM Na3VO4 , proteinase inhibitor cocktail ) . Samples were separated by SDS-PAGE and transferred onto a PVDF membrane ( Bio-Rad ) using Trans-Blot semi dry transfer cell ( Bio-Rad ) . Membranes were blocked for 1hr in 5% bovine-serum albumin with TBST or 5% skim milk within PBST , followed by incubation with primary antibody overnight at 4°C . Next day , membranes were washed with TBST or PBST , and incubated at room temperature with HRP-conjugated secondary antibody . Then , membranes were washed 3 times with TBST or PBST , followed by developing with Western blotting detection reagents ( GE healthcare , ECL select Western Blotting Detection Reagent ) . HEK293 cells were lysed with RIPA buffer containing protease inhibitor cocktail ( Roche ) . Lysates were incubated with anti-FAF1 antibody overnight at 4°C , followed by incubation with protein A/G agarose ( Santa Cruz Biotechnology ) for 3hrs at 4°C . Then immunoprecipitates were washed with 1% nonidet P-40 for 3 times and separated by PAGE gels , followed by Coomassie blue staining . Protein bands were excised from the gel and identified by Q-TOF mass spectrometer . ELISA was performed to detect the secreted cytokines and chemokines in sera or cell culture supernatants . Mouse IL-6 ( BD biosciences , 555240 ) and mouse IL-12 ( BD biosciences , 555165 ) , RANTES ( Invitrogen ) , MCP-1 ( Invitrogen ) were used for analysis according to the manufacturer’s protocols . The oxidative fluorescent dye 20μM CM-H2DCFDA ( Molecular probe ) , 20uM Amplex red ( Sigma ) with 0 . 1 unit/ml peroxidase ( Sigma ) and 20μM DHE ( Sigma ) were used to detect intracellular total ROS ( Excitation 485nm , Emission 530nm ) , H2O2 production ( Excitation 530nm , Emission 620nm ) and O2- ( Excitation 485nm , Emission 620nm ) , respectively , using fluorescence module of GloMax-Multi Microplate Reader ( Promega , E7031 ) . NO detection in culture media was performed using Griess reagent ( G4410 , Sigma ) at 540 nm . Lucigenin ( M8010 ) and NADPH ( N1630 ) were used to determine NADPH oxidase activity as previously described [12] . Total RNA was isolated from cells and murine tissues using the RNeasy Mini Kit ( Qiagen ) . cDNA synthesis was performed using reverse transcriptase ( TOYOBO ) , cDNA was quantified by real-time polymerase chain reaction ( PCR ) using QuantiTect SYBR Green PCR kit ( TOYOBO ) , according to the manufacturer`s instructions on a Rotorgene ( Qiagen ) . The primer sequences were as follow: mFAF1 , 5'-GGT GAC TGC CAT CCT GTA TTT T-3' ( forward ) and 5'-TGC TCT GTT GGT GTC CTT TG-3` ( reverse ) , mGAPDH , 5`-TGA CCA CAG TCC ATG CCA T-3` ( forward ) and 5`- GAC GGA CAC ATT GGG GGT AG-3` ( reverse ) ; mIL-6 , 5`- GAC AAC TTT GGC ATT GTG G-3` ( forward ) and 5`- ATG CAG GGA TGA TGT TCT G-3` ( reverse ) ; mIL-12p40 , 5'-CAG AAG CTA ACC ATC TCC TGG TTT G-3' ( forward ) and 5'-TCC GGA GTA ATT TGG TGC TTC ACA C-3' ( reverse ) ; mIL-1β , 5`-TTG TGG CTG TGG AGA AGC TGT-3` ( forward ) and 5`-AAC GTC ACA CAC CAG CAG GTT-3` ( reverse ) ; mCOX-2 , 5`-TGA GTA CCG CAA ACG CTT CT-3` ( forward ) and 5`-CTC CCC AAA GAT AGC ATC TGG-3` ( reverse ) ; miNOS , 5`-TGG GAA TGG AGA CTG TCC CAG-3` ( forward ) and 5`-GGG ATC TGA ATG TGA TGT TTG-3` ( reverse ) ; CXCL10 , 5`-GCC GTC ATT TTC TGC CTC A-3` ( forward ) and 5`-CGT CCT TGC GAG AGG GAT C-3` ( reverse ) ; RANTES , 5`- CCA GAG AAG AAG TGG GTT CAA G-3` ( forward ) and 5`- AAG CTG GCT AGG ACT AGA GCA A-3` ( reverse ) ; mp67phox , 5´-CAG ACC CAA AAC CCC AGA AA-3´ ( forward ) and 5´-AGGGTGAATCCGAAGCTCAA-3´ ( reverse ) ; mp47phox , 5´-GTC CCT GCA TCC TAT CTG GA-3´ ( forward ) and 5´-TAT CTC CTC CCC AGC CTT CT-3´ ( reverse ) ; mgp91phox , 5´-TCG CTG GAA ACC CTC CTA TG-3´ ( forward ) and 5´-GGA TAC CTT GGG GCA CTT GA-3´ ( reverse ) ( Bioneer , Daejeon , Republic of Korea ) . BMDMs or HEK293T cells were seeded into eight-chamber slides , followed by treatment or transfection desired . The cells were fixed in 4% paraformaldehyde at RT for 20min , then permeabilized by incubation for 20min with 100% Methanol at -20°C . Then , the fixed cells were incubated with 2% FBS for 1hr to block non-specific binding of antibodies . The appropriate primary antibodies were incubated overnight at 4°C . The cells were washed three times with PBST , and incubated with the appropriate secondary antibodies ( Invitrogen ) for 1hr at RT without light exposure . Then , the cells were washed three times with PBST , and stained with DAPI ( ratio , 1:100 , 000 ) , washed with PBS , and mounted in mounting solution ( VECTOR ) . Images were acquired under a Nikon laser scanning confocal microscope ( C2plus ) and analyzed using NIS-Elements software . BMDMs or Raw264 . 7 cells were infected with L . monocytogenes ( MOI = 0 . 1 ) for 1hr and washed 3 times with sterile PBS , followed by incubation with DMEM containing gentamycin ( 100μg/ml ) for the indicated times . Finally , cells were harvested and lysed with 0 . 1% Triton X-100 ( Sigma ) to release the intracellular bacteria , and cell lysates were then diluted 10-fold in BHI broth ( BD ) . Each sample were plated on BHI agar ( BD ) and incubated at 37°C for one day . Colony-forming unit ( CFU ) was utilized to ensure quantification of intracellular bacteria . Prism 6 software ( GraphPad Software ) was used for charts and statistical analyses . The significance of results was analyzed by an unpaired two-tailed Student’s t-test and Mann-Whitney test with a cutoff P value of 0 . 05 . Error bars and P-values are indicated in the figure legends . | Phagocytic NADPH oxidase plays a pivotal role in generating reactive oxygen species ( ROS ) and in defense against bacterial infections such as L . monocytogenes . ROS eliminate phagocytosed bacteria directly and are implicated in transduction of signals that mediate inflammatory responses . Here , we show that the apoptotic protein FAF1 regulates ROS production in macrophages by regulating phagocytic NADPH oxidase activity upon infection by L . monocytogenes . FAF1 interacts directly with and stabilizes p67phox , a regulatory protein of the phagocytic NADPH oxidase complex , to induce ROS production during L . monocytogenes infection . Production of ROS leads to release of proinflammatory cytokines , chemokines and , ultimately , to bacterial clearance . Interestingly , FAF1gt/gt mice deficient in FAF1 expression exhibit weakened inflammatory responses and are thus more vulnerable to bacterial infection than FAF1+/+ mice . This study reveals that FAF1 is a crucial regulator that induces inflammatory responses to bacterial infection via ROS production . | [
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] | 2019 | Fas-associated factor 1 mediates NADPH oxidase-induced reactive oxygen species production and proinflammatory responses in macrophages against Listeria infection |
Tripartite motif ( TRIM ) proteins belong to a large family with many roles in host biology , including restricting virus infection . Here , we found that TRIM2 , which has been implicated in cases of Charcot–Marie–Tooth disease ( CMTD ) in humans , acts by blocking hemorrhagic fever New World arenavirus ( NWA ) entry into cells . We show that Trim2-knockout mice , as well as primary fibroblasts from a CMTD patient with mutations in TRIM2 , are more highly infected by the NWAs Junín and Tacaribe virus than wild-type mice or cells are . Using mice with different Trim2 gene deletions and TRIM2 mutant constructs , we demonstrate that its antiviral activity is uniquely independent of the RING domain encoding ubiquitin ligase activity . Finally , we show that one member of the TRIM2 interactome , signal regulatory protein α ( SIRPA ) , a known inhibitor of phagocytosis , also restricts NWA infection and conversely that TRIM2 limits phagocytosis of apoptotic cells . In addition to demonstrating a novel antiviral mechanism for TRIM proteins , these studies suggest that the NWA entry and phagocytosis pathways overlap .
Arenaviruses are enveloped single-stranded RNA viruses whose entry is mediated by the viral glycoprotein ( GP ) , generated by proteolytic processing of a precursor into the envelope proteins GP1 , GP2 , and stable signal peptide ( SSP ) , a third subunit required for virus–cell fusion [1] . The clade B New World arenaviruses ( NWAs ) , including Junín and Machupo viruses—the causative agents of Argentine and Bolivian hemorrhagic fever , respectively—use human but not mouse ( Mus ) transferrin receptor 1 ( TfR1 ) for cell entry [2] , whereas the Old World arenaviruses ( OWAs ) Lassa virus and lymphocytic choriomeningitis virus ( LCMV ) use alpha-dystroglycan [3] . NWAs also enter cells via TfR1-independent means and use receptors other than TfR1 to infect sentinel cells of the immune system , their probable initial in vivo targets [4–6] . Other clade B NWAs , such as Tacaribe virus , use TfR1s from their own host but not the human receptor ( reviewed in [7] ) . The T-cell immunoglobulin and mucin ( TIM ) receptor has also been implicated in mediating entry via binding of phosphatidyl serine on the virus membrane ( reviewed in [8] ) , and we suggested that voltage-gated calcium channels ( VGCCs ) serve as additional NWA entry receptors [9] . Subsequent to GP interaction with receptors on the cell surface , trafficking to a late endosomal compartment is required for virus entry [10–13] . Although it is generally accepted that OWAs enter cells via a macropinocytosis-like process that is clathrin- and dynamin-independent , whether this is also the case for NWAs is less clear [7 , 14 , 15] . In a small interfering RNA ( siRNA ) screen for host factors that play a role in Junín virus entry , we identified a number of host genes that alter infection , including tripartite motif 2 ( TRIM2 ) , which was antiviral [9] . TRIM2 knockdown resulted in a 3- to 5-fold increase in infection levels by the replication-competent vaccine strain of Junín virus ( Candid 1 ) and by gammaretrovirus pseudoviruses bearing either the Junín ( Parodi strain ) or Machupo GP as the only NWA protein , suggesting that TRIM2-mediated restriction works at an entry step [9] . TRIM2 did not affect entry by pseudoviruses bearing retroviral envelope proteins or the rhabdovirus vesicular stomatitis virus ( VSV ) GP [9] . The human genome encodes at least 70 TRIM proteins , many of which function as antiviral restriction factors acting at different stages of the virus replication cycle , including uncoating , transcription , and virion release , as well as indirectly by playing a role in cellular antiviral responses [16–19] . TRIM proteins are characterized by an N-terminal RBCC domain , consisting of a RING domain with potential ubiquitin E3 ligase activity , 1–2 zinc-binding B-box motifs , and a central coiled-coil ( CC ) domain involved in protein–protein interaction . The C-terminal domains of TRIM proteins are more variable , with approximately 10 different motifs present in the various family members . TRIM2 belongs to subgroup VII , which contains filamin ( FIL ) domains and NCL-1 , HT2A , and Lin-41 ( NHL ) repeats at their C terminus; only 4 mammalian TRIM proteins belong to this subgroup: TRIM2 , TRIM3 , TRIM32 , and TRIM71 [20] . Little is known about the biology of these 4 proteins . TRIM3 has been implicated in the transport of cellular cargo [21] , TRIM71 in microRNA and mRNA biology [22 , 23] , and TRIM32 is thought to play a role in muscle filaments; mutations in TRIM32 are associated with limb-girdle muscular dystrophy [24] . TRIM2 is highly expressed in the brain . As with other TRIMs , the TRIM2 RING domain encodes E3 ubiquitin ligase activity . TRIM2 binds neurofilament light chain ( NEFL ) subunit through its RBCC and FIL domains [25] . Knockout mice deficient in TRIM2 were reported to develop NEFL buildup in central nervous system axons accompanied by progressive neurodegeneration , tremor , and ataxia , which was attributed to an inability to degrade NEFL [25] . TRIM2 has also been implicated in rare peripheral neuropathies in humans , part of the Charcot–Marie–Tooth diseases ( CMTDs ) ; patients lacking functional TRIM2 protein developed peripheral axonal neuropathy [26 , 27] . TRIM2 interacts with several other cellular proteins . It interacts with Bcl-interacting mediator of cell death ( BIM/BCL2l11 ) and regulates its degradation in the proteasome and with myosin5A ( MYO5A ) through its NHL domain [28 , 29] . In a yeast 2-hybrid screen , TRIM2 was also shown to bind signal regulatory protein α ( SIRPA/SHPS1 ) [30] . SIRPA is a transmembrane glycoprotein that plays a critical role in the phagocytosis of cells by macrophages; binding of SIRPA on phagocytic cells to CD47 on the surface of target cells inhibits their engulfment [31] . SIRPA’s cytoplasmic domain contains 4 tyrosine motifs that , when phosphorylated , become binding sites for the SH2 domains of SHP-1 and SHP-2 , which in turn get activated , initiating a cascade that blocks phagocytosis . Phosphorylation of SIRPA is regulated by various growth factors and integrin activation [32] . Here , using Trim2-knockout mice with different deletions , we show that TRIM2 functions in vivo to suppress NWA infection . Moreover , we show that TRIM2 reduces virus uptake into cells and that one of its interacting partners , SIRPA , functions as an antiviral factor . In in vitro and in vivo studies , we found that TRIM2’s antiviral activity at minimum requires the FIL domain and not the RING domain encoding ubiquitin ligase activity . These studies thus define a novel antiviral function for TRIM proteins and suggest a link in mechanism between virus endocytosis and phagocytosis .
We previously showed that siRNA-mediated depletion of TRIM2 in human U2OS or 293T cells resulted in increased infection by either Junín or Machupo virus GP-pseudotyped murine leukemia virus ( MLV ) or the Junín vaccine strain Candid 1 [9] . To determine if TRIM2 overexpression also altered infection , we transfected a TRIM2 expression vector into U2OS cells and then infected them with pseudoviruses bearing the Junín GP ( Fig 1A ) or with Candid 1 ( Fig 1B ) . Western blot analysis of extracts made from cells transduced in parallel confirmed TRIM2 overexpression and knockdown , respectively ( inset , Fig 1A ) . TRIM2 overexpression resulted in decreased infection by Junín pseudoviruses as well as Candid 1 , and as we showed previously , treatment with TRIM2 siRNA increased infection ( Fig 1A and 1B ) . Depletion of either TfR1 ( the viral entry receptor in human cells ) or the viral nucleoprotein ( NP ) resulted in decreased Candid 1 infection ( Fig 1B ) . As a control , we tested knockdown and overexpression of the retrovirus restriction factor TRIM5α and showed that it did not alter infection by Junín pseudoviruses or Candid 1 ( Fig 1A and 1B ) [9] . We also tested whether TRIM2 affected infection by the NWA Tacaribe virus and pseudoviruses bearing the GPs from the OWAs Lassa virus and LCMV . TRIM2 overexpression or knockdown had no effect on Lassa or LCMV GP pseudovirus infection ( Fig 1A ) . In contrast , TRIM2 knockdown increased and overexpression decreased infection by Tacaribe virus ( Fig 1C ) . Knockdown of the calcium channel α2δ2 ( CACNA2D2 ) subunit of the VGCC , which we previously showed was needed for infection by NWAs but not OWAs , reduced infection by Tacaribe virus , whereas TfR1 knockdown had no effect on Tacaribe infection , as this virus does not use this receptor on human cells ( Fig 1C ) [33 , 34] . Thus , TRIM2 preferentially restricts infection by NWAs . Mice and murine cells can be infected by both the pathogenic and vaccine strains of Junín virus , although mouse TfR1 does not function as a receptor [4 , 5 , 35 , 36] . To determine if TRIM2 acted as an in vivo restriction factor , we created mice with targeted deletion of Trim2 , using clustered regularly interspaced short palindromic repeat ( CRISPR ) /CRISPR-associated 9 ( Cas9 ) . Two guide RNAS were used , one targeting exon 3 and the other targeting exon 9 ( S1A Fig ) . Three independent strains were developed from the knockout injections: A , which deleted sequences between the 2 guide RNAs and potentially expresses only the RING domain because of a stop codon introduced by the deletion; B , which contains the RING domain but has a large internal deletion and then goes back in frame and retains the 3 terminal NHL repeats; and C , which deleted 30 amino acids , including the C’-terminal portion of the RING domain , and then retains the rest of the protein ( Fig 2A ) . Western blot analysis of brains from these mice , using an antibody that recognizes the CC domain , showed no protein from strains A and B and a slightly smaller protein in strain C ( Fig 2B ) . There were 2 TRIM2 isoforms detected in the wild-type and C extracts , likely the result of alternative splicing of a first coding exon or to protein modification ( see below ) . Although no protein was detected in strains A and B with this antibody , RT-qPCR analysis using primers to exon 11/12 showed that both made RNA containing this region ( S1C Fig ) . We also subcloned the cDNAs for the deleted Trim2 in strains B and C and showed that they encoded proteins of the predicted sizes ( see below ) . Both the A and B strains developed ataxia and tremors , as had been previously reported for a TRIM2 knockout generated by insertional mutagenesis [25] , although the phenotype in A strain mice was more severe . A and B strain mice also developed peripheral neuropathy . Although it lacked part of the RING domain needed for ubiquitin ligase function , strain C had no visible phenotype . We first tested primary bone marrow–derived macrophages ( BMDMs ) and fibroblasts from these mice for their ability to be infected by Candid 1 , Tacaribe virus , and LCMV . BMDMs from both the A and B knockout strains were infected at about 10-fold higher levels with Candid 1 than were those from parental C57BL/6 mice ( Fig 2C ) ; fibroblasts derived from the knockout mice were also more highly infected ( S2A Fig ) . Tacaribe virus also infected BMDMs from the A and B knockout mice at about 5-fold higher levels ( Fig 2D ) , whereas infection by LCMV was similar in knockout and wild-type cells ( Fig 2E ) . We then tested whether in vivo infection would be affected by TRIM2 deletion . We showed previously that Candid 1 predominantly infects astrocytes and microglia after intracranial inoculation [37] . Mice of each genotype received intracranial inoculations of Candid 1 , and 5 d post infection ( dpi ) , their brains were harvested and analyzed for viral RNA levels and virus titers . Both the A and B knockouts showed significantly higher levels of infection than did C57BL/6 mice ( Figs 2F and S2B ) . Similar results were obtained when newborn mice received intraperitoneal inoculations of Tacaribe virus , and their spleens were examined for infection ( Figs 2G and S2C ) . Infection of strain C mice in vivo with either Candid 1 or Tacaribe virus was not significantly different than that seen with C57BL/6 mice ( Figs 2C , 2D and S2D and S2E ) . These data demonstrated that TRIM2 restricted NWA but not OWA infection in mice as well as in human cells and suggested that the RING domain was not critical for the antiviral activity . A CMTD patient with early onset peripheral axonal neuropathy was identified as a compound heterozygote for mutations in TRIM2 by whole-exome sequencing [26] . One allele in this patient contains a missense mutation ( E227V ) in a conserved stretch of amino acids at the junction of the first CC motif and the intercoil region that destabilizes the protein; the other allele has a 1-bp deletion ( c . 1699delA ) leading to a frameshift with premature termination , truncating the NHL repeat region and destabilizing the RNA ( Fig 3A ) . RNA from fibroblasts established from this patient showed that TRIM2 protein levels were about 13% of control cells [26] . We tested these primary fibroblasts , as well as those from 2 independent controls , for their ability to be infected with Junín virus . The patient fibroblasts were 4-fold more susceptible to Junín pseudovirus ( Fig 3B ) and 6-fold more susceptible to Candid 1 ( Fig 3C ) , whereas VSV pseudoviruses showed similar infection levels for all cells . Thus , both human and mouse cells lacking TRIM2 are more susceptible to Junín virus infection . Junín virus infection requires binding of the viral GP to the cell surface receptor TfR1 in human cells and to the VGCC in mouse cells . We showed previously that siRNA knockdown of TRIM2 did not alter TfR1 expression or TfR1-mediated uptake of transferrin [9] , suggesting that TRIM2 does not alter the normal biological function of TfR1 . Although TRIM2 is a cytoplasmic protein , it could have an indirect effect on TfR1 or other surface receptors like the VGCC such that they no longer bind Junín virus . We next performed a virus-binding assay with fluorescein isothiocyanate ( FITC ) -labeled Candid 1 and U2OS human cells , which express high levels of TfR1 , and showed that TRIM2 depletion had no effect on binding ( Fig 4A ) . In contrast , knockdown of TfR1 decreased virus binding to cells , as previously been shown [2 , 9] ( Fig 4A ) . Surface expression of the VGCC , likely the NWA receptor in mouse cells , was also unchanged in cells derived from TRIM2-knockout mice ( S3A Fig ) . These data suggested that TRIM2 inhibited infection at a postbinding step . Junín virus enters cells after endocytosis of receptor-bound virus and requires trafficking to a low-pH compartment where virus–membrane fusion occurs and the capsid enters the cytoplasm [4 , 12 , 38] . To determine if TRIM2 altered virus internalization , cells were transfected with the mouse or human TRIM2 expression plasmids , and 24 hr post transfection , virus was bound to cells on ice and then allowed to internalize at 37°C for 1 hr or kept on ice . Virus was stripped from cells , and internalized viral RNA levels were determined by RT-qPCR . Viral RNA levels were reduced by 50% in cells overexpressing TRIM2 compared to untransfected cells or cells transfected with a control green fluorescent protein ( GFP ) expression plasmid ( Fig 4B ) . No virus was detected in the cells kept on ice for the duration of the incubation ( S4 Fig ) . When the same experiment was performed with primary fibroblasts isolated from the A and B strain knockout mice , increased virus entry was seen in the knockout cells compared to the wild-type cells ( Fig 4C ) . These data show that TRIM2 plays a role in restricting virus internalization . The results presented thus far showed that both mouse and human TRIM2 , which are 93% identical at the amino acid level , inhibited NWA infection . Balastik and colleagues created a number of TRIM2 deletion mutants in the mouse backbone and demonstrated that the mouse TRIM2 FIL and NHL domains were both required for NEFL binding ( Fig 5A ) [25] . We used these and created several additional constructs: one expressing the FIL domain , one expressing the RBCC domain , one deleted for the FIL domain , and constructs encoding the cDNAs from strains B and C ( Fig 5A ) . We also subcloned the strain A protein-coding region but did not detect any stable protein . We then tested these constructs for their antiviral activity . The proteins were all expressed at equivalent levels after transfection into U2OS cells , although the FIL construct appeared to form aggregates ( Fig 5B ) . Transfection of the ΔNHL and ΔRBCC constructs significantly decreased Candid 1 infection , as did the construct retaining only the FIL domain ( Fig 5C ) . In contrast , the ΔFIL construct completely lost antiviral activity ( Fig 5C ) . The construct that expressed only the NHL domain had diminished antiviral activity . We then tested if overexpression of the constructs derived from the strain B and strain C mice would inhibit NWA infection . As we saw with the BMDMs from the mutant mice , the B construct had no antiviral activity against Candid 1 , whereas both full-length mouse and human TRIM2 and the C constructs suppressed infection ( Fig 5D ) . We also tested whether the C construct , which retains antiviral activity but is deleted for part of the RING domain , retained auto-ubiquitinylation activity as was previously reported for TRIM2 [25] . The 293T cells were cotransfected with myc-tagged wild-type TRIM2 or C expression vectors , along with a hemagglutinin ( HA ) -tagged ubiquitin construct . Following immunoprecipitation with anti-HA , western blots were performed using anti-myc antibodies . The wild-type construct was heavily ubiquitinylated , whereas the C construct showed much lower levels of ubiquitinylation ( S1D Fig ) . Moreover , treatment of primary macrophages from wild-type or strain A mice with the proteasome inhibitor MG132 had no effect on Candid 1 infection of BMDMs ( S1E Fig ) . Taken together , these data show that the TRIM2’s FIL domain but not its RING domain is necessary for antiviral restriction . Moreover , they confirm that the ubiquitin ligase activity encoded in the RING domain is not needed to inhibit NWA infection . Interactome studies identified several proteins in addition to NEFL that interact with TRIM2 , including SIRPA , BIM , and MYO5A [28–30 , 39] . We immunoprecipitated endogenous TRIM2 from the brains of wild-type mice and showed that SIRPA , NEFL , and MYO5A coimmunoprecipitated ( Fig 6A ) . As a control , we showed that none of these proteins precipitated when the anti-TRIM2 antibody was used with strain A brain extracts ( Fig 6A ) . We were unable to carry out these coimmunoprecipitations with BIM and TRIM2 because of high background with the anti-BIM antisera and brain extracts . To determine if any of these factors also affected NWA infection , we used siRNAs to diminish their expression in U2OS cells . Depletion of SIRPA but not the other proteins caused increased Candid 1 infection ( Fig 6B ) . We also tested whether knockdown of any of these genes would affect infection in human monocyte-like cells , the likely initial targets of Junín virus infection in vivo . THP-1 cells were differentiated with 25 nM of phorbol 12-myristate 13-acetate ( PMA ) and treated with siRNAs to SIRPA , BIM , and MYO5A . Again , only TRIM2 and SIRPA depletion resulted in increased infection ( Fig 6C ) . SIRPA and TRIM2 knockdown but not BIM or MYO5A also increased Candid 1 infection of primary BMDMs isolated from wild-type or strain C mice ( Fig 6D ) ; NEFL expression in THP-1 cells and primary macrophages was undetectable by RT-qPCR , and therefore , siRNA knockdown was not tested . SIRPA overexpression in U2OS cells blocked Candid 1 infection to a similar extent , as TRIM2 overexpression ( S6A Fig ) and SIRPA knockdown also increased infection by Parodi-GP pseudotyped MLV ( S6B Fig ) . However , knockdown of SIRPA in strain A or B mice did not further increase infection ( Fig 6D ) , nor was SIRPA surface expression diminished in the TRIM2 knockout mice ( S3B Fig ) . SIRPA and TRIM2 also colocalized in transfected U2OS cells ( Fig 7A ) ; this colocalization was not affected by NWA infection ( S6C Fig ) . Using the deletion constructs described in Fig 5A , we also found that TRIM2 coimmunoprecipitated via the FIL or NHL but not the RBCC domain ( Fig 7B ) . Finally , to confirm that the TRIM2’s inhibition of infection relied on its interaction with SIRPA , we treated U2OS cells overexpressing TRIM2 with SIRPA siRNA and infected them with Candid 1 . SIRPA knockdown in the context of TRIM2 overexpression restored infection levels almost to that seen in control cells ( Fig 7C ) . Taken together , these data suggested that TRIM2 and SIRPA function in the same pathway to restrict NWA internalization . SIRPA is expressed on the surface of antigen-presenting cells such as macrophages and plays a critical role in phagocytic engulfment of tumor and other cells [31] . Upon binding to CD47 on tumor cells , the cytoplasmic tail of SIRPA becomes tyrosine-phosphorylated , and SHP-1 and SHP-2 phosphatases are recruited and activated , initiating dephosphorylation of downstream substrates [40] . SHP-1 is predominantly expressed in hematopoietic cells , whereas SHP-2 is more ubiquitously expressed . We next tested whether SHP-2 also played a role in regulating NWA infection using siRNA knockdown in U2OS cells . SHP-2 depletion resulted in a large decrease in Candid 1 and Tacaribe virus infection ( Figs 8A and S7A ) . These data suggested that phosphorylation of SIRPA or TRIM2 might play a role in infection; whereas the biological significance of SIRPA phosphorylation is well-established , TRIM2 phosphorylation has not been previously reported . We thus tested whether endogenous TRIM2 and SIRPA were tyrosine-phosphorylated . Brain extracts from A , B , C , and wild-type mice were immunoprecipitated with anti-phosphotyrosine antisera , and anti-TRIM2 and anti-SIRPA antisera were used to detect protein on western blots . A single TRIM2 isoform , corresponding to the upper band of the doublet , was immunoprecipitated from the extracts from the C and wild-type mice but not the A or B mice ( top panel , Fig 8B ) . SIRPA was also phosphorylated in the brains of all the mice . Similar results were seen when TRIM2 or SIRPA was overexpressed in U2OS cells ( S7B Fig ) . Next , we tested whether infection with Candid 1 altered phosphorylation of TRIM2 or SIRPA . SIRPA phosphorylation was detected in the infected brains of strains A and B but was greatly decreased in strain C or wild-type mice upon infection ( Fig 8B ) . A similar decrease in phosphorylation of endogenous SIRPA was seen after Tacaribe virus infection of TRIM2-transfected U2OS cells ( S7D Fig ) . TRIM2 phosphorylation was not altered by Candid 1 or Tacaribe virus infection . Moreover , when we coimmunoprecipitated TRIM2 and SIRPA , we found that the interaction between TRIM2 and SIRPA decreased upon infection ( Figs 8B and S7C ) . These data suggest that dephosphorylation of SIRPA leads to its decreased interaction with TRIM2 . Finally , we tested whether loss of TRIM2 affected phagocytosis of apoptotic cells by macrophages , a process known to be down-regulated by SIRPA [41 , 42] . BMDMs isolated from strain A TRIM2-knockout and wild-type mice were incubated with phrodo Red–labeled apoptotic thymocytes , and relative phagocytosis was analyzed; phrodo Red–labeled viable thymocytes served as a control . BMDMs from the knockout mice phagocytosed significantly more apoptotic cells than did those from wild-type mice ( Figs 8C and S8 ) , suggesting that TRIM2/SIRPA complexes might be fundamental to regulation of different endocytic processes .
Arenavirus infection requires binding of the viral GP to cell surface receptors followed by trafficking to acidic endosomes , where virus fusion occurs and capsids are released into the cytoplasm [38] . Although the general steps in the NWA entry pathway have been elucidated , the cellular proteins involved in this process have not been identified , particularly with regard to factors that might limit virus entry . Here , we show that TRIM2 , a member of a relatively understudied TRIM subfamily , acts to limit internalization of NWAs but not OWAs and that it does this by interacting with SIRPA , a protein known to be involved in phagocytosis , a specialized form of endocytosis . TRIM proteins are known to affect different stages of viral infection , including uncoating , viral gene transcription , release from the cells , and intrinsic/innate immune responses , and many of these activities require the ubiquitin ligase activity conferred by the RING domain [18 , 19] . TRIM2 itself has been implicated in the ubiquitination and degradation of several interacting partners through its RBCC domain , including BIM and NEFL [25 , 29] . In contrast , we found that TRIM2 inhibition of NWA infection both in vitro and in vivo was independent of the RBCC domain and instead required the FIL domain . Indeed , the C mutant , which lacked auto-ubiquitination through partial deletion of its RING domain , still behaved as a restriction factor in vitro and in vivo . Mice bearing this gene deletion had no neurological disease , suggesting that NEFL degradation also does not play a role in the neuropathology seen in CMTD patients . Many TRIMs are found in the cytoplasm and do not colocalize with commonly used cellular markers for subcellular compartments such as the Golgi apparatus , endocytic vesicles , clathrin-coated pits , mitochondria , intermediate filaments , tubulin , and actin; the exceptions are TRIM1/midline 2 ( MID2 ) and TRIM18/MID1 , which localize to microtubules [43 , 44] . TRIM2 belongs to the subgroup of cytoplasmic filamentous TRIMs that also do not colocalize with known compartment markers , including tubulin [44] . The filamentous structures might be involved in cargo transport of virus particles and contribute to TRIM2 restriction activity . For example , TRIM3 , another subgroup VII member , plays a role in the cytoskeletal-associated-recycling/transport complex and binds to the kinesin motor protein kinesin family member 21B ( KIF21B ) as well as MYO5 , a microtubule-associated motor protein [21 , 45] . TRIM2 also associates with MYO5A ( Fig 6A ) [28] . Although siRNA knockdown of MYO5A did not affect Junín virus infection in vitro , it is possible that other motor proteins are involved in TRIM2 activity . Of the proteins in the TRIM2-interactome , only SIRPA showed anti-NWA activity . Like TRIM2 , SIRPA is expressed in both myeloid and neuronal cells . A major role for SIRPA is the inhibition of phagocytosis upon binding to CD47 on host cells [31 , 46] . The cytoplasmic domain of SIRPA contains 4 tyrosine motifs that harbor the consensus binding sites for the SH2 domains of SHP-1 and SHP-2 phosphatases , which upon SIRPA binding subsequently dephosphorylate downstream targets , thereby regulating phagocytosis [31] . Phosphorylation of SIRPA is regulated by various growth factors such as epidermal growth factor and integrin activation and is greatly increased in cells overexpressing catalytically inactive SHP-2 [47] . Our data demonstrated that TRIM2 and tyrosine-phosphorylated SIRPA constitutively interact in vivo and that such interaction is diminished upon Junín virus infection . We also showed that SIRPA phosphorylation is decreased upon infection; although TRIM2 also contains phosphotyrosines , infection did not lead to its dephosphorylation . Whether infection leads to SIRPA dephosphorylation and disassociation from TRIM2 or follows the dissociation is currently under investigation . However , similar interactions have been reported for TRIM2’s interaction with BIM; TRIM2 binds to BIM only when it is phosphorylated by p42/p44 mitogen-activated protein ( MAP ) kinase [29] . TRIM2 binds to membrane acidic phospholipids found on the cytosolic side of membranes , which may bring it into contact with SIRPA [48] . Taken together , these data suggest that phosphorylated SIRPA binds to TRIM2 and that this complex blocks virus internalization; dephosphorylation of SIRPA , either directly by SHP-2 or by other cellular phosphatases activated by infection , leads to dissociation of the complex and allows infection ( Fig 9 ) . Although we have not yet demonstrated how infection triggers this response , we as well as others have shown that arenaviruses interact with several Toll-like receptors ( TLRs ) , and SHP phosphatases have been implicated in both TLR- and retinoic acid–inducible gene I ( RIG-I ) -mediated signaling [4 , 37 , 49–52] . However , SHP-2 is involved in many pathways , so the inhibition of infection found in cells depleted for SHP-2 may not be directly linked to its interaction with SIRPA . We also found that loss of TRIM2 lead to increased macrophage engulfment of apoptotic cells , a process known to be regulated by SIRPA , suggesting that there is overlap in the pathways used for NWA entry and phagocytosis . In conclusion , we show that TRIM2 , which belongs to a subfamily in which other members play a role in cargo trafficking , interacts with SIRPA , a known modulator of phagocytosis , and that this interaction plays a role in limiting NWA entry , an antiviral function heretofore not described for TRIM proteins . Whether TRIM2 affects the other known functions of SIRPA , including phagocytosis , is currently under investigation . The results of these studies could lead to a better understanding of its role in macrophage and neuronal cell function in addition to its role in virus entry .
All mice were housed according to the policies of the Institutional Animal Care and Use Committee of the University of Pennsylvania and of the Animal Care Committee of the University of Illinois at Chicago; all studies were performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The experiments performed with mice in this study were approved by the University of Pennsylvania IACUC ( protocol #803700 ) and University of Illinois at Chicago ACC ( protocol #15–222 ) . Vero , U2OS , BHK-21 , and 293T cells were cultivated in Dulbecco’s modified Eagle Medium ( DMEM; Gibco ) supplemented with glutamine ( 2 mM ) , 10% fetal bovine serum ( FBS; Invitrogen ) , and penicillin ( 100 U/ml ) -streptomycin ( 100 μg/ml ) ( Invitrogen ) . THP-1 cells were grown in RPMI medium ( Gibco ) supplemented with 10% FBS and antibiotics . Candid 1 ( obtained from Robert Tesh ) , was propagated in Vero cells , whereas LCMV ( obtained from John Wherry ) and Tacaribe virus ( TRVL-11573; BEI Resources ) were propagated in BHK-21 cells . Cells monolayers were infected at 70%–80% confluency with a multiplicity of infection ( MOI ) of 0 . 01–0 . 03 . Media were removed 24 hr post infection ( hpi ) , and the cells were fed with media supplemented with 2% FBS . Media were harvested at 3 , 4 , and 5 dpi to collect LCMV and at 7 , 8 , 9 , and 10 dpi for Candid 1 and Tacaribe virus . Virions were partially purified by centrifugation through a 30% sucrose cushion , resuspended in DMEM supplemented with 2% FBS , and stored at −80°C until use . MLV pseudoviruses encoding the luciferase gene and bearing the different viral GPs were created as previously described [4] . Candid 1 titers were determined by infectious center assays ( ICAs ) . Vero cells were infected with serial dilutions of the virus for 1 hr at 37°C . Virus was removed , and cells were washed with PBS followed by the addition of an overlay composed of 1% agarose and medium supplemented with 2% FBS . Three days after infection , the cells were fixed with 4% paraformaldehyde , permeabilized with blocking buffer ( 1X PBS , 2% BSA , 0 . 1% Triton X-100 ) , incubated with a monoclonal antibody against JUNV NP ( NP IC06-BA10; BEI Resources ) , and incubated with Alexa Fluor 488-coupled secondary antibody ( Invitrogen ) . Cells were visualized with a Keyence fluorescence microscope and foci counted using automated software . Tacaribe virus titers were determined by TCID50 [53] . In brief , virus dilutions from 10−1 to 10−8 were used to infect Vero cell monolayers cultured in 96-well flat-bottom plates ( Corning ) . The plates were incubated for 1 wk at 37°C , and the virus titer was defined as the last dilution showing cytopathic effects in culture in at least half of the wells infected with each dilution ( 12 replicates per dilution ) . LCMV titers were determined by plaque assay [54] . Briefly , Vero cells were seeded on 6-well plates and infected with serial 10-fold dilutions of LCMV . Agarose overlays ( 1% agarose in 2X medium 199 [Gibco] ) were added to each well after removing the inoculum . The plates were incubated for 4 d at 37°C , fixed with 10% formaldehyde , and stained with 0 . 1% crystal violet solution , after which plaques were counted . To generate Trim2-knockout mice , exon 3 and exon 9 were targeted by 2 sgRNAs using CRISPR/Cas9 technology ( S1 Fig ) . The sgRNAs and CRISPR RNAs were microinjected into zygotes from C57BL/6N mice ( Charles River ) by the University of Pennsylvania Transgenic and Chimeric Mouse Facility . Genotyping was performed using primers 5′-GCTTTTTCTACTACTTGGTGGCC-3′ and 5′-CCCGTGATTTCTGTGTTAGTTCA-3′; these primers only amplified the A and B knockout alleles , as they are about 25 kB apart in the wild-type gene . To further determine small deletions or mismatches at the endogenous target arising from dsDNA break repair via NHEJ , we performed T7 endonuclease 1 ( T7EN1 ) cleavage assay on genomic DNA . PCR amplification of exon 2 ( 5′-GCTTTTTCTACTACTTGGTGGCC-3′ and 5′-CCCGTGATTTCTGTGTTAGTTCA-3′ ) and exon 9 ( 5′-AGCTTCAGGTTGGTTTCTGGA-3′ and 5′-GACATCATGCAAATGTGAGCAGA-3′ ) . The PCR products were then denatured and reannealed; the annealed PCR products were treated with T7EN1 , as recommended by the manufacturer ( NEB ) and analyzed on 2% agarose gels . The exact deletions found in each strain were determined by sequencing genomic DNA ( all strains ) and cDNA ( strains B and C ) generated from total cellular RNA ( sequences showing the deletion and coding regions are deposited in a Mendeley dataset at http://dx . doi . org/10 . 17632/d2vwry7j3x . 2 ) . Primary BMDMs were isolated from hind limbs of 8- to 10-wk-old mice as previously described [4] . Macrophages were cultured in DMEM supplemented with 10% FBS , penicillin ( 100 U/ml ) -streptomycin ( 100 μg/ml ) , and 100 μg/ml of macrophage colony–stimulating factor ( M-CSF; Gibco ) . Cells were harvested 7 d after plating and were seeded in 24-well plates for siRNA knockdown and infection assays . Mouse macrophages were infected with Candid 1 at a MOI of 1 , and after adsorption for 1 hr at 37°C , unbound virus was washed off with 0 . 1 M sodium citrate ( pH 3 ) . THP-1 cells were differentiated into macrophages by treatment with 200 μM PMA ( Sigma ) for 24 hr . Cells were washed with PBS , fresh media were added , and the cells were incubated at 37°C for 72 hr . Cells were infected with Candid 1 as described above for mouse macrophages . Three different experiments were performed , using cell passages 4 , 5 , and 6 . Patient and control cells , as well as U2OS cells , were infected with MLV pseudoviruses bearing the Junín or VSV GPs for 48 hr , and luciferase readings were taken to evaluate infection levels . For Candid 1 infections , the cells were infected with Candid 1 ( MOI = 0 . 1 ) for 24 hr , and RNA was isolated . Reverse-transcribed RT-qPCR was performed for the expression of NP , and the fold infection levels were compared between patient and control fibroblasts . The results of the experiments from the 3 passages were averaged . Eight- to 10-wk-old mice were infected by intracranial inoculation of Candid 1 . Each mouse was injected with 2 × 104 PFU , and the infection progressed for 5 d , at which time the brains were harvested . Neonatal mice ( 1–3 d after birth ) were infected with Tacaribe virus ( TRVL-11573 ) by intraperitoneal inoculation . Each pup received 2 × 103 TCID50 of the virus . Spleen infection was analyzed at 1 wk post infection . The brains of Candid 1-infected mice were homogenized in 1X PBS . The homogenate was clarified by centrifugation , and the supernatants were collected and stored at −70°C . Viral titers were quantified by ICA . A portion of the brain homogenate was used for RNA isolation by using the TRIzol reagent ( Invitrogen ) according to the manufacturers’ instructions . The spleens from Tacaribe virus–infected pups were homogenized and clarified as described for adult mice . Virus titers were determined by TCID50 . Total RNA was isolated using the RNeasy kit ( Qiagen ) . The RNA was used as a template for cDNA synthesis using the SuperScript III First-Strand Synthesis System ( Invitrogen ) and random hexamer primers following the manufacturer’s specifications . RT-qPCRs were performed with specific primer pairs ( S1 Table ) using a Power SYBR green PCR kit ( Applied Biosystems ) and the QuantStudio 5 Real-Time PCR System ( Applied Biosystems ) . RNA quantifications were normalized to glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) . The amplification conditions were 50°C for 2 min , 95°C for 10 min and 40 cycles of 95°C for 15 s , and 60°C for 1 min . The efficiency of amplification was determined for each primer pair by generating a standard curve with 10-fold serial dilutions of a known concentration of DNA . The slope values of the standard curves for the primer pair amplicons ranged from 3 . 5 to 3 . 2 , indicating 90%–100% efficiency . For each primer pair , a no-template control was included , and each sample was run in triplicate . BMDMs from mutant ( A/A , B/B , C/C ) and wild-type mice were stained with mouse anti-dihydropyridine binding complex ( A1S ) antibody ( Millipore ) and FITC-labeled anti-mouse CD172a ( SIRPA ) ( Biolegend ) . Cells stained with the A1S antibody were incubated with Alexa 647–conjugated secondary antibody ( Invitrogen ) . Cells were analyzed in a CyAn ADP High-speed Analyzer ( Beckman Coulter ) using FlowJO v10 ( Tree Star ) software . Gating strategies and fcs files are deposited in a Mendeley dataset at http://dx . doi . org/10 . 17632/d2vwry7j3x . 2 . Candid 1 was concentrated by centrifugation on 30% sucrose cushions , titered , and labeled with FITC using Fluorotag FITC conjugation kit ( Sigma ) . Cells were transfected with siRNAs and incubated with FITC-labeled Candid 1 for 1 hr on ice and then transferred to 37°C for 1 hr; a particle/cell ratio of 1 , 000 was used to ensure saturation of all binding sites . Cells were subjected to the above described protocol and analyzed in a FACS Calibur cytometer ( Becton Dickinson ) . U2OS cells were transfected in triplicate with the human TRIM2 , mouse TRIM2 , or pGFP plasmids . At 24 hr post transfection , the cells were incubated on ice with Candid 1 ( MOI of 5 ) for 1 hr , shifted to 37°C for 1 hr , and then treated with sodium citrate ( pH 3 ) at 37°C for 15 min to strip off virus still on the cell surface . RNA was isolated and used for RT-qPCR to measure internalized virus . Values were normalized to Candid 1–infected untransfected cells . For the depletion of target genes in human and mouse cells , siRNAs from Qiagen were used for TRIM2 ( SI04165602 ) , SHP-2 ( SI04165602 ) , and control ( 1022076 ) ; from Ambion for CACNA2D2 ( 21426 ) , NEFL ( 17405 ) , BIM ( 262307 ) , MYO5A ( 118346 ) , and SIRPA ( 109944 ) ; and from Dharmacon for TfR1 ( L-003941 ) . Briefly , cells were transfected using the forward transfection method and Lipofectamine RNAi Max ( Invitrogen ) . siRNA depletion was carried out for 48 hr . Cells were infected with Candid 1 or Junín GP-MLV pseudoviruses , and plates were incubated for another 24 hr . The c-myc-tagged mouse TRIM2 , ΔRBCC , ΔNHL , and NHL constructs were obtained from Martin Balastik [25] . The human TRIM2 and TRIM5α constructs were obtained from Walter Mothes . Constructs encoding the Trim2 sequence from strains B and C were generated by PCR using reverse-transcribed RNA from mouse brain extracts and amplified with the primers 5′-TGGTGGAAGCTTGCAATGGCCAGTGAGGGCGCCAGCA-3′ and 5′- TGGTGGCTCGAGCTGTAAGTACCGGTAGACCTT-3′ . The ΔFIL construct was generated by PCR-mediated plasmid DNA deletion from the full-length TRIM2 plasmid , using primers designed to amplify the entire coding sequence except for the region to be deleted: 5′-CAACCTGGGGACCATCCTCATCCGCTCTGCCGACG-3′ and 5′-GACACGTCGGCAGAGCGGATGAGGATGGTCCCCAGG-3′ [55] . The RBCC construct was generated by PCR using the human TRIM2 plasmid as template and the primers 5′-TTGTTGAAGCTTGCAATGCACAGGAGTGGCCGT-3′ and 5′- TTGTTGTCTAGACTGGTCGGCCAGCTCGTT-3′ , and the FIL construct was generated using primers 5′-GGGGTACCATGACCACCAACGCCGTTGC-3′ and 5′-CCTCTAGACACTTTCAGCTTAAACGGGC-3′ . The full-length coding sequence of human SIRPA was amplified by PCR using cDNA reverse transcribed from U2OS cells RNA with primers 5′-TAATGGGGATCCGCAATGGAGCCCGCCGGCCCG-3′ and 5′-TTGTTGTCTAGACTTGTCGTCATCGTCTTTGTAGTCCTTCCTCTGGACCTGGAC-3′; a FLAG-tag was included in the reverse primer . The purified DNA from each construct was cloned into a pcDNA3 . 1 ( + ) myc-His vector ( Thermo-Fisher ) ; the myc and His tags were in frame with the coding regions of the constructs . The final constructs were validated by Sanger sequencing . Equal amounts of protein extracts ( 50 μg ) were resolved by 10% SDS-PAGE and transferred to polyvinylidene difluoride ( PVDF ) membranes . Detection of JUNV NP was done using a monoclonal antibody NA05-AG12 ( BEI Resources ) . Myc-tagged TRIM2 proteins were detected with an anti-Myc antibody ( Cell Signaling Technologies [CST] ) , and FLAG-tagged SIRPA was detected with an anti-FLAG M2 antibody ( Sigma ) . Endogenous and transfected TRIM2 was detected by rabbit anti-TRIM2 antibodies ( Sigma SAB4200206 ) . NEFL , SIRPA , MYO5A , SHP-2 , and phospho-ERK1/2 were detected with rabbit polyclonal antibodies ( CST ) . Full-length and mutant versions of TRIM2 and full-length SIRPA plasmids ( Addgene ) were transfected into U2OS cells using Lipofectamine 3000 ( ThermoScientific ) for 24 hr according to the manufacturers’ instructions . The cells were infected with Candid 1 or Tacaribe virus ( MOI = 10 ) for 1 hr on ice and shifted to 37°C for an additional hour . The staining and visualization of the cells was performed as described above . Myc-tagged TRIM2 and strain C constructs were cotransfected with an expression plasmid encoding HA-tagged ubiquitin ( Addgene ) in 293T cells . After 24 hr in culture , 20 μM MG-132 ( Sigma ) was added to the media , and cells were cultured for 8 hr . Cells were lysed with 1X cell lysis buffer ( CST ) supplemented with 2% of Halt Protease and Phosphatase Inhibitor Cocktail ( ThermoScientific ) and 50 mM N-ethylmaleimide ( NEM; Sigma ) . Lysates were subjected to immunoprecipitation with a rabbit polyclonal anti-HA antisera ( CST ) and Protein A/G agarose beads ( Santa Cruz Biotechnology ) and analyzed by western blot , using anti-myc antibodies ( CST ) . After transfection of the expression plasmids , the cells were fixed with ice-cold methanol , incubated with 125 mM glycine , permeabilized with 1X PBS-0 . 3% Triton X-100 , and then blocked with 1X PBS-1% BSA . Staining with primary antibodies rabbit polyclonal anti-TRIM2 ( Sigma SAB4200206 ) , mouse monoclonal anti-human SIRPA ( R&D Systems ) , and rabbit anti-Myc ( CST ) was carried out according to the manufacturer’s suggestion . After washing with PBS–0 . 1% Tween-20 , the cells were incubated with Alexa Fluor–coupled ( anti-mouse 488 , anti-rabbit 568 , anti-chicken 647 ) secondary antibodies ( Invitrogen ) . Cells were visualized under a Keyence fluorescence microscope . Brain tissue was homogenized in 1X cell lysis buffer ( CST ) supplemented with 2% of Halt Protease and Phosphatase Inhibitor Cocktail ( ThermoScientific ) . The protein lysate was incubated on ice for 30 min , sonicated 4 times for 30 s , and clarified by centrifugation . The extracts were precleared with Protein A/G PLUS-Agarose beads ( Santa Cruz Biotechnology ) , and the supernatant was incubated with the primary antibody ( rabbit polyclonal anti-TRIM2; Sigma SAB4200282 ) or mouse Phospho-Tyrosine mAb ( P-Tyr-100; CST ) and 20 μl of Protein A/G PLUS-Agarose beads overnight . The immunocomplexes were analyzed by western blots as described above . Thymocytes from a wild-type mouse were treated with 0 . 1 μM dexamethasone ( Sigma ) for 14 hr at 37°C to induce apoptosis and then stained with pHrodo Red , succinimidyl ester ( ThermoScientific ) for 1 hr . Fully differentiated BMDMs from 3 mice of each genotype were incubated in duplicate with the thymocytes for 2 hr at 37°C at a ratio of 1:5 , after which they were stained with FITC-conjugated anti-CD11b ( Invitrogen ) and analyzed by FACS . The percentage of double-positive cells was determined , and the percent internalization was normalized to wild type for each experiment . Presented is the average of 3 experiments done on different days . Each experiment was done with 3 technical replicates/experiment . Data shown are the average of at least 3 independent experiments , or as indicated in the figure legends . For in vivo experiments , the number of mice used in each experiment is shown in the graphs . Statistical analysis was performed using the GraphPad/PRISM software . Raw data for all figures are deposited in a Mendeley dataset at http://dx . doi . org/10 . 17632/d2vwry7j3x . 2 . | New World arenaviruses ( NWAs ) are rodent-transmitted viruses that cause high mortality when they evolve the ability to infect humans . Although these clade B pathogenic viruses are known to bind to transferrin receptor 1 and other receptors on the cell surface , the steps leading to their entry into the cell are not well determined . We show that a host factor identified in a previous small interfering RNA ( siRNA ) screen , tripartite motif 2 ( TRIM2 ) , limits NWA endocytosis into cells . Moreover , we show that a member of the TRIM2 interactome , signal regulatory protein α ( SIRPA ) , which is well-known for inhibiting phagocytosis by macrophages , interacts with TRIM2 and also blocks NWA infection . This finding suggests that there are common mechanisms that regulate virus endocytosis and phagocytosis . | [
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] | 2019 | TRIM2, a novel member of the antiviral family, limits New World arenavirus entry |
Dengue virus ( DENV ) is the most important vector-borne virus globally . The safe and effective vaccines are still under development and there are no antiviral drugs for DENV induced diseases . In this study , we obtained five DENV1 isolates ( DENV1 A to E ) from the outbreak of dengue fever in 2014 of Guangzhou , China , and analyzed their replication efficiency and virulence in vitro and in vivo . The results suggested that among the five DENV1 strains , DENV1 B has the highest replication efficiency in both human and mosquito cells in vitro , also causes the highest mortality to suckling mice . Further study suggested that nonstructural proteins from DENV1B have higher capacity to suppress host interferon signaling . In addition , the NS2B3 protease from DENV1B has higher enzymatic activity compared with that from DENV1 E . Finally , we identified that the 64th amino acid of NS2A and the 55th amino acid of NS2B were two virulence determining sites for DENV1 . This study provided new evidences of the molecular mechanisms of DENV virulence .
Dengue virus ( DENV ) is currently the most popular mosquito-borne virus and widely spreads in tropical and subtropical regions[1] . A series of symptoms caused by DENV , such as dengue hemorrhagic fever/dengue shock syndrome ( DHF/DSS ) , seriously threaten human health[2 , 3] . Dengue virus belongs to a single-stranded positive sense RNA virus and lacks of accurate replication correcting system . Virus nucleotide changes will eventually lead to stronger or weaker virus virulence during the long-term process of virus spread . Secondly , host response is induced upon virus infection and the interactions between host and virus also influence the virulence . These two aspects corporately influence the virus pathogenicity and severity of the diseases[4 , 5] . Therefore , it is of great significance to identify the sites within the virus genome that are associated with virulence and to investigate the interactions between virus and host . DENV genome is an approximately 10 . 7-kb positive-sense RNA , encodes a single polyprotein that is cleaved posttranslationally by host and viral proteases into three structural proteins ( capsid [C] , premembrane [prM] , and envelope [E] ) and seven nonstructural proteins ( NS1 , NS2A , NS2B , NS3 , NS4A , NS4B , and NS5 ) . Structure proteins C , M and E are components of viral particles , and the viral nonstructural proteins are critical for viral genome transcription and replication[5] . At the same time , flavivirus nonstructural proteins are reported to attenuate host antiviral responses and facilitate viral survival[6] . For example , Dengue virus ( DENV ) NS4B and NS4A inhibited TBK1 phosphorylation thereby reducing the IFN production[7] . DENV NS2A , 2B , 4B and NS5 inhibit IFN-mediated JAK-STAT activation and impair interferon-stimulated gene ( ISG ) production[8–12] . DENV NS5 could inhibit STAT2 phosphorylation thereby blocking IFN downstream signaling[13] . The amino acid changes in the nonstructural proteins were believed to influence the activity of virus to antagonize host antiviral responses . The variations in virus genome are closely related with the virulence . Lots of studies showed that the mutations in virus E protein resulted in the significant changes in virulence of flavivirus[14] . By using the reverse genetic approaches , Prestwood and collaborators found mutations at amino acid 124 and 128 in E protein increased the virulence of DENV[15] . Three substitutions in E protein ( 196Met→Val , 365Val→Ile , 405Thr→Ile ) and one in NS3 protein ( 435Leu→Ser ) were reported to be associated with the pathogenesis of neurotoxicity of DENV[16 , 17] . As a multiple function protein , NS3 has serine protease activity in its N terminal domain , which is required for the cleavage of viral polyprotein and the maturation of viral particles . The NS3 protease cleavage ability will determine the assembling efficiency of viral particles[18 , 19] . Furthermore , the hypervariable regions of the 3’UTR are also believed to be the virulence determination sites , although the biological relevance is remained to be elucidated[20 , 21] . In the past 25 years , cases of dengue infection have been reported in Guangdong province of China every year[22–24] . The peak of infection happened in 2014 , and DENV1 appeared as the major serotype at that year[23 , 25] . We acquired five DENV1 isolates with different genotypes from Guangdong province among the outbreak of dengue fever of 2014 . The differences between these virus strains were studied in in vitro and in vivo models . To further understand the molecular mechanism underlying the virulence difference of five variants , we investigated the ability of the variants antagonizing host innate immune response and the functions of their NS2B3 protease .
Five different DENV1 isolates , named DENV1A to DENV1E in this study , were isolated from the DENV outbreak of 2014 in Guangdong Province , China . The nucleotide sequences of these five DENV1 strains were determined by high throughput sequencing/assembling approach and submitted to Genebank under the accession numbers MH271402 ( DENV1A ) to MH271406 ( DENV1E ) . To test the replication efficiency of these five isolates in mammalian cells , human 293T cells were infected with DENV1 A to E respectively at the same MOI of 0 . 5 . Cells were harvested at 12 , 24 , 48 and 72 h post infections , and the viral replication efficiency were determined by measuring viral envelope ( E ) gene mRNA copies , then normalized to human β-actin gene . The results suggested that DENV1B and DENV1C had higher replication efficiency among the five virus strains in 293T cells ( Fig 1A ) . Consistent with the intracellular viral RNA levels , the virus titers in supernatants from DENV1B and 1C infected cells were higher than those from DENV1D and 1E infected cells ( Fig 1B ) . To test the infection ability of these five strains to mosquito cells , C6/36 cells ( origin from Aedes albopictus ) were infected with DENV1 A to E . The results suggested that DENV1B also showed higher replication efficiency and produced more viral particles in mosquito cells when compared with other strains ( Fig 1C and 1D ) . Then we used a sucking mice infection model to test the virulence of these five DENV1 strains in vivo . Three- or four-day-old suckling mice were inoculated intracerebrally with 100 PFU of DENV1 A to E respectively , and the mortality rates were monitored daily . The results suggested that sucking mice started to die at 10 days post DENV1B infection , while this date was postponed to day 15 in case of DENV1E infection . 100% of DENV1B infected mice died at day 15 post infection , but 70% of DENV1E infected mice were survived from infection and recovered ( Fig 1E ) . These data suggested that DENV1B is the most virulent virus , while DENV1E is the weakest . We also quantified the viral loads in infected mouse brains by qRT-PCR and plaque assays . Consistently , the viral loads in the brains of DENV1B infected mice were significantly higher than those from DENV1E infected mice ( Fig 1F and 1G ) . To further confirm that DENV1B is the most virulent virus while the DENV1E is the weakest , HUVEC and Huh7 . 0 cells were infected with DENV1B and E , respectively . The results suggested that DENV1B showed significantly higher replication levels at all time points post infection and produced more viral particles in these cells ( Fig 1H to 1K ) . Taken together , these data suggested that DENV1B is the most virulent virus among the five DENV1 strains , while DENV1E is the weakest . DENV-1 can be divided into 5 main genotypes . Genotype II and III have only a few early strains , and I , IV and V are the three major genotypes in circulation[26 , 27] . In order to understand the origin and relationships of the five DENV-1 viruses , molecular evolution analysis was performed using various bioinformatics approaches . 123 full length DENV1 sequences were downloaded from ViPR ( www . viprbrc . org ) database . The ORFs of these 123 viruses , together with DENV1 A to E from this study , were analyzed by Multiple alignment program Mafft ( https://mafft . cbrc . jp/alignment/server/ ) . The phylogenetic tree showed that DENV1A , B and C belong to genotype I of DENV1 ( Fig 2A , and S1 Fig ) . DENV1A is closely related with the DENV1 viruses that are endemic in Zhongshan ( China ) ( 2013 ) and Shizuoka ( Japan ) ( 2014 ) . DENV1 B and C are closely related to LC011948 , which is endemic in Chiba , Japan in 2014 . Then we speculated that the strains erupted in Guangdong and Japan in 2013–2015 probably came from the same ancestor . DENV1D and 1E are very similar to each other . They are located in a branch of DENV1-V genotype , share homology with DENV-1 ( KX380801 and KX380796 ) isolated from Singapore in 2014 ( Fig 2A , and S1 Fig ) . In addition , DENV1B and C share high similarities to a DENV1 strain ( AB178040 . 1 ) isolated from Japan in 2004 ( Fig 2B ) . Then , a DENV1 replicon , DGL2 , origin from this DENV1 strain[28] was used as a reverse genetics approach to perform the single point mutations in DENV1B genomes . Using MEGA software , the ancestral sequences for the five DENV1 viruses were analyzed and 72 amino acid variations between DENV1 A&B&C and DENV1 D&E were identified ( S2 Table ) . At the same time , all the variations in NS2A , 2B , 4A and 4B among DENV1 A to E were showed in Fig 2C–2F . DENV NS proteins were reported to have the ability to suppress IFN signaling , and this activity will contribute to its virulence in mammalian host . To test whether NS proteins from DENV1 A-E have different capacity against IFN signaling , NS2A , 2B , 4A and 4B from all these five strains were cloned and expressed in 293T cells . IFN-β-Luciferase reporter assay suggested that NS2A and 2B from DENV1B showed the highest inhibitory activity against RIG-I directed IFN activation , compared with NS2A/2B from other strains . NS4A and NS4B from DENV1 A&B&C also have higher inhibitory capacity to IFN signaling compared to those from DENV1 D&E ( Fig 3A–3D ) . Consistent with these results , RIG-I induced IFNβ mRNA expression was also dramatically decreased in cells expressing NS proteins from DENV1B when compared with those from other strains ( Fig 3E ) . Type one IFNs binds to interferon receptor and activates the transcription of genes containing an ISRE responsive element in their promoters . We also tested whether NS proteins from different DENV1 strains showed variable capacities to modulate the ISRE activation . The results suggested that NS proteins from DENV1B also showed the highest inhibitory activity on ISRE-Luc activity during RIG-I-N or IFNα stimulation ( Fig 3F and 3G ) . Consistently , RIG-I-N or IFNα induced transcriptions of typical ISG genes , such as IFIT1 and Cig5 , were significantly inhibited in DENV1B NS protein expressing cells ( Fig 3H and 3I ) . In line with this , we also confirmed that DENV1B showed a better replication than DENV1E in 293T cells if we treated the cells with IFNα . To confirm the functions of DENV1B NS2A , we constructed two mutant DENV1 replicon plasmids ( NS2A A64V and F159L ) based on the DGL2 replicon ( Fig 3J ) ( The NS2A proteins of DGL2 are 100% identical with that of DENV1B ) . The 64th Ala ( A ) and 159th Phe ( F ) of NS2A from DENV1B were changed to Val ( V ) and Leu ( L ) ( from DENV1E ) , respectively . DNA sequencing results indicated that the point mutation was successfully introduced into DGL2 replicon ( Fig 3K ) . After transfecting these replicons into 293T cells , we found that NS2A A64V mutation significantly impaired the replication efficiency of DENV1 replicon , but F159L substitution only slightly influenced the replication ( Fig 3L ) . These data suggested that NS2A amino acid position 64 is one of the important virulence determinants for DENV1 . Since NS proteins from DENV1B have higher capacity to inhibit IFN signaling , we wondered whether this is a major factor that determining the virulence of these five DENV1 strains . IFNAR1-/- mice were introduced to study the replication efficiency of DENV1 B and E in IFN non-responsive system . MEF cells from wild type and IFNAR1-/- mice were obtained and infected with DENV1 B and E , respectively . Surprisingly , DENV1B still has higher infection efficiency than DENV1E in IFNAR1-/- MEFs , just like what it does in wild type MEFs ( Fig 4A–4D ) . To further confirm this , IFNAR1-/- mice were challenged with DENV1B and E via intraperitoneal infection for 3 days , then the viral loads in blood and spleens were tested by qRT-PCR and plaque assay . The results suggested that the viral load in blood and spleen samples from DENV1B infected IFNAR1-/- deficient mice were significantly higher than that from DENV1E infected mice ( Fig 4E–4H ) . These data suggested that the difference in antagonizing IFN signaling is not the only determination factor for the virulence of these DENV1 strains . The results above remind us that the amino acid variations may not only contribute to the difference in virus-host interaction , but also determine the replication ability of the virus itself . In DENV’s life cycle , NS2B forms a complex with NS3 , and plays an important role in viral polyprotein procession . We then try to address whether amino acid changes in NS2B will directly influence viral protease function as well as viral replication . The mature forms of NS2B3 protease , which has a 48 amino acids NS2B co-factor domain ( 48–95 aa ) and 180 amino acids NS3 protease domain , have been cloned and expressed in recombinant GST prokaryotic expression system ( Fig 5A and 5B ) . The enzymatic assay suggested that NS2B3 protease from DENV1B showed higher substrate cleavage efficiency than NS2B3 from DENV1E ( Fig 5C and 5D ) . Using site-directed single point mutation technology , we made a K55R mutation in NS2B3 of DENV1B , in which the 55th amino acid Lys ( K ) was changed to Arg ( R ) ( which is from DENV1E NS2B ) , as well as a R55K mutation to NS2B3 of DENV1E ( Fig 5E and 5F ) . The enzymatic test showed that DENV1B NS2B3-K55R protein had lower enzymatic activity than wild type NS2B3 from DENV1B , while DENV1E NS2B3-R55K showed higher cleavage activity than wild type DENV1E NS2B3 ( Fig 5G ) . We then made a NS2B K55R mutation to DENV1 replicon DGL2 ( Fig 5H ) , and tested its replication efficiency . NS2B-K55R DGL2 replicon showed significantly lower replication efficiency than WT replicon ( Fig 5I ) . These results suggested that NS2B K55 is a virulence determinant that important for DENV1 NS2B3 protease activity and viral replication . While , there are also several amino acid differences in the NS3 1–180 protease domain between DENV1B and DENV1E . Our preliminary data suggested that these mutations may also slightly influence the activity of NS2B3 activity . Further study need be performed to characterize other potential virulence determinants in NS3 protease domain .
Viruses are small infectious agents that replicates only inside the living cells of other organisms . The viral genome only encodes a limited number of proteins which are necessary for viral structure and replication . Instead , viruses use the machinery and metabolism of a host cell to complete their life cycles . At the same time , viral infections provoke an immune response that usually eliminates the infecting virus . To counteract the host defense mechanism , many viruses have evolved suppressor proteins to overcome the antiviral responses . So that , the virulence of a virus will be determined by two aspects: one is the ability of virus utilizing or antagonizing host responses , the other is the essential functions of those viral proteins . A number of studies have reported single mutations in flavivirus protein influence the viral-host interactions , thereby determining the virulence of distinct virus . Yuan L et al . reported that S139N mutation in preM protein significantly increased the neurovirulence of Zika virus ( ZIKV ) , and this could be the reason why ZIKV caused more microcephaly since the outbreak of 2010s[29] . Xia H et al . identified the A188V substitution in ZIKV NS1 , which enhancing its IFN antagonizing activity [30] . The N124D and K128E mutations in DENV2 E protein reduced its heparin sulfate binding activity , and weakened the infectivity of mutated viruses[15] . In our current study , we also noticed that DENV1B NS proteins have stronger inhibitory ability against host IFN signaling . The A64V mutation in NS2A impaired the replication of DENV1 , suggesting that A64 NS2A is a novel virulence determinant that may influence virus-host interaction . At the same time , other studies suggested that variations in viral proteins may directly influence the viral protein functions . Some of DENV virulence determinants have been described , most of which locate at the E protein[14] . For example , the N67Q mutation in DENV2 E protein decreased virus growth , and N67 was identified as an important N-glycosylation site for this protein which is critical for viral assemble and budding[31] . Some substitutions in NS1 , NS4B , and NS5 proteins were evidenced to increase viral replicative fitness in native mosquitoes[32] . In this study , we also identified two novel virulence determinants in the genomes of DENV1 . The K55R substitution in NS2B results in an impaired protease activity of NS2B3 , thereby compromised the viral replication efficiency . The 64th amino acid of NS2A was also important for DENV1 replicon replication . The transmembrane topological structure of NS2A and NS2B[33–35] , as well as the 3D crystal structure of NS2B3[36] , were reported previously by several groups . By sequence alignment analysis , we found that 55th amino acid residue of NS2B was located near the end of the first β-strand structure of the NS2B cofactor domain , which could be critical for stabilization of NS3 protease . Mutations made to the 63-65th amino acids of NS2A displayed a lethal phenotype to DENV2 virus[35] . The 64th amino acid residue was located in the top of the hinge area of the third transmembrane helix domain which may influence the topology of NS2A . Beside of this , molecular evolution analysis also suggested an A9G variation in Capsid protein between DENV1 B and DENV1 E ( S2 Table ) . In the ViPR database , almost all of the Capsid proteins from DENV1 strains are A9 , and only 52 strains which are G9 . This suggests that the 9th Alanine residue may be the dominant virulence loci . There are also a 20nt deletion in 3’UTR region of DENV1 D and E compared with DENV1 A-C , and this deletion may interfere with the stability of a SL1 loop in the 3’UTR , which is critical for the sfRNA generation[21] . Further study will be required to explore those potential virulence determinants for DENV1 . We should also mention that even though we have confirmed that NS2A A64V and NS2B K55R mutations in replicons of DENV1B backbone have defect replication efficiencies than wild type replicon , the reverse mutations of these amino acids in a replicon with DENV1E backbone should also be important to support these findings . Further experiments will be performed to address this question . Taken together , we compared the difference of replication efficiency and virulence of five DENV1 variants . We found that DENV1B is the most virulent virus , and DENV1E is the weakest . We further suggested that the 64th amino acid of NS2A and 55th amino acid of NS2B were potential virulence determinants of DENV1 , which provided a theoretical basis for better understanding the molecular mechanisms of DENV virulence . It also provides new ideas for investigation of DENV protein function , pathogenic mechanism and novel attenuated vaccine .
The HUVEC ( Human Umbilical Vascular Endothelium Cells ) and PBMC ( human Peripheral Blood Mononuclear Cells ) were obtained from BeNa Culture Collection ( Bejing , China ) . The projects using of human biological specimens were approved by an institutional review board ( IRB ) of Soochow University . Animal experiments were conducted according to the Guide for the Care and Use of Medical Laboratory Animals ( Ministry of Health , People’s Republic of China ) and approved by the Animal Care and Use Committee as well as the Ethical Committee of Soochow University ( No . SYSK- ( S2012-0062 ) ) . Five different DENV1 viruses , isolated from the DENV outbreak of 2014 in Guangdong , were obtained from CDC of Guangdong province . The viruses were propagated in mosquito C6/36 cells ( ATCC CRL-1660 ) . 293T , Huh7 . 0 and Vero cells were obtained from ATCC ( Manassas , USA ) and grown in DMEM ( Life Technologies , Grand Island , USA ) supplemented with 10% FBS and antibiotics/antimycotics . HUVECs were grown in 1640 ( Life Technologies ) supplemented with 10% FBS and antibiotics/antimycotics . Mouse embryonic fibroblasts ( MEFs ) were prepared from the mouse embryo using standard protocols [37] . Cells were infected with DENV at a multiplicity of infection ( MOI ) of 0 . 5 , unless otherwise stated . BABL/C and C57BL/6J mice were obtained from Shanghai Laboratory Animal Center ( Shanghai , China ) . IFNAR1-/- mice ( in a C57BL/6J background ) were prepared by Institute of medical laboratory animal research , Chinese Academy of Medical Sciences ( Beijing , China ) . All the animals were maintained in a biosafety level 2 animal facilities . Total RNA from DENV infected cells were extracted using the total RNA kit I ( OMEGA , USA ) and reverse-transcribed using the PrimeScript Master Mix kit ( TaKaRa , Japan ) . cDNAs were mixed with RT-PCR primers and SYBR Premix Ex Taq II ( TaKaRa , Japan ) and amplified for 40 cycles ( 95°C 15 s , 60°C 30 s , and 72°C 15s ) . The intracellular viral loads , in terms of transcript levels of the specific viral genes , were quantified through qRT-PCR and normalized to β-actin gene . The mRNA expression levels of human IFNβ1 , IFIT1 , and Cig5 genes were also determined via qRT-PCR . ( Oligo-primer sequences for qRT-PCR of this study were shown in S1 Table ) . The titers of DENV in cell-free supernatants or tissue extracts were determined with a median tissue culture infective dose ( TCID50 ) assay and plaque assay according to protocols previously described [38 , 39] , with slight modifications . Briefly , samples were serially diluted and inoculated into Vero cells in 96-well plates . After 5-day incubation , cells were fixed with 4% paraformaldehyde , stained with 10% crystal violet buffer , and examined for cytopathic effects ( CPE ) and plaque formation under a light microscope . The virus titer ( TCID50/ml ) was calculated using the Reed-Muench method . 1 TCID50/ml was equivalent to 0 . 69 pfu/ml[40] . DNA-based replicons ( for DENV type 1 ) expressing secreted Gaussia luciferase ( DGL2 ) , were generously provided by Dr . Takayuki Hishiki ( Kyoto University , Kyoto , Japan ) [28] . The point mutations to the DGL2 replicon were obtained by using the QuickChange Site-directed Mutagenesis kit ( Agilent Technologies , USA ) according to manufacturer’s instructions . For the Gaussia luciferase assay , 50 ng of DGL2 replicon plasmid was transfected into 293T cells in 96-well plates . Culture supernatants were collected at different time points and luciferase was measured using BioLux Gaussia Luciferase Assay Kit ( New England Biolabs , UK ) according to manufacturer’s instructions . Each 3- or 4-day-old BABL/C suckling mouse was inoculated intracerebrally with 100 PFU of DENV1 A-E respectively as previously described[41] . Animals were monitored for 21 days to evaluate the morbidity and mortality . The DENV replication levels in cerebrum at day 4 were measured by qRT-PCR method described above . For infection of IFNAR1-/- mice , 4–6 week-old IFNAR1-/- mice were infected with 1×107 PFU of DENV1B or DENV1E respectively by intraperitoneal injection . At day 3 post infection , mice were euthanized and the viral loads in whole blood cells and spleens were determined by qRT-PCR and plaque assays as described above . The ORFs of NS2A , 2B , 4A and 4B from DENV1 A-E were subcloned into a eukaryotic expression vector pcDNA3 . 1A-His/Myc individually . The expressions of NS proteins were confirmed by western blot using anti-His Antibody ( Sigma , USA ) . Prokaryotic expression plasmids for protease NS2B3 of DENV1 B and E ( and NS2B3 mutants ) were constructed as described previously[11 , 18 , 42] . Briefly , the coding region of NS2B enzyme co-factor domain ( 48–95 aa ) and NS3 protease domain ( 1–180 aa ) were amplified by nested PCR using the primers listed in the S1 Table , and cloned into the pGEX-6p2 bacterial expression vector . Then the pGEX-NS2B3 constructs were transformed into Escherichia coli strain BL21 ( DE3 ) for protein expression . The GST-tagged recombinant proteins were induced with 0 . 1mM IPTG at 30°C for 4 h and purified using GST affinity agarose ( GE Healthcare , Sweden ) . The GST tag was removed by Prescission Protease ( Sigma , USA ) . IFNβ- or ISRE-Luciferase reporter assay was performed as described previously[39 , 43] . Briefly , 293T cells were transfected with IFNβ- Luc ( or ISRE-Luc ) ( Firefly luciferase , experimental reporter , 100 ng/well ) and pRL-TK reporter ( Renilla luciferase , internal control , 5 ng/well ) plasmids ( Clontech , USA ) , IFNβ activator RIG-I-N ( the active caspase recruitment domain ( CARD ) containing form of RIG-I ) , together with individual NS proteins from DENV1 A-E or vector control . ( For ISRE-Luc assay , cells were also treated with IFNα ( 1000 U/ml ) for 6h instead of stimulation with RIG-I-N transfection . ) 24 h post-transfection , cells were lysed and the luciferase activity was measured using a Dual Glow kit according to the manufacturer’s instructions ( Promega , USA ) . Various concentration of purified recombinant NS2B3 from DENV1B , E and 1B K55R ( or 1E R55K ) mutants were incubated with DENV1 substrate Ac-EVKKQR-pNA [42] ( GL Biochem , Shanghai , China ) at 37°C for indicated time courses , respectively . Enzymatic assay were carried out with the following buffers: 50 mM Tris-HCl , 10mM NaCl , 20% glycerin , 1mM CHAPS , pH 9 . 2 . The substrate cleavage efficiencies were analyzed by measuring the OD value at 405nm as described before[42] . Prism 7 software ( GraphPad Software ) was used for survival curves , charts and statistical analyses . The significance of results was analyzed using ANOVA followed by Tukey’s test for multiple comparisons , Student’s t-test ( for comparisons between two groups ) and Log-rank ( Mantel-Cox ) Test ( for survival data ) , with a cutoff P value of 0 . 05 . | Dengue is the most important vector-borne viral infection that endangers an estimated 2 . 5 billion people globally . The recently licensed dengue vaccine has major weaknesses and there are no antiviral drugs for the treatment of dengue related diseases . Identifying the virulence determinants is important for understanding the molecule bases of viral life cycle , also contributing to vaccine design and development . In this study , we analyzed the virulence differences among five DENV1 strains that obtained from the 2014 DENV outbreak in Guangzhou , China , and identified two novel virulence determining sites for DENV1 . This study provides new ideas for investigation of DENV protein function , pathogenic mechanism and novel attenuated vaccine . | [
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] | 2019 | Virulence difference of five type I dengue viruses and the intrinsic molecular mechanism |
Sri Lanka was acknowledged to have eliminated lymphatic filariasis ( LF ) as a public health problem in 2016 , largely due to its success in Mass Drug Administration ( MDA ) to interrupt disease transmission . Analysis of the Strengths , Weaknesses , Opportunities and Threats ( SWOT ) of the national Morbidity Management and Disability Prevention ( MMDP ) program , the other pillar of the LF control program , was carried out with the objective of evaluating it and providing recommendations to optimize the use of available resources . A situation analysis of the MMDP activities provided by the state health sector was carried out using published records , in-depth interviews with key informants of the Anti Filariasis Campaign , site-visits to filariasis clinics with informal discussions with clinic workforce and personal communications to identify strengths and weaknesses; and opportunities to overcome weaknesses and perceived threats to the program were explored . The principal strength of the MMDP program was the filariasis clinics operational in most endemic districts of Sri Lanka , providing free health care and health education to clinic attendees . The weaknesses identified were the low accessibility of clinics , incomplete coverage of the endemic region and lack of facilities for rehabilitation . The perceived threats were diversion of staff and resources for control of other vector-borne infections , under-utilization of clinics and non-compliance with recommended treatment . Enhanced high level commitment for MMDP , wider publicity and referral systems , integration of MMDP with other disease management services and collaboration with welfare organizations and research groups were identified as opportunities to overcome weaknesses and challenges . The recommended basic package of MMDP was functional in most of the LF-endemic region . The highlighted weaknesses and challenges , unless addressed , may threaten program sustainability . The identified opportunities for improvement of the programme could ensure better attainment of the goal of the MMDP program , namely access to basic care for all affected by lymphatic filarial disease .
A total of eight districts ( Colombo , Gampaha , Kalutara , Galle , Matara , Hambantota , Puttalam and Kurunegala ) belonging to three provinces ( Western , Southern and North Western ) in Sri Lanka were identified as endemic for LF during the elimination program ( see Fig 1 ) . Post-MDA surveillance in the endemic region revealed low-level persistence of bancroftian filariasis in a few areas and re-emergence of brugian filariasis after four decades [16] , both of which require continued individual treatment . Reduction of microfilaria rates below the target threshold of 1% , following five successful rounds of MDA ( DEC + albendazole ) , enabled the submission of the elimination dossier in 2015 . In 2016 , Sri Lanka received validation from WHO of having eliminated LF as a public health problem [17] . Given the high profile efforts required to interrupt transmission , morbidity management has been given rather lower priority . The current status of the MMDP program was assessed using the SWOT analysis tool , within the context of recent validation of LF elimination in Sri Lanka . SWOT analysis is defined as an examination of an organization’s internal strengths and weaknesses , the opportunities for growth and improvement , and the threats posed by the external environment to its survival [18] . This process was originally designed for use in the corporate sector and although novel , is gaining recognition for use in healthcare . Ideally SWOT analysis includes a comprehensive review of healthcare literature , in-depth data analysis and input from a panel of experts [18] . Findings from the analysis are sorted into four broad categories; strengths , weaknesses , opportunities and threats . This tool provides a framework for reviewing the program in an inter-disciplinary manner and brings the organization into balance with the external environment and maintains that balance over time . The goal of the SWOT analysis was to evaluate the MMDP program and services with the intent of providing recommendations for maximizing organizational performance with the limited resources available for achieving the goals of the MMDP program , i . e . , to provide access to basic care for all affected by lymphatic filarial disease .
In order to identify the strengths and weaknesses within the MMDP program and the opportunities and threats from outside the AFC and its MMDP program , a situation analysis was carried out in June 2017 . The national Anti-Filariasis Campaign ( AFC ) is responsible for implementation of disease prevention and control strategies , which include conduct of filariasis clinics which are the main MMDP service providers . Data was collected for the SWOT analysis by reviewing LF data published in reports of the AFC , by in-depth interviews with identified key informants of the AFC and Regional Filariasis Control Units ( RFCU ) , site-visits and focus group discussions with service providers of MMDP ( filariasis clinics ) . Facts extracted from peer reviewed publications on patient based surveys and personal communications were also included in the analysis . The key-informants included a Specialist Community Physician , Medical Officer , Public Health Nursing Sister , Public Health Inspector identified from the AFC ( n = 4 ) , and the RFCUs ( Medical Officers , Public Health Field Officers and Public Health Inspectors , n = 6 ) . Two open ended questions were included into interviews and group discussions to evaluate service performance and perceived challenges to MMDP program , namely , practices implemented for management of lymphoedema in their respective units and the challenges and obstacles faced by the respective units in implementing the program activities , especially those perceived to be linked to LF elimination status . Knowledge and adherence to disease management guidelines , adequacy of staff and vacant cadre positions , staff training and supervision and , the extent of political commitment for the MMDP program were also areas that were probed at interviews and group discussions . All interviews and discussions were conducted by persons external to the AFC and recorded with the consent of the informants to minimize data loss during transcription . Information on clinic performance was extracted from the annual bulletins of the AFC , and lymphoedema management practices of clinic attendees and reasons for underutilization of clinics were extracted from peer reviewed publications , conference proceedings and personal communications . Existing external resources for improving the program were explored and identified as opportunities . The information thus gathered was evaluated and categorized into four broad themes: strengths , weaknesses , opportunities and threats .
The AFC was established in 1947 to reduce the burden of LF in Sri Lanka . It enabled LF elimination status by its early commitment to annual MDA , and has been documented as one of the finest LF elimination programs [19] . The AFC is headed by a director , supported by a deputy . It has cadre provision for many different categories of health personnel: specialist community physicians , medical officers , nursing sisters , public health inspectors , field assistants , laboratory staff , entomologists and assistants and administrative personnel ( officers and support staff ) . Activities related to filariasis control and morbidity management launched by the AFC were disseminated to the provinces via the RFCU . RFCUs have been established in seven of the eight endemic districts . The RFCUs , together with the AFC , continued with xenomonitoring guided enhanced surveillance to trace residual foci of infection and treated such persons with a 12-day regimen of DEC combined with a stat dose of albendazole and provided morbidity management services for lymphoedema patients . The AFC provided technical expertise , conducted staff training programs for new recruits and acted as the central body coordinating activities between the center and the periphery . The surveillance and morbidity data were submitted quarterly by RFCUs to the AFC , which compiled and disseminated the data in the form of quarterly and annual bulletins . Nine of the ten interviewees identified staff shortages as the main weakness . At the time of the analysis , there were vacant positions in all categories of staff ( medical officers , field officers , entomological officers , laboratory technicians and labourers ) with significant gaps in expertise ( medical parasitologist , health educationists ) within the work force of the AFC and RFCUs . Lack of complete coverage of the entire endemic region was a major deficiency . One endemic district in the Southern Province ( Hambantota district ) lacked LF morbidity alleviation services . This was seen as an unacceptable situation , particularly because those affected with lymphoedema and elephantiasis have multiple issues associated with mobility ( worsening of oedema , pain and discomfort , unwillingness to use public transport due to social stigma and shame ) which would deter them from seeking treatment from distant clinics [5 , 25] . In some districts that did have RFCUs and Filariasis Clinics , the accessibility of services was somewhat deficient , as the frequency of clinic sessions was low ( weekly in Kurunegala ) [26] . Limiting clinic sessions to weekdays also reduced their accessibility to patients who were employed . Morbidity management for hydroceles was provided by the state health sector and was thus accessible to all affected . However , little information on hydrocelectomies was available to the MMDP program , which was identified as a rectifiable weakness . Although the advantages of community home-based care ( CHBC ) in LF morbidity alleviation have been well documented [23 , 25] , it is yet to be implemented in Sri Lanka . Lack of indicators to measure successful management of morbidity ( e , g . , stage regression of lymphoedema , reduction of frequency of ADLA , improvement in quality of life ) and similar targets for evaluating program success , was another deficiency identified within the program [27] . Guidelines or care-pathways for disability management and rehabilitation of those with disability were also yet to be established . Some of the challenges were consequent to achievement of LF elimination status . The most imminent threat perceived by eight of ten key informants ( AFC ) , was the diversion of staff and resources of the AFC and RFCUs for control of other vector-borne infections such as dengue , which were regarded as more important due to its associated mortality . Loss of alliances and funding was another factor that was regarded by majority of interviewees ( 70% ) as hindering expansion and strengthening of the MMDP program , especially its rehabilitation component . The available treatment facilities were greatly underutilized , partly attributed to lack of awareness of their existence even among the medical community . Other reasons for underutilization of clinic services were , lack of confidence with regard to efficacy of recommended therapy ( experienced by 83% of a case cohort of lymphoedema patients in Matara [28] ) , the costs associated with attending clinics ( reported by Perera et al and Yahatugoda et al [5 , 25] and the social stigma of being labelled as a case of filariasis by attending clinics ( reported by the majority of females ( 71% ) and 42% of males in the Matara study [28] as well as in others[5] . Another challenge to scaling up the morbidity alleviation programme was the dearth of evidence on how best to integrate the services into the existing health systems . Strong high level commitment within the Ministry of Health for LF morbidity alleviation and disability management was regarded as essential for sustaining and strengthening the MMDP program . Integrating filariasis management with management of other chronic diseases such as diabetes , leprosy or non-filarial lymphoedema ( establishment of lymphoedema management centers rather than filariasis clinics ) was recommended as it would be cost-effective . Such a strategy would maximize the use of limited resources as well as overcome the social stigma of being labelled as a case of ‘filariasis’ , by reason of attending filariasis clinics . Publicity campaigns to raise awareness of treatment centers would be a simple way to improve their utilization . This could be achieved by displaying posters and banners at community centers , hospitals and other health care facilities . Establishment of referral systems through primary health care providers ( medical officers , general practitioners , and field staff ) would further improve utilization of clinics . Primary health care providers such as general practitioners , medical officers at hospital out-patients-departments and even consultants , require to be up-dated on current lymphoedema management strategies to ensure provision of appropriate care . Collaborations with Non-Governmental Organizations and research groups would provide opportunities for national program managers to obtain much needed funds and expertise for the program . Inter-ministerial collaborations for provision of rehabilitation facilities that were beyond the purview of the Ministry of Health ( eg , Department of Social Services under Ministry of Social Empowerment Welfare and Kandyan Heritage ) was identified as another opportunity to rehabilitate those with disability . The importance of conducting evidence based and operational research for optimizing management ( e . g . newly adopted triple therapy in the management of lymphoedema ) and service delivery ( integration of MMDP into primary health care system ) is emphasized .
The recommended minimum package for morbidity alleviation of LF is functional in most parts of the endemic area of Sri Lanka . However , the MMDP program has significant weaknesses and threats that need to be addressed , in order to enable national program managers to scale up and strengthen the program . | Lymphatic filariasis ( LF ) is a tropical disease causing swelling of limbs ( lymphoedema , elephantiasis ) and male genitalia ( hydrocele ) . It is a disabling and deforming disease caused by parasitic worms transmitted by mosquitoes . The Sri Lankan Anti Filariasis Campaign was successful in reducing LF transmission to very low levels by annual mass drug administration , resulting in recent achievement of elimination status . The other pillar of LF elimination is the management of morbidity and disability prevention ( MMDP ) among those with lymphatic filarial disease . The strengths , weaknesses and threats of the MMDP program were evaluated and opportunities for improvement were explored in June 2017 . The filariasis clinics established in the endemic area , providing care for patients with lymphoedema and elephantiasis , were identified as the main strength . Hospital surgical units were important in the treatment of hydrocele . The weaknesses were low accessibility of clinics , incomplete coverage of endemic districts , lack of facilities for rehabilitation and lack of morbidity targets . The threats were diversion of staff and resources , under-utilization of clinics , social stigma and loss of alliances . Enhanced commitment to improve coverage and access to clinics in the endemic areas , wider publicity , referral systems , integration of MMDP into other disease management services , collaborations with welfare organizations and research groups were the opportunities identified . | [
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] | 2018 | Morbidity management and disability prevention for lymphatic filariasis in Sri Lanka: Current status and future prospects |
Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure . We investigated the evolution of small , adaptive logic-gate networks ( “animats” ) in task environments where falling blocks of different sizes have to be caught or avoided in a ‘Tetris-like’ game . Solving these tasks requires the integration of sensor inputs and memory . Evolved networks were evaluated using measures of information integration , including the number of evolved concepts and the total amount of integrated conceptual information . The results show that , over the course of the animats' adaptation , i ) the number of concepts grows; ii ) integrated conceptual information increases; iii ) this increase depends on the complexity of the environment , especially on the requirement for sequential memory . These results suggest that the need to capture the causal structure of a rich environment , given limited sensors and internal mechanisms , is an important driving force for organisms to develop highly integrated networks ( “brains” ) with many concepts , leading to an increase in their internal complexity .
Many studies have sought to elucidate the role of information in evolution [1]–[4] , its relation to fitness [5]–[7] , and how information about the environment is acquired and inherited by an organism [8] , [9] . Common to most current approaches to characterize and quantify information in biology is the notion that biological information has to be physically implemented and should be functional , meaning valuable to the organism and related to the environment [3] , [4] , [9] . There is also growing interest in how measures of information can shed light on the apparent growth in complexity during evolution [2] , [10]–[12] . Artificial adaptive agents ( “animats” ) have proven useful for investigating how various information and complexity measures change during evolution [6] , [7] , [13] . Animats consist of small neural networks ( “brains” ) , with sensors , hidden elements , and motors , which are evolved under selection based on task fitness . In recent work we used animats consisting of Hidden Markov elements evolving in a task environment that requires integrating current sensor inputs with memory . We showed that the animats' increasing fitness is associated with an increase in the capacity to integrate information [6] , [7] . In this study , we extend these initial results in two ways . First , we evaluate the animats' capacity for integrated information using the comprehensive set of measures recently introduced in the context of integrated information theory ( IIT 3 . 0 , see Box 1 and [14] , [15] , for previous versions see [16] ( “IIT 2 . 0” ) and the original formulation for stationary systems [17] , [18] ( “IIT 1 . 0” ) ) . Specifically , we ask whether adaptation to an environment leads to an increase in the number of evolved concepts and in the total amount of integrated conceptual information ( ΦMax , “Big Phi” ) . Second , we compare how different task environments influence the evolution of animats and their capacity to integrate information depending on memory requirements and size of the sensory-motor interface . In this way , we aim to elucidate under which conditions integrated brains with high ΦMax become advantageous . Information-theoretic approaches to assess the evolved complexity of ( artificial ) organisms are typically based on extrinsic correlational measures , either between the system's genome and its environment [8] , [19] or between the system's sensors and motors [20] ( sensory-motor information ) , or between successive system states [6] , [7] ( predictive information [21] ) . By contrast , IIT quantifies information from the intrinsic perspective of the system , based on the causal power of its internal mechanisms - the “differences that make a difference” within the system [14]–[16] , [18] , [22] , [23] . In the animats employed here , a mechanism consists of one or more system elements that , at a given time , are in a particular state ( on or off ) . A mechanism in a state specifies a concept if it meets the following conditions ( see Methods for details ) . First , the mechanism must specify which past and future states of the system are possible and which are not ( information ) . The particular way in which it does so constitutes its cause-effect repertoire , the probability distribution of past and future system states given the current state of the mechanism . Second , its cause-effect repertoire must be irreducible to that specified by sub-mechanisms ( integration ) . Irreducibility of a mechanism is assessed by measuring its integrated information φ ( “small phi” ) - the distance between the cause-effect repertoire of the intact mechanism and that of its minimum partition ( MIP ) , which renders the weakest connection of the mechanism causally ineffective . φ thus quantifies how much causal information is lost due to the MIP . A mechanism can specify only one cause-effect repertoire , the one that is maximally irreducible ( exclusion , φMax , see Methods ) . This constitutes its concept—what the mechanism in a state “does” for the system from the intrinsic perspective of the system itself . The set of all concepts and associated φMax values generated by a set of elements constitutes a conceptual structure ( information , see Methods for details ) . As for individual concepts , the integration of a conceptual structure can be evaluated by measuring the distance Φ ( “big phi” ) between the conceptual structure of the intact set and that of its minimum ( unidirectional ) partition ( see Methods ) . Within some animats , a set of elements may generate a maximally integrated conceptual structure ( ΦMax ) , which constitutes a main complex ( MC , exclusion ) . Other animats may not contain complexes ( Φ = 0 ) because their brains are constituted of functionally segregated modules with feed-forward architecture ( containing at most self-loops ) [15] . In sum , Φ can be viewed as a measure of complexity , since only systems with many specialized , but integrated mechanisms have high Φ , whereas systems that have only a few different mechanisms and/or are very modular have low or no Φ [15] , [16] , [22] . From an engineering point of view , modular systems with segregated functions are much simpler to design and understand than integrated systems . However , simplicity of design is not an issue for evolution by natural selection . Instead , important factors are economy of elements/wiring [24] , composition of functions [14] , degeneracy ( multiple ways to achieve the same function ) [25] , adaptability in the face of change [26] , [27] , integrated control [14] , and robustness to failure [28] . These factors should favor the evolution of organisms with integrated brains in an environment that is complex , changing , and requires sensitivity to context [14] , [25] , [29] . Based on these considerations , we predict that measures of integrated information should increase with the complexity of the environment . Specifically , i ) evolving animats should show an increase in the number of concepts; ii ) integrated conceptual structures should become larger and more irreducible; iii ) the increase in concepts and integrated conceptual structures should be related to the complexity of the environment and to the requirements for memory . Moreover , to the extent that IIT is correct in claiming that the capacity for information integration underlies consciousness [14] , [15] , [18] , [23] , finding an increase in animats' ΦMax values in complex environments would provide a plausible account of why and how consciousness evolved . In what follows , we test and confirm these predictions by evolving animats solving perceptual categorization tasks [13] , [30] in task environments that vary in the amount of sequential memory necessary to solve the task optimally . The results show that , given strict constraints on the number of elements in the animat's brain , integrated network architectures become advantageous over modular or feed-forward architectures when the environment was more complex . Moreover animats with restrictions on the number/fidelity of their sensors or motors evolved more concepts and larger integrated conceptual structures , in line with an increased reliance on memory .
Each animat is equipped with a fixed number of sensors , hidden elements , and two motor outputs ( to move either left or right , see Fig . 1 ) . All elements are binary Markov variables , whose value is specified by deterministic logic gates . Each animat has a genome , which encodes the wiring diagram of the animat's brain and the logic functions of its elements . More precisely , each gene specifies a hidden Markov gate ( HMG ) and all HMGs together determine the brain's causal structure ( see Methods and [6] , [13] ) . The animats are allowed to evolve over 60 , 000 generations using a genetic algorithm , starting with an initial population of 100 animats without connections between brain elements ( generation zero ) . To compose the next generation , the genetic algorithm selects a new sample of 100 animats based on an exponential measure of the animats' fitness ( roulette wheel selection ) . The genome of each selected animat is mutated according to three probabilistic mutation mechanisms ( point mutations , deletions , and duplications ) [13] . The mutated genomes then determine the wiring diagrams and logic functions of the next animat generation , which are tested for fitness in the respective task environment . In sum , adaptation arises through mutation and selection driven by the animat's task performance . Throughout this study , the animats' task environments are variants of “Active Categorical Perception” ( ACP ) tasks [13] , [30] , where moving blocks of different sizes have to be distinguished in a ‘Tetris-like’ game ( Fig . 1B ) . Adaptation is measured as an increase in fitness , where fitness corresponds to the fraction of successfully caught or avoided blocks within a fixed number of trials ( 128 for each animat at each generation , with one falling block per trial ) . Blocks move sideways and down at 1 unit per time step either to the right or left starting from one of 16 possible initial positions . If a block moves out on the left it will reappear on the right and vice versa . A block is “caught” if the animat overlaps with at least one of its units when it reaches the bottom ( after 36 time steps ) ; otherwise the block is “avoided” . Each animat's size is 3 units , with a space of 1 unit between the two sensors ( a “blind spot” ) . Therefore , only blocks of size ≥3 can activate both sensors at the same time ( Fig . 1C , D ) . Note that the sensors of the animat convey limited information about the environment and only at a single time step , yet solving ACP tasks successfully requires integration of sensor inputs over multiple time steps . Hence , information about past sensor states ( memory ) has to be stored through the states of internal elements . At the end of each evolutionary run at generation 60 , 000 , the line of descent ( LOD ) of one animat is traced back through all generations . Every 512 generations along the LOD , a transition probability matrix ( TPM ) is generated for all possible states of the animat's brain , which captures how the brain transitions from one state to another . From these TPMs , concepts and integrated conceptual information Φ can be calculated across the LOD . We averaged the causal measures for a particular generation in one LOD across all network states experienced by the animat during the 128 test trials , weighted by their probability of occurrence . For each task condition , 50 independent LODs were obtained , each from a different evolutionary run . To investigate how the number of concepts and their integration depends on the causal structure of the task environment , we tested the animats in four tasks ( Task 1–4 ) with different block categories and strategic requirements ( Fig . 1E ) . Given the periodic boundary conditions and the fact that the animats can actively explore their environment , predicting the evolutionary difficulty of an ACP design is not straightforward . Nevertheless , if solving a task requires more memory of input sequences , the number of concepts developed by the animats should increase . Since the number of evolvable hidden elements is limited to four , the number of time steps that can be combined without feed-back between elements and thus Φ = 0 ( see Methods and [15] ) is limited , too . Higher memory requirements should thus bias the animats towards developing brains with more integrated conceptual structures with larger main complexes and higher Φ . As a first simple task environment ( Task 1 ) , the animats have to catch blocks of size 1 and avoid blocks of size 3 . In Task 1 , the two block conditions can in principle be distinguished based on a momentary sensor state ( S1S2 = 11 , see Fig . 1C , D ) . Categorization can thus be achieved in a modular manner ( e . g . , “if S1S2 = 11 avoid , else follow” ) . However , memory is still required to identify the direction of the moving blocks , since sensor information of at least two time steps must be combined to infer movement direction . Task 1 will serve as the comparison environment in the following sections . In Task 2 , the blocks to be avoided are smaller ( 2 units ) . Consequently , the two block categories cannot be distinguished based on a single sensor state , since neither block can activate both sensors at the same time . Here , memory is required for both categorization of block size and direction . In Task 3 , four instead of just two different block sizes have to be distinguished . The blocks to be caught ( size 1 and 4 ) and avoided ( size 2 and 3 ) cannot be distinguished based on a single threshold ( e . g . “≥3” ) , nor based on a single sensor state . Adaptation to Task 3 is thus expected to be more difficult . However , sensor state S1S2 = 11 allows distinguishing blocks of size 1 and 2 from blocks of size 3 and 4 . Whether to catch or avoid a block can then be decided based on a memory of one time step , just as in Task 2 . Note also that in Task 3 at least 75% fitness can be achieved with the same categorization strategy as in Task 2 ( “≥2” ) . Therefore , more concepts than in Task 2 are expected only for fitness levels>75% . Finally , in Task 4 , four blocks of sizes ≥3 have to be distinguished . To successfully catch blocks of size 3 and 6 and avoid blocks of size 4 and 5 the animats have to combine memory of at least 3 time steps . In sum , the evolutionary pressure to develop brains with integrated concepts should be lowest for Task 1 , intermediate for Task 2/3 , and highest for Task 4 , in line with the requirements of sequential memory in Task 1–4 . According to IIT , both the average number of concepts and their integration ( ΦMax ) should therefore be highest in Task 4 and lowest in Task 1 . Throughout the following analysis , the animats are evaluated in two ways: first , all concepts and the sum of their φMax values are calculated for the animat's brain as a whole , including the sensors , motors , and all hidden elements . These measures quantify all causal relations ( “IF-THEN” ) in the animat's brain . Second , the main complex ( MC ) within the animat's brain is identified and the number of elements that form the MC ( “MC elements” ) , the number of concepts in the MC ( “MC concepts” ) , and its ΦMax value are calculated according to IIT 3 . 0 [15] . These measures quantify the amount of integration in the animat's brain . In this way , increases in fitness that rely on integrated structures can be distinguished from those that can be achieved with modular networks with feed-forward architecture ( containing at most self-loops ) . Fig . 2 illustrates all the causal measures of a potential animat brain in one particular state . The maximal possible number of concepts specified by an animat's brain is 15 ( 24−1 , the power-set of all hidden elements excluding the empty set , see Fig . 2B ) . An animat's main complex can , at most , comprise the 4 hidden elements . Determining upper bounds for ΣφMax and ΦMax is not straightforward ( see S1 Text ) . In the present set of simulations , the overall highest observed values for an animat in a particular state were ΣφMax = 3 . 11 and ΦMax = 4 . 125 . Note that all the above measures are state-dependent [15] . At a particular generation , these measures are evaluated for every brain state experienced by the animat during the test trials . The resulting state-dependent values are then averaged , weighted by the probability of occurrence of each brain state . Fig . 3 shows the evolution of all causal measures during adaptation over 60 , 000 generations in all four task conditions . For each task condition , 50 independent LODs are assessed every 512 generations . In Table 1 , the average Spearman rank correlation coefficients across all 50 LODs are listed for all measures and tasks . As previously observed in a different kind of task environment [7] , trial-by-trial correlation coefficients with fitness were rather broadly distributed ( see histograms in S1 Fig . ) . While the causal measures are interrelated to some extent and the MC measures in particular tend to correlate , dissociations among them occur for individual LODs ( see S2 Fig . for examples ) . Task 1 ( Fig . 3 , 1st column ) : At generation 59 , 904 the average fitness across all 50 LODs was 94 . 2±0 . 7% ( mean ± SEM ) ; in 13 out of 50 evolutionary lines the animats reached perfect fitness . On average , all causal measures were found to increase during the initial steep rise in fitness . The number of concepts and their ΣφMax values measured in the whole animat brain showed significant positive correlation with fitness ( p<0 . 05 ) in 34/50 LODs . MC measures only correlated positively with fitness in 12/50 LODs ( S1 Fig . ) , reflecting the fact that both modular ( functionally segregated ) and integrated concepts can lead to an increase in fitness . In other words , not every increase in fitness requires an increase in integration . In the case of Task 1 , perfect categorization can be achieved with a purely modular ( no MC , ΦMax = 0 , 7/13 animats ) as well as with an integrated network ( ΦMax>0 , 6/13 animats , see below , Fig . 4 ) . Task 2 ( Fig . 3 , 2nd column ) : In terms of adaptation , Task 2 was as difficult as Task 1 since the same level of fitness was reached ( 94 . 0±1 . 2% ) . Perfect fitness was achieved in 22/50 LODs . 16 out of these 22 animats developed integrated brains . Compared to Task 1 ( black ) , with increasing fitness in later generations the animats developed brains with more concepts and higher ΣφMax values in Task 2 ( U98 = 695 . 5/749 . 0 , Z = −3 . 844/−3 . 454 , p = 0 . 000/0 . 001 respectively for #concepts/ΣφMax averaged across the last 3 , 000 generations ) . MC measures in Task 2 increased more subtly , but reached higher values than in Task 1 ( U98 = 985/966/922 , Z = −1 . 899/−2 . 035/−2 . 350 , p = 0 . 058/0 . 042/0 . 019 respectively for #MC elements/#MC concepts/ΦMax ) . The number of LODs with significant positive correlation with fitness ( p<0 . 05 ) was also higher than in Task 1 for number of concepts and ΣφMax ( 42/50 ) and MC measures ( 24/50 ) . Task 3 ( Fig . 3 , 3rd column ) : The average fitness reached at generation 59 , 904 was 82 . 9±1 . 0% . Perfect fitness was achieved only temporarily in one LOD ( with final fitness 98 . 4% ) . The average number of concepts and ΦMax evolved to higher values in Task 3 compared to Task 1 ( black ) ( U98 = 854/899 , Z = −2 . 746/−2 . 530 , p = 0 . 006/0 . 011 for #concepts/ΦMax ) , while ΣφMax and the number of MC concepts and MC elements stayed comparable to those of Task 1 . To compare the different tasks without confounding effects due to differences in fitness , a subset of LODs with high final fitness was chosen out of the 50 LODs of Task 3 , so that the average fitness across the last 5 , 000 generations matched that of Task 1 ( 9 fittest LODs , shown in dark red ) . When compared at the same level of fitness , all causal measures evolved to significantly higher values , except for the number of MC concepts , which still almost reached significance p<0 . 05 ( U57 = 77 . 5/71 . 0/136/141/112 , Z = −3 . 143/−3 . 247/−1 . 999/−1 . 886/−2 . 538 , p = 0 . 002/0 . 001/0 . 046/0 . 059/0 . 011 respectively for #concepts/ΣφMax/#MC elements/#MC concepts/ΦMax ) . As predicted , the evolutionary pressure for concepts and integration in Task 3 appeared to be comparable to that of Task 2 . Accordingly , trial-by-trial positive correlation with fitness in Task 3 was also similar to Task 2: number of concepts and ΣφMax correlated significantly with fitness in 39/50 LODs; MC measures correlated significantly with fitness in 24/50 LODs . At comparable average fitness levels , the fact that four instead of just two blocks had to be distinguished only led to a marginal increase in the number of concepts and their integration , since the requirement for sequential memory remained comparable between Task 2 and 3 . Solving the more difficult Task 3 perfectly , however , might still require significantly more overall concepts and higher ΣφMax values than Task 2 , since the perfect solution requires distinguishing the 4 different block sizes under every initial condition ( see below , Fig . 5A ) . Task 4 ( Fig . 3 , 4th column ) : As expected , Task 4 was the most difficult task in terms of adaptation with an average final fitness of 79 . 5±1 . 4% at generation 59 , 904 . The highest overall fitness reached across all 50 LODs was 97 . 7% ( 125/128 correct trials ) in one LOD . Despite the lower fitness reached , the average number of concepts , ΣφMax , and ΦMax were significantly higher in Task 4 than in Task 1 ( U98 = 813/862/850 , Z = −3 . 034/−2 . 675/−2 . 879 , p = 0 . 002/0 . 007/0 . 004 for #concepts/ΣφMax/ΦMax ) . More evolutionary pressure for sequential memory thus led to causal structures with a higher number of concepts and more integration . This became even more evident when comparing a subset of LODs of Task 4 with equivalent average fitness ( fittest 7 LODs ) to Task 1 ( U55 = 28 . 5/47/53/52/33 , Z = −3 . 604/−3 . 112/−3 . 159/−3 . 185/−3 . 677 , p = 0 . 000/0 . 002/0 . 002/0 . 001/0 . 000 for #concepts/ΣφMax/#MC elements/#MC concepts/ΦMax ) . In this subset , the evolved ΦMax of Task 4 was significantly higher than in any of the other tasks ( U55/55/14 = 33/61/11 , Z = −3 . 677/−2 . 792/−2 . 170 compared to Task 1/2/3 ) . Also most other causal measures were significantly higher than in Task 2 ( U55 = 62 . 5/103/66/74 , Z = −2 . 740/−1 . 751/−2 . 670/−2 . 474 , p = 0 . 006/0 . 080/0 . 008/0 . 013 for #concepts/ΣφMax/#MC elements/#MC concepts ) . Moreover , the number of LODs positively correlated with fitness was highest in Task 4: in 48/50 LODs the number of concepts and ΣφMax correlated significantly with fitness , and the MC measures correlated significantly with fitness in 33/50 LODs . Taken together , comparing the causal measures across different task environments confirmed the predictions of IIT: the number of concepts that evolved during adaptation and their integration was higher in those tasks that required more memory and that could not be solved based on momentary sensor inputs – lowest for Task 1 , intermediate for Task 2/3 , and highest in Task 4 . Given the restrictions imposed on the animats' brains ( binary elements and at most 4 hidden elements ) , evolutionary selection based on task fitness provides a driving force for more concepts and their integration proportional to the amount of memory necessary to solve the tasks . This can be illustrated by considering the evolved network structures with high fitness in Task 1–4 . In Task 1 the maximum fitness reached with just one hidden element was 92 . 2% ( 118/128 correct trials ) . Yet , perfect fitness in Task 1 can be achieved in both a modular and integrated manner , i . e . , with network structures with either ΦMax = 0 or ΦMax>0 ( Fig . 4 ) . Out of the 13 LODs in which animats reached perfect fitness , 7 developed modular networks . An example LOD is shown in red in Fig . 4A . In this example , an initial increase in fitness at generation 9 , 216 was accompanied by an increase in integration . Subsequently , however , the animat's brain turned modular again at generation 13 , 824 ( Φ = 0 ) , which in this case led to a jump in fitness . The evolved network structure is shown in Fig . 4B for generation 59 , 904 . The two hidden elements have memory in the form of self-loops , which however does not count as integration ( Φ = 0 , since single units cannot form a MC because they cannot be partitioned ) . In all of the 7 independent LODs that led to perfect fitness and a modular brain , the final generation of animats had evolved the same functional wiring diagram and similar logic functions with only 2 types of behavior ( low degeneracy ) . In the remaining 6 LODs in which animats achieved perfect fitness , they evolved an integrated main complex with feedback between elements . An example LOD is shown in blue in Fig . 4A . The initial increase in fitness of that LOD to 87 . 5% was achieved without a main complex ( ΦMax = 0 ) and just one concept in the whole animat brain ( generation 8 , 704-51 , 200 ) . The rapid increase to 100% fitness at generation 52 , 224 , however , was preceded by the formation of a main complex ( ΦMax>0 ) and thus integration of concepts at generation 51 , 712 . In Fig . 4C the final evolved wiring diagram at generation 59 , 904 is shown . This network structure is predominant among the evolved animats that reached perfect fitness in an integrated manner ( 5 out of 6 ) . Despite this “anatomical” uniformity , the evolved logic functions , and thus the evolved behavior of the animats in the final generation , differed for all 6 LODs ( high degeneracy ) . Analyzing all animats with perfect fitness across all generations and LODs , the animats with ΦMax>0 showed 341 different TPMs , leading to 332 different behavioral patterns , which were implemented by 15 different wiring diagrams . By contrast , animats with ΦMax = 0 had only 60 different TPMs , leading to 44 different behavioral patterns , which were implemented by 11 different wiring diagrams . Moreover , once a solution ( perfect fitness ) with ΦMax = 0 was encountered , subsequent descendants with ΦMa>0 networks ( and vice versa ) were rather rare and the variability of TPMs within one LOD was lower for modular networks with ΦMax = 0 than for integrated networks ( see Fig . 4A and S3 Fig . ) . This indicates that , while solutions with ΦMax = 0 were encountered with about equal probability to ΦMax>0 solutions across 50 independent LODs , within a LOD neutral mutations without decrease in fitness happen more frequently given integrated networks . Recurrent networks with Φ>0 are thus more flexible , in the sense that there are other solutions close by on the fitness landscape , which can be reached through neutral mutations . Taken together , perfect adaptation to Task 1 seems to require at least 2 hidden elements , but could be achieved in a recurrent/integrated and feed-forward/modular manner with about equal likelihood . However , animats with perfect fitness and ΦMax>0 showed higher degeneracy and variability in structure and behavior ( see also S3 Fig . ) . In Task 2 the maximum fitness reached with just one hidden unit was only 75% ( 96/128 correct trials ) compared to 92 . 2% in Task 1 . The fact that the two categories of blocks in Task 2 have to be distinguished based on memory without the possibility to rely on momentary evidence thus appears to increase the evolutionary pressure to develop more hidden elements . Nevertheless , in Task 2 as well , perfect fitness was achieved with both modular ( Φ = 0 ) and integrated networks ( Φ>0 ) . However , out of the 22 independent LODs with perfect fitness only 6 showed no integration of concepts ( Φ = 0 ) at generation 59 , 504 , with the same wiring diagram as shown in Fig . 4C ( Task 1 ) in 5 out of 6 cases . Of the remaining 16 animats with perfect fitness and integrated MCs , half evolved 2 hidden elements and half 3 , with 9 different types of wiring diagrams and even higher degeneracy in their evolved logic functions and behavior . This corroborates the fact that evolutionary pressure for more concepts and integration is higher in Task 2 than in Task 1 . As in Task 1 , degeneracy and variability in network structure and behavior in Task 2 was higher for animats with integrated brains: taking all animats with perfect fitness across all generations and LODs into account , the animats with ΦMax>0 showed 920 different TPMs , leading to 407 different behavioral patterns , implemented by 34 different wiring diagrams , compared to only 235 different TPMs , with 85 different behavioral patterns , implemented by 30 different wiring diagrams for animats with ΦMax = 0 . Although Task 3 and 4 were more difficult , the maximal fitness that was reached with just one hidden element in these tasks was similar to that of Task 2: 78 . 1% ( 100/128 ) in Task 3 and 77 . 3% ( 99/128 correct trials ) in Task 4 . However , even with 2 hidden elements , the highest overall fitness reached was only 96 . 9% ( 124/128 correct trials ) in Task 3 and 93 . 8% ( 120/128 correct trials ) in Task 4 . While in Task 3 the highest fitness achieved with a modular network without an integrated main complex ( Φ = 0 ) was 96 . 1% , in Task 4 it was only 89 . 8% . The wiring diagrams of the fittest animats of both tasks are displayed in Fig . 5 . In both cases , the animats developed brains with more than two hidden elements and an integrated main complex . Notably , the fittest animat in Task 4 evolved a main complex that was strongly integrated with <ΦMax> = 1 . 13 and had many higher order concepts . Fig . 5C shows the conceptual structure of the fittest animat of Task 4 for one representative state . While the MC concepts are always about the elements in the main complex , some may be interpreted from the extrinsic perspective , such as the concept AC = 11 , which here could mean “keep going right” . Which concepts exist at a given time depends on the state of the system . In this way , evolved concepts can correlate with and indirectly refer to specific states/events of the environment . A detailed interpretation of the extrinsic and intrinsic meaning of the animats' MC concepts is , however , beyond the scope of this study . Although it cannot be excluded that Task 4 is in principle solvable with 4 hidden elements connected in a non-integrated manner ( Φ = 0 ) , these results suggest that evolution strongly prefers integrated brains in Task 4 . In summary , under the constraints of maximally 4 binary , hidden elements , the fittest animats evolved in Task 1 developed modular and integrated wiring diagrams with similar likelihood . With higher memory requirements evolution increasingly selected for integrated networks with ΦMax>0 . In Task 4 , all animats with>90% fitness ( 8 LODs ) developed an integrated main complex . Task difficulty and the amount of sequential memory necessary to solve a task depend not only on the environment , but also on the sensor and motor capacities of the animats themselves . Solving the same task with fewer ( or worse ) sensors and motors requires increased reliance on memory . Consequently , the animats' evolved number of concepts and their integration should increase if the animats' sensor and motor capacities are restricted during adaptation . To test this hypothesis , 50 additional LODs were evolved in the environment of Task 1 with one of the animats' sensors disabled ( set to 0 at each time step and thus rendered useless ) . As explained above , with two functional sensors the two blocks in Task 1 can be categorized based on momentary sensory data alone ( Fig . 2C , D ) . As a result , Task 1 could be solved equally well with a modular and integrated brain network ( Fig . 4 ) . Given only a single sensor , however , the task becomes more complex and requires memory of input sequences for block categorization . Fig . 6 shows the results obtained from the animats with only one sensor compared to Task 1 with two sensors ( in black ) . The average fitness reached with just one sensor was 82 . 8±1 . 4% . Nevertheless , in 4/50 LODs the animats reached 98 . 4% fitness ( 126/128 correct trials ) . As predicted , the animats evolved brains with more concepts , higher ΣφMax , and more integration than those with two sensors at their disposal ( U98 = 510 . 5/514/746 . 5/749 . 5/728 . 5 , Z = −5 . 116/−5 . 074/−3 . 591/−3 . 566/−3 . 716 , p = 0 . 000 , respectively for #concepts/ΣφMax/#MC elements/#MC concepts/ΦMax ) . Also the number of LODs that correlated positively with fitness was higher with only one sensor: number of concepts and ΣφMax correlated significantly in 46/50 LODs and MC measures in 36/50 LODs ( compared to only 34/50 and 12/50 , respectively , with two sensors ) . The increase in concepts and integration due to restricted sensors is even more apparent in the subset of 19 fittest LODs with the same average final fitness as in Task 1 with two sensors ( Fig . 6 , dark orange ) . In terms of network structure , with just one sensor , the maximal fitness achieved with one hidden element was only 67 . 2% ( compared to 92 . 2% with two sensors ) and 95 . 3% with two hidden elements ( 100% with two sensors ) . In three out of the four fittest LODs ( 98 . 4% fitness ) , the animats evolved brains with an integrated main complex ( Φ>0 ) . Overall , the results obtained in Task 1 with one sensor are comparable to those of Task 4 , the task with the largest block sizes , which requires most sequential memory ( Fig . 3 , 4th column ) . As demonstrated above , restricting the sensor capacities of the animats increased brain integration since Task 1 had to be solved based on memory alone instead of momentary sensor states . Restricting the animats' motor capacities still allows using the sensor state S1S2 = 11 to distinguish blocks of size 3 from size 1 . Nevertheless , with just one available motor , reliance on memory should increase , since movements have to be coordinated across several time steps . This , in turn , should lead to more concepts and higher integration . Fig . 7 shows the results of another 50 LODs evolved in Task 1 with one of the animats' motors disabled ( set to 0 at every time step ) . Overall , restricting the animats' motor capacities to one motor led to larger main complexes with more concepts and higher integration ( ΦMax ) ( U98 = 806/824/741 , Z = −3 . 156/−3 . 028/−3 . 618 , p = 0 . 002/0 . 002/0 . 000 for #MC elements/#MC concepts/ΦMax ) . With one motor only , the maximal fitness achieved was 87 . 5% ( 112/118 correct trials ) in one LOD; average final fitness was 78 . 8±0 . 7% . Task 1 with one motor could thus not be compared at the same level of fitness as Task 1 with two motors . Instead , a subset of the 10 fittest animats is plotted in dark green in Fig . 7 , in addition to the average across all 50 LODs ( light green ) . In this subset , also the number of modular concepts was significantly increased compared to the standard Task 1 ( U58 = 107 . 5 , Z = −2 . 857 , p = 0 . 004 ) . The maximal fitness reached with one motor and one hidden element was 71 . 8% . 24/50 animats evolved the same wiring diagram as shown in Fig . 4B , but with only one motor element . The fittest animat ( 112/128 correct trials ) evolved an integrated main complex with at most 3 elements and <ΦMax> = 0 . 38 . Positive correlation with fitness was also higher given just one motor: the number of concepts and ΣφMax correlated significantly in 40/50 LODs and MC measures in 34/50 LODs . Finally , evolutionary pressure for more memory should also arise with sensory data that are less reliable . Consequently , more concepts and higher integration are expected to evolve in an environment where sensor inputs are noisy , if compensating mechanisms are developed . To test this prediction , we simulated 50 additional LODs of Task 1 with 1% sensor noise for each of the two sensors ( Fig . 8 ) , meaning that the state of each sensor had a probability of 1% to be flipped . During evolution with noise , each trial was repeated 20 times and the next generation of animats was selected based on the average fitness across repetitions . On average ( Fig . 8 , pink ) , animats evolved in the noisy environment developed brains with similar number of concepts and integration as those evolved in the noise-free environment ( black ) . Presented with the noise-free Task 1 , their average final fitness was lower than for those animats that had adapted to the noise-free environment ( 88 . 1±1 . 0% compared to 94 . 2±0 . 7% ) . Given the limited size of the animats' brains , it is possible that during 60 , 000 generations no compensatory mechanisms could be developed and the sensor noise only reduced the animats' performance without adaptive influence on their network structures . However , when fitness is evaluated in the environment with 1% sensor noise , the animats that had adapted to the noisy environment reached 79 . 0±0 . 8% fitness at generation 59 , 904 , while the animats that had evolved without sensor noise only reached 76 . 3±0 . 7% fitness . This indicates that in a subset of the 50 evolutionary runs , the animats adapted to compensate for the sensor noise , at least in part . We thus evaluated the subset of 20 LODs evolved under noise with highest fitness in the noisy environment , shown in purple in Fig . 8 . In line with the above predictions , this subset of LODs indeed showed more concepts and a trend for higher ΣφMax , and larger main complexes with more MC concepts than the animats that evolved without sensor noise ( U68 = 299 . 0/368 . 0/380 . 0/382 . 0 , Z = −2 . 638/−1 . 716/−1 . 658/−1 . 630 , p = 0 . 008/0 . 086/0 . 097/0 . 103 , respectively for #concepts/ΣφMax/#MC elements/#MC concepts ) , although their fitness in the noise-free Task 1 was very similar ( first panel , Fig . 8 ) . Note that , due to the data processing theorem [31] , introducing sensor noise would generally decrease standard ( Shannon ) measures of information processing across the communication channel between the environment and the animat , regardless of compensatory mechanisms in the system . By contrast , measures of information integration may actually increase , since they take into account the noise compensation mechanisms implemented by the intrinsic causal structure of the animat . Taken together , the results presented in this section show that the number of concepts and their integration not only increase with the complexity of the environment , but also with the complexity of the environment relative to the sensor and motor capacities of the organism . This confirms the hypothesis that , if more reliance on memory is required to reach high levels of fitness and the number of elements is restricted , evolutionary pressure favors more integrated network structures .
The notions of information and complexity play an important role in recent attempts to understand evolutionary success [2]–[4] , [6] , [7] , [13] , [20] , [21] , [32] . For example , Marstaller et al . [13] presented a measure of “representation” , defined in information-theoretic terms as the mutual information between ( coarse-grained ) states of the environment and internal “brain” states , given the states of the sensors . Applied to animats adapting to a block categorization task similar to Task 1 , representation of a set of salient environmental variables was shown to increase during adaptation [13] . Another recent study examined how sensory-motor mutual information ( ISMMI ) [20] , predictive information ( IPred ) [21] , and integrated information as defined in [6] , change over the course of adaptation to a single environment with fixed statistical properties ( traversing random mazes ) [6] , [7] . The mutual information between sensors and motors quantifies the degree of differentiation of the observed input-output behavior [20] , [32] . Thus , ISMMI reflects the richness of a system's behavioral repertoire ( behavioral complexity ) , which should be advantageous in a complex environment . Predictive information [21]—the mutual information between a system's past and future states—measures the differentiation of the observed internal states of a system . Thus , IPred reflects the richness of a system's dynamical repertoire ( dynamical complexity ) , which is also expected to promote adaptation to complex environments . ISMMI , IPred , and integrated information as defined in [6] all increased during evolutionary adaptation to the maze environment [6] , [7] . Moreover , these indices showed a positive correlation with fitness and positive lower bounds pointing to a minimal , necessary amount of complexity for a given fitness [7] . In the present simulations , IPred always increased during evolution and was highest for Task 4 ( see S4–S6 Figs . ) . However , changes in ISMMI with adaptation as measured in [6] , [7] , [13] varied with the task . Specifically , in Task 1 and 2 , after an initial maximum ISMMI actually decreased with increasing memory capacity , as also observed in [13] . The present approach extends previous investigations in several ways . In addition to aggregate measures of information applied to the animat's brain as a whole , we evaluated all the individual concepts specified by the elements of each animat , taken alone or in various combinations ( as specified in IIT 3 . 0 [15] ) . In essence , concepts characterize the irreducible input-output functions performed by a mechanism in a state [15] . Assessing concepts requires a perturbational approach that reveals a mechanism's causal properties within a system under all possible initial states [14] , [15] . Thus , a concept expresses the entire set of causal dispositions or “powers” conferred by a mechanism in a given state to the system to which it belongs . This analysis thus picks up causes and effects , not just correlations , and does so for the entire set of possible circumstances to which an animat may be exposed , not just for those that happen to be observed in a given setting . Importantly , the causal analysis performed here also shows that combinations of elementary mechanisms ( higher-order mechanisms ) may specify additional concepts , thus greatly enriching the causal powers of an animat for a given number of elements . Crucially , higher-order concepts only count if they are integrated ( φ>0 ) , indicating that their causal power cannot be reduced to the causal power of their parts . For each animat in the present study the IIT 3 . 0 measures were evaluated for every brain state with p>0 and averaged , weighted by each state's probability of occurrence while the animat is performing the task . The finding that successful adaptation to more complex environments leads to the development of an increasing number of concepts fits well with the notion that , everything else being equal , different concepts provide different causal powers , thereby increasing the substrate available to selective processes . The present results also show that complex environments lead not only to an increasing number of concepts available to an animat , but also to the formation of integrated conceptual structures within the animats' brains . If a conceptual structure specified by a set of elements is maximally irreducible to the conceptual structures specified by subsets of elements ( ΦMax ) , the set of elements constitutes a main complex ( MC ) [15] . The conceptual structure specified by the main complex of an animat thus corresponds to a local maximum of causal power . In this way , the main complex forms a self-defined causal entity , whose borders are determined based on the causal powers of its own mechanisms . Importantly , while the concepts within a main complex are specified over hidden elements ( the cause-effect repertoires are all within the MC ) , they do reflect previous input from the sensors and they can , of course , influence the motors . In this way , an integrated conceptual structure can combine current inputs and outputs with past ones and with the state of internal elements that may reflect past memories as well as future goals . All the concepts specified by the main complex over itself thus reflect a system's intrinsic complexity . Complexity and fitness are often associated , though not invariably [6] , [7] , [10] , [33] , [34] . In particular environmental niches , simple systems can be very successful , while complex systems may be selected against if , for example , increased energy requirements trump higher behavioral flexibility ( e . g . , [35]–[38] ) . For the evolution of intrinsic complexity investigated in this article , it is thus important to understand under which environmental conditions integrated conceptual structures become advantageous . Overall , the results of the present simulations indicate that , given constraints on the number of elements and connections , integrated systems can have a selective advantage if the causal structure of the environment is complex . This was shown , first , by the finding that the highest fitness in the more complex tasks ( 2 , 3 and especially 4 ) was achieved by animats with ( highly ) integrated conceptual structures . By contrast , in a simpler task ( Task 1 ) , high fitness was achieved by both integrated and modular systems . Accordingly , correlations between measures of integration and fitness were low in Task 1 , but increased progressively over Tasks 2–4 ( Table 1 , S1 Fig ) . The relative simplicity of Task 1 is illustrated by the rapid achievement of close to maximum fitness in most evolutionary histories and by the minimal requirement for sequential memory ( in Tasks 2–4 , a longer sequence of sensor inputs needs to be stored inside the animat's brain to perform adequately ) . Second , when Task 1 was made more difficult without changing the environment , by reducing the number of sensors and motors , animats had to rely more on sequential memory to achieve high fitness . In this case , animats that evolved highly integrated conceptual structures had once again a selective advantage . Why is this so ? Given limitations on the number of hidden elements , integrated brains can implement more functions ( concepts ) for the same number of elements , because they can make use of higher-order concepts , those specified by irreducible combinations of elements ( see also [26] ) . Moreover , integrated brains with functions specified by hidden elements over hidden elements , or combinations of input , hidden , and output elements , are able to rely more on memory . Note that given an upper limit , or cost on the number of sensors , motors , and hidden elements ( and the speed of interaction between them ) , an empirical positive lower bound of Φ will exist for higher fitness values in complex task environments , as observed for the informational measures evaluated in [7] ( ISMMI , IPred , and integrated information as defined in [16] ) . Note also , however , that any task could , in principle , be solved by a modular brain with Φ = 0 given an arbitrary number of elements and time-steps ( see in particular Fig . 21 in [15] and [39]–[41] ) . Another potential advantage of integrated brains is related to degeneracy [25] . Degeneracy is the property according to which a given function can be performed by many different structures [25] , [42] , [43] , and it is ubiquitous in biology [44] . Degenerate structures show equivalent behavior in certain contexts , but can perform different functions in different contexts . Degeneracy contrasts with redundancy , where many identical structures perform the same function under every circumstance . Systems that show high degeneracy usually are well-suited to integrating information [14] , [25] . Indeed , our results are in line with higher degeneracy for animats having high Φ , both at the population level and within each individual animat brain . The number of different neural architectures , logic functions , and behaviors developed by animats with integrated brains ( Φ>0 ) that solved Task 1 and 2 was much higher than for animats with modular brains ( Φ = 0 ) . More potential solutions with Φ>0 provide a probabilistic selective advantage for integrated structures and lead to higher variability due to neutral mutations ( S3 Fig . ) and more heterogeneous populations . This suggests that populations having high Φ and high degeneracy should be better at adapting rapidly to unpredictable changes in the environment and more robust to mutations , because some animats are likely to be available that are already predisposed to solve new problems . A similar advantage is provided by degeneracy in the concepts available to each individual animat . In integrated brains , selective pressure may favor the emergence of particular concepts . However , in such brains higher order concepts will also become available at no extra cost in terms of elements or wiring , and they may prove useful to respond to novel events . How the evolution of integrated conceptual structures with high degeneracy is affected by changing environments , or by environments with multiple connected niches and coevolution of different species [45] will be the subject of future work . To conclude , rich environments that put a premium on context-sensitivity and memory , such as competitive social situations , should favor the evolution of organisms controlled by brains containing complexes of high Φ . This is because the integrated conceptual structures specified by complexes of high Φ can accommodate a large number of functions in a way that is more economical and flexible than what can be achieved with modular or nearly-modular architectures . Moreover , since according to IIT integrated conceptual structures underlie consciousness [14] , [15] , [18] , [23] , the finding that such structures offer a selective advantage in complex environments could provide a rationale as to why and how consciousness evolved .
Animat brains consist of 8 binary elements: 2 sensors , 4 hidden elements , and 2 motors ( left , right ) that can loosely be referred to as neurons . The sensors are directed upwards with a space of one unit between them and activated ( set to 1 ) if a falling block is located directly above a sensor ( Fig . 1 ) . Otherwise the sensor element is set to 0 . All elements are updated from time step t to t+1 according to a transition probability matrix ( TPM ) . In general , the TPM could be probabilistic with transition probabilities between 0 and 1 . In the present work , however , the animats' TPMs are purely deterministic , i . e . , transition probabilities are either 0 or 1 . The brain elements can thus be considered as binary Markov variables , whose value is specified by deterministic logic gates ( just as the Markov brains in [13] ) . Note that the elements are not limited to classic logic gates , such as ANDs , ORs , or XORs , but can potentially specify any deterministic logic function over their inputs . If only one of the motors is updated to state 1 , in the next time step the animat will move one unit to the right ( motor state 01 ) or left ( motor state 10 ) , respectively . Since no other movement was required of the animat , motor state 11 ( both motors on ) was chosen to be redundant with motor state 00 , for which the animat will not move . To evaluate the number of different TPMs and connectivity matrices for animats with perfect fitness in Task 1 and 2 , the TPMs and connectivity matrices were compared in “normal form” , i . e . , independent of the labels of their elements and only potentially causal connections were included in the analysis ( meaning , hidden elements with only inputs or outputs to the rest of the system were excluded ) . To that end , for a given matrix all elements were permuted and the resulting permuted matrices were ordered lexicographically . The first permuted matrix was then chosen as the “normal form” . All animat brains are initialized without connections between their elements . Connectivity evolves indirectly during adaption to the environment as outlined below , following a genetic algorithm that selects , mutates , and updates the animat's genome at each new generation . The animats' genes encode hidden Markov gates ( HMGs ) , which in turn determine the connectivity and transition table of each brain element: each HMG has input elements , output elements , and a logic table that specifies the elements' transition table ( see [6] , [13] for details ) . In this study , the ancestral genome ( generation 0 ) of all animats does not encode any HGM . Different from previous publications [6] , [7] , [13] , evolution is thus not “jump-started” , which avoids random causal connections in the animats' brains , but requires more generations to reach high levels of fitness . The animats' genomes consist of at least 1 , 000 and at most 20 , 000 loci , where each locus in the genome is an integer value ∈ [0 , 255] . The beginning of a gene is marked by a start codon ( the consecutive loci 42 and 213 ) , followed by two loci that respectively encode the number of inputs and outputs of one HMG . The next eight loci are used to determine where the inputs come from and the outputs go to . Because gates are allowed to have at most 4 in- and at most 4 outgoing connections , 8 loci are reserved , and used according to the 2 preceding loci . The subsequent loci encode the transition table of the HMG , determining the input and output elements and their logical relations . This encoding is robust in the sense that mutations that change the input-output structure of an HMG only add or remove the respective parts of the HMG's logic table , while the rest of the table is left intact . Encoding the connectivity and logic functions of the animats' brain elements with HMGs allows for recurrent connections between hidden elements and also self-connections . Feedback from the hidden elements to the sensors , and also from the motors to the hidden units is however prohibited by zeroing out the sensors and motors at each time-step respectively before the new sensor input arrives and after the movement was performed . The animat is located at the bottom row of a 16×36 unit world with periodic boundary conditions ( Fig . 2B ) . We chose the height of 36 units to allow the animats enough time to assess the direction and size of the falling blocks from each initial condition . Each animat is tested in 128 trials: all 16 initial block positions , with blocks moving to the right and left , and four potentially different block sizes . Note that in Task 1 ( “catch size 1 , avoid size 3” ) and Task 2 ( “catch size 1 , avoid size 2” ) the two different block sizes are thus shown 2×32 = 64 times , while in Task 3 ( “catch size 1+4 , avoid size 2+3” ) and Task 4 ( “catch size 3+6 , avoid size 4+5” ) each block size is shown 32 times . In each trial a block of a certain size falls from top to bottom in 36 time steps , moving 1 unit downwards and sideways always in the same direction ( left or right ) . If at time-step 36 at least one of the animat's units overlaps with the block , it is counted as “caught” , otherwise as “avoided” . In Task 1 , sensor state S1S2 = 11 unambiguously distinguishes size 3 blocks from size 1 blocks . In all other cases , whether a block should be caught or avoided cannot be decided based on a momentary sensor input state . An animat's fitness F at each generation is simply calculated as the percentage of successfully caught and avoided blocks out of all possible 128 test trials . Starting from a set of 100 ancestral animats without HMGs and thus without connections between elements , the animats adapt according to a genetic algorithm across 60 , 000 generations . At each generation , fitness is assessed for all animats in a population of 100 candidates . The most successful candidates are selected probabilistically for differential replication according to an exponential fitness measure S = 1 . 02F*128 . For every successfully caught or avoided block the score is thus multiplied by 1 . 02 . The 100 candidate animats are ranked according to S and selected into the next generation with a probability proportional to S and thus to their fitness ( roulette wheel selection without elite ) . After this replication step , the new candidate pool is mutated in three different ways: a ) by point mutations , which occur with a probability of p = 0 . 5% per locus , causing the value to be replaced by a random integer drawn uniformly from [0 , … , 255]; b ) by deletion: with 2% probability , a sequence between 16 and 512 adjacent loci is deleted; c ) by duplication: with 5% probability a sequence between 16 and 512 adjacent loci is duplicated and inserted at a random location within the animat's genome , where the size of the sequence to be deleted or duplicated is uniformly distributed in the range given . Since insertions are more likely than deletions , genomes tend to grow in size during evolution . Deletions and duplications are , however , constrained so that the genome remains between 1 , 000 and 20 , 000 loci . All genes are expressed . Some of the genes may give rise to redundant HMGs , which , however , will not be robust to mutation . Under fitness selection , the number of genes thus tends to converge to a balanced level ( roughly the number of possible elements ) . Under random selection , only very few rapidly changing random connections between elements appear , and existing network structures decompose within less than 1 , 000 generations [7] . For each task , 50 evolutionary runs of 60 , 000 generations are performed . At the end of each evolutionary run , the line of descent ( LOD ) [19] of a randomly chosen animat from the final generation is traced back to its initial ancestor at generation 0 . For each evolutionary run one LOD is obtained , which captures the run's particular evolutionary history . Since reproduction is asexual , without crossover , a unique LOD can be identified for an animat from the final generation . Because , moreover , all animats are part of the same niche , it makes almost no difference which animat is chosen in the final generation , since going backwards across generations their different LODs quickly coalesce to a single line [6] . We performed the full IIT analysis across each line of descent every 512 generations starting from 0 . The most recent mathematical formulation of the integrated information theory ( “IIT 3 . 0” ) is presented in detail in [15] . In the following we will summarize the main principles and measures relevant to this study , illustrated in simple examples of neuron-like logic gates mechanisms ( Fig . 9 ) . Table 1 shows the average ( nonparametric ) Spearman rank correlation coefficients across all 50 LODs for all evaluated IIT measures in Task 1-4 . In S1 Fig . complementary histograms are shown of the correlation coefficients of all individual LODs . Correlation coefficients were calculated based on ranked variables ( i . e . , using Spearman's instead of Pearson's correlation coefficients ) , since the amount by which fitness increases is not expected to depend linearly on any of the causal measures . Initial increases in fitness can be large , simply because initially there is more room for large improvements than at later generations where the animat already has a high percentage of fitness . Error margins throughout this article denote SEM . Since none of the measured variables was found to be normally distributed for all task conditions ( Kolmogorov-Smirnoff test for normality ) and variances between tasks differed for some of the measures , statistical differences were evaluated using a Kruskal-Wallis test , the non-parametric equivalent of a one-way ANOVA . For all statistical tests across task conditions after adaptation , measures were averaged over the last 3 , 000 generations ( 6 data points ) . Task 1–4 were compared ( see Fig . 3 ) , first , taking all 50 independent LODs of each task into account , despite the lower average fitness reached in Task 3 and 4 . In this set , statistical differences were found for the number of concepts , ΣφMax , and ΦMax ( p = 0 . 001/0 . 002/0 . 016 ) , but not for the number of MC concepts and MC elements . Second , Task 1–4 were compared at the same level of fitness , taking only a subset of LODs with high final fitness into account in Task 3 and 4 ( 9 and 7 fittest LODs , respectively ) . The respective subsets of LODs were selected as the set of fittest LODs in Task 3 and 4 , whose average fitness across the last 5 , 000 generations was closest to that achieved on average in Task 1 . Compared at the same level of fitness , all IIT measures showed statistical differences ( p = 0 . 000/0 . 000/0 . 003/0 . 003/0 . 000 for #concepts/ΣφMax/#MC elements/#MC concepts/ΦMax ) . Moreover , the standard Task 1 was compared to Task 1 with one sensor only , one motor only , and 1% sensor noise ( Fig . 6–8 ) . All measures showed significant difference ( p = 0 . 000 ) when all 50 LODs of each condition were taken into account and also when a subset of LODs with high fitness was compared ( again , p = 0 . 000 for all measures ) . Differences between pairs of task conditions reported in the results section were assessed by post-hoc Mann-Whitney U tests . Custom-made MATLAB software was used for all calculations . The program to calculate the complex of a small system of logic gates and its constellation of concepts is available under [51] . EMD calculations within the IIT program were performed using the open source fast MATLAB code of Pele and Werman [49] . The IBM SPSS software package was used for statistical analysis . | The capacity to integrate information is a prominent feature of biological brains and has been related to cognitive flexibility as well as consciousness . To investigate how environment complexity affects the capacity for information integration , we simulated the evolution of artificial organisms ( “animats” ) controlled by small , adaptive neuron-like networks ( “brains” ) . Task environments varied in difficulty due primarily to the requirements for internal memory . By applying measures of information integration , we show that , under constraints on the number of available internal elements , the animats evolved brains that were the more integrated the more internal memory was required to solve a given task . Thus , in complex environments with a premium on context-sensitivity and memory , integrated brain architectures have an evolutionary advantage over modular ones . | [
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] | 2014 | Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity |
Burkina Faso belongs to a group of countries in which human African trypanosomiasis ( HAT ) , caused by Trypanosoma brucei gambiense , is no longer considered to be a public health problem . Although no native cases have been detected since 1993 , there is still the risk of HAT re-emergence due to significant population movements between Burkina Faso and active HAT foci in Côte d’Ivoire . Since 2014 , Burkina Faso receives support from the WHO to implement a passive surveillance program . This resulted in the detection in 2015 of the first putative native HAT case since two decades . However , epidemiological entomological and molecular biology investigations have not been able to identify with certainty the origin of this infection or to confirm that it was due to T . b . gambiense . This case emphasises the need to strengthen passive surveillance of the disease for sustained elimination of HAT as a public health problem in Burkina Faso .
Human African trypanosomiasis ( HAT ) , or sleeping sickness , is a neglected tropical disease caused by the protozoan parasites Trypanosoma brucei ( T . b . ) gambiense and T . b . rhodesiense , which are transmitted through the bites of infected tsetse flies ( Glossina spp . ) . Control of T . b . gambiense HAT , assumed to be primarily a chronic anthroponosis in West and Central Africa , relies on the detection and treatment of infected cases and on vector control . As a result of intensive control campaigns and changes in land use and climate that have reduced the human reservoir of trypanosomes and tsetse populations , the prevalence of HAT has been drastically reduced in recent decades . In 2016 , 2 , 184 HAT cases were reported to the World Health Organization ( WHO ) , of which more than 97% were due to T . b . gambiense [1] . Currently in West Africa , the endemic HAT foci are localised in the coastal mangrove area of Guinea and the forest area of Côte d’Ivoire [2] . Although the savannah area of Burkina Faso was particularly affected between 1930 and 1980 with tens of thousands of cases [3] , the last native case was reported in 1993 in the Bobo-Dioulasso area [4] . No cases have been reported in at-risk areas since 2005 , when active mass screening was initiated [5 , 6] . However , a few cases imported from Côte d’Ivoire are detected every year in Burkina Faso [7] . This situation is due to the significant migratory movements of populations between these two bordering countries and their important historical , social and economic connections [8] . Thus , there is still a risk of HAT re-emergence in areas where the vector persists in Burkina Faso , mainly in the southwestern part of the country [5] . In order to eliminate HAT as a public health problem by 2020 as targeted by the WHO [9] , a passive surveillance system based on 6 sentinel sites was established in April 2015 in the main health referral structures of this area , which is comprised of three administrative regions ( Fig 1 ) . Two sites were selected in each of the three regions: a hospital and a peripheral health structure in Bobo-Dioulasso ( Hauts-Bassin region ) ; in Banfora ( Cascades region ) ; the hospital in Gaoua and a peripheral health structure in Diebougou ( Sud-Ouest region ) . Health staff located at these six sentinel sites received training on the clinical suspicion of the disease as well as serological diagnosis using a Rapid Diagnostic Test ( RDT ) . In the event of an RDT-positive subject , the blood is then sampled and spotted on filter paper ( Whatman n°4 ) and sent to the Centre International de Recherche-Développement sur l’Elevage en zone Subhumide ( CIRDES; Bobo-Dioulasso , Burkina Faso ) for subsequent immune trypanolysis ( TL ) testing [10] . If the TL test is positive , classical parasitological assays are performed with the support of the central level and the CIRDES staff . In August 2015 , one HAT case was detected at the Banfora hospital sentinel site . Here , we describe this first probably native HAT case to be detected in Burkina Faso since 1993 , as well as the investigations that were conducted to identify the contamination source and to anticipate the risk of re-emergence .
On August 10 , 2015 a 14-year-old boy was admitted to the psychiatric department of the Regional Hospital of Banfora for psychiatric disorders primarily characterised by logorrhea , hypersomnolence and a persistent fever . For at least five months before admission , the patient visited several peripheral health care facilities close to his village with the same symptoms . However , no health professionals considered the possibility of HAT since the disease is no longer regarded to be a threat in this area . The symptoms then progressively became aggravated and the parents said they believed that their child was “possessed by spirits” . They visited some traditional healers but his health deteriorated further , and the parents were not sure how to save their child . Fortunately , the patient’s uncle , a teacher , convinced the parents to take him to the Regional Hospital of Banfora , a preeminent health care centre in the region . Based on the above described signs and symptoms , and thanks to the fact that a doctor had recently been trained for HAT clinical suspicion , a HAT RDT ( SD Bioline HAT ) was performed on August 11 , 2015 and the patient turned out to be positive . The serological suspicion was subsequently reinforced by a positive TL test ( on August 17 ) using the LiTat 1 . 3 variant antigenic type ( VAT ) performed on blood that had been dried on filter paper and by a positive Card Agglutination Test for Trypanosomiasis ( CATT; on August 19 ) preformed on whole blood and an end titer of 1/32 in CATT performed with twofold plasma dilutions ( CATT pl ) . Parasitological investigations conducted on August 19 revealed the presence of trypanosomes in the blood with the mini Anion Exchange Centrifugation Technique performed on 350 μl of buffy coat [11] ( 20 trypanosomes ) and in the cerebrospinal fluid ( CSF ) using the Modified Simple Centrifugation ( MSC ) performed with 3 . 5 ml of CSF [12] ( 5 trypanosomes ) . For CSF white blood cell count , a Uriglass counting chamber was used , revealing 174 cells/mm3 . On the basis of these results , the patient was classified in stage 2 of the disease and treatment with eflornithine ( DFMO ) , according to the national procedure , was started on August 25 . The patient stayed for 2 weeks in the Regional Hospital of Banfora . His 6-month post-therapeutic follow-up confirmed that treatment was successful , as no trypanosomes were detected in the blood or CSF , fewer than 5 cells/mm3 were found in the CSF , and his general clinical condition was normal . On August 19 , 2015 whole blood , buffy coat ( BC ) , plasma and CSF were collected and frozen at -20°C in the field ( car freezer ) and at -80°C in the lab until subsequent molecular analysis performed at CIRDES . The plasma tested positive with the immune TL test-cloned populations of T . b . gambiense VAT LiTat 1 . 3 , LiTat 1 . 5 and LiTat 1 . 6 , as previously described [10 , 13] . Briefly , 25 μl of plasma was mixed with an equal volume of guinea pig serum , to which 50 μl of a 107 trypanosomes/ml suspension prepared from infected mouse blood was added . After 90 min of incubation at room temperature , the suspension was examined by microscopy ( ×400 ) . The TL test was considered positive when more than 50% of the trypanosomes were lysed . TL is considered to be 100% specific for gambiense-HAT sero-diagnosis in humans [10] . DNA extractions from the blood , BC and CSF were performed using the QIAamp DNA Blood Mini Kit ( QIAGEN ) . The three DNA samples tested positive with the Trypanozoon-specific TBR1-2 primers [14] but were negative with the T . b . gambiense-specific primers that target the TgsGP gene [15] . We unsuccessfully tried to characterise the DNA samples using four microsatellite markers ( M6C8 [16] , Misatg4 , Misatg9 and Micbg6 [17] ) , probably because the method was not sensitive enough to detect and amplify small quantities of DNA . Unfortunately , the trypanosome strain could not be isolated despite inoculation of blood and CSF in six BALB/c mice that were immunosuppressed with cyclophosphamide ( 300 mg/kg of Endoxan®; administered before and then every 5 days after infection ) . The reported case came from the village of Gouèra , located in the Niangoloko commune in the Cascades region ( Fig 1B ) near the Banfora-Niangoloko road . It is close to the source of the Tanion River , which is a tributary of the Comoe River that has its source in Burkina Faso and continues its course in Côte d’Ivoire . Due to the presence of a consistent hydrological network , many transhumant cattle pass through this area on their way from Burkina Faso and Mali to the north of Côte d’Ivoire during the dry season . Epidemiological investigations were conducted to identify the possible sources of infection . First , vertical transmission was excluded since the mother was negative for both CATT and TL . In addition , the patient never received a transfusion , thus excluding accidental infection . Family history information was then gathered , especially regarding their link with Côte d’Ivoire . From 1984 to 1994 , the patient’s father , his two wives and their children ( all Burkinabe people ) lived in the Bonon area in Côte d’Ivoire , where they worked on coffee-cocoa plantations . Bonon is currently considered to be the most active HAT focus in the country [18] . However , the family returned to Burkina Faso in 1994 and settled in Gouera . The patient was born in this village seven years later in 2001 and never left the area since his birth , except for a 10-day stay with a traditional healer in the Ivorian village of Kawara in July 2015 . Kawara is located in northern Côte d’Ivoire ( near the border with Burkina Faso ) , far from any currently active foci . Importantly , no HAT cases have been reported in more than 20 years in this area [19] . The other members of the immediate family have not returned to Côte d’Ivoire since 1994 , except for one brother who still maintains a coffee-cocoa plantation in the Man area ( near the border with Guinea ) . No imported cases of HAT have been diagnosed in Gouera area in more than 10 years . As with most families living in Gouera , the primary activity of the case family involves seasonal agriculture based on growing maize , millet , cotton , sesame , rice and peanut , in close proximity to the Tanion River and its tributaries . The family’s secondary activity is cattle and sheep breeding , and the patient , who does not attend school , primarily works as a herder . Although the family principally obtains water year-round from pumps and wells , the patient as well as other village herdsman ( mainly young boys ) often bring their animals to the rivers to graze and drink . Some people in Gouèra are also involved in agricultural activities in the coffee-cocoa plantations of the forest area of Côte d’Ivoire , mainly in the old HAT focus of Aboisso , in the southeastern part of the country . A focus group discussion with the village authorities , elder and community-based health workers was held in Gouera village . This made it possible to observe that the population of Gouera had a limited knowledge of HAT and its transmission , although they did mention the presence of tsetse flies along the rivers near the village . However , one elder man declared himself to be a former HAT patient who received treatment in 1960 . Blood samples from 46 individuals , including all members of the patient’s family and subjects living in the same house , were tested using CATT , and three subjects were found to be positive . The three detected individuals were the first wife of the patient’s father ( not the patient’s biological mother ) ( CATT pl = 1/2 ) , her son ( CATT pl = 1/4 ) , and her grandson ( CATT pl = 1/8 ) . However , all three were negative for the parasitological and TL tests , thus excluding the possibility of contact with T . b . gambiense . In addition , microfilaria were detected in the mAECT-BC of the first wife’s son . The patient was monitored at his daily living spaces during both the dry and rainy seasons ( Fig 1C ) . Specifically , the patient’s residence , the family’s fields , the water supply points , the bathing places , and the pasture points were geo-referenced and characterised . A total of 31 biconical traps were deployed for 48 hours at the most relevant sites favourable to tsetse populations . A total of 15 tsetse flies were collected in three traps , all Glossina tachinoides . The flies were dissected and examined by microscopy for possible trypanosome infection in the midgut , proboscis , and salivary glands . One tsetse fly was determined to be infected by trypanosomes only in the proboscis , suggesting a Trypanosoma vivax infection . In order to identify the possible sources of HAT infection in the patient and to prevent the risk of HAT re-emergence , an exhaustive , reactive medical survey was conducted focussing on the populations of Gouera ( 2 , 781 inhabitants ) and three other villages that share the same spaces ( Koutoura: 2 , 000 inhabitants; Panga: 1 , 392 inhabitants; and Gnamiadougou: 2 , 403 inhabitants ) ( Fig 1B ) . A total of 4 , 214 individuals ( 49 . 13% ) were tested by CATT whole blood . Out of the 27 CATT-positive subjects , 14 had a CATT plasma level ≥ 1/4 but were negative for the mini Anion Exchange Centrifugation Technique performed on buffy coat [11] . Each of the 27 CATT-positive subjects were negative for the TL test . Simultaneously , a veterinary survey was performed and blood was collected from 46 pigs , 7 cattle and 23 sheep in the four villages . All assayed animals were negative by microscopic examination using the buffy coat technique ( BCT ) [20] , in addition to the TL tests using the LiTat 1 . 3 , LiTat 1 . 5 and LiTat 1 . 6 variants .
This case report describes a single HAT case diagnosed in 2015 in the context of a passive surveillance program implemented in the southwestern part of Burkina Faso . The area is considered to be at-risk area regarding the presence of tsetse flies , due to the significant population movements between this area and the endemic foci of Côte d’Ivoire [8] . This HAT infection case from the Banfora area is the first putative native case to be identified in more than 20 years in Burkina Faso . The medical investigations were unable to identify the source of contamination , since no other trypanosomes could be detected in humans or in a sample of domestic animals occupying the same spaces as the HAT case . These results therefore seem to exclude the re-emergence of HAT in the study area , even if we were unable to screen the total human and domestic animal populations of Gouera . However , the presence of tsetse flies was confirmed . Concerning the identification of the trypanosome , some indicators suggest that the infection is due to T . b . gambiense: the clinical status of the patient , the detection of parasites in the CSF , the positive result with the Trypanozoon-specific TBR primers , and the positive TL result with the LiTat 1 . 3 and LiTat 1 . 5 variants . Nevertheless , this could not be confirmed by TgsGP PCR or by microsatellite genotyping . However , it should be noted that the corresponding primers target single copy genes and may not be sensitive enough to exclude the presence of T . b . gambiense in the case of a negative result obtained from biological samples , for which parasitaemia are generally low [21] . Unfortunately , the strain isolation assays failed , making it impossible to apply these primers to purified and more concentrated DNA . Regarding the well-known low virulence of T . b . gambiense and its low success rate of isolation in rodents [22–24] , the isolation failures encountered in this study are an additional argument for characterising this as a T . b . gambiense infection , even if it is still not a definitive proof . To complicate matters , a recent study conducted in trypanosomes circulating in domestic animals in the HAT foci of Bonon and Sinfra in Côte d’Ivoire suggested that it cannot be excluded that T . b . brucei strains are capable of expressing the LiTat 1 . 3 variant , culminating in TL-positive results [25] . To summarise , although we strongly suspect the presence of a T . b . gambiense infection , we cannot exclude the possibility of a T . b . brucei infection associated with possible immunodeficiency . Indeed , the T . b . brucei parasite is normally not infectious to humans since it undergoes immediate lysis through the trypanolytic activity of the human-specific apolipoprotein L-1 ( ApoL1 ) [26] . Nevertheless , a lack of the trypanolytic ApoL1 protein could be responsible for human infection with animal trypanosomes , as already described for one T . evansi infection in India [27] and one transient T . b brucei infection in Ghana [28] . A T . evansi infection is very unlikely in this region . Our investigations suggest that the source of contamination may be a HAT case infected in an Ivorian focus , since part of the local population regularly stays in Côte d’Ivoire to work in the coffee-cocoa plantations , a biotope favourable to human/tsetse fly contact and where HAT still occurs [29] . However , such a case could not be detected during the medical surveys , either because no such infected individuals participated in the active case finding or because they do not live in the area anymore ( e . g . they have returned to Côte d’Ivoire ) . The source of contamination could also be a residual local human reservoir since the area is a previous focus . It was recently observed that HAT is not invariably fatal if untreated , and that some individuals can tolerate T . b . gambiense without obvious symptoms for a prolonged period [30 , 31]; one recent case persisted for 29 years without displaying any symptoms [32] . Finally , it should not be excluded that the source of contamination may be a domestic or wild animal reservoir of T . b . gambiense , since the existence of such a reservoir is still under debate [25 , 33] . No T . b . gambiense were detected in local domestic animals in this study , suggesting that this potential animal reservoir would rather be due to the transhumant cattle [34] that regularly stay in the area during the dry season or to wild animals . The detection of this probable native case confirms the risk of HAT re-emergence in Burkina Faso and highlights the importance of maintaining a passive surveillance program in the areas at risk . More generally , it is crucial in the context of the elimination process to integrate HAT control into the national peripheral health facilities , mainly in areas of low prevalence . This case report also affirms that further studies are required to clarify the roles of population migration , latent human infections , and possible animal reservoirs of T . b . gambiense in the epidemiology of HAT . Studies on the movement of human and animals populations in HAT foci and the examination of animals may become part of the toolbox for post-elimination monitoring , in order to ensure sustained zero-transmission in controlled HAT foci . Finally , there is also the possibility of underestimating atypical human infections caused by trypanosomes that normally infect animals [35] , and thus the ability to differentiate a T . b . gambiense infection from these atypical infections is also an important challenge . This illustrates the importance of developing sensitive , T . b . gambiense-specific tools [1] . | In 2012 , the roadmap for the Control of Neglected Tropical Diseases ( NTD ) of the World Health Organization ( WHO ) included human African trypanosomiasis ( HAT ) to be eliminated as a public health problem by 2020 . To reach this ambitious objective in Burkina Faso , where the vector ( and consequently a risk of HAT re-emergence ) is still present , a passive surveillance system based on sentinel sites was established in the southwestern part of the country , considered to be the most at-risk area . The implementation of this system recently resulted in the diagnosis of the first putative native sleeping sickness case since two decades . Although the origin of this infection and how the patient was infected could not be identified , the detection of this native case confirms that HAT re-emergence in Burkina Faso is still a risk . This demonstrates the importance of implementing , maintaining and reinforcing passive surveillance programs in at-risk areas . | [
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] | 2018 | Description of the first sleeping sickness case diagnosed in Burkina Faso since two decades |
Multiple sclerosis ( MS ) is an autoimmune disease with high prevalence among populations of northern European ancestry . Past studies have shown that exposure to ultraviolet radiation could explain the difference in MS prevalence across the globe . In this study , we investigate whether the difference in MS prevalence could be explained by European genetic risk factors . We characterized the ancestry of MS-associated alleles using RFMix , a conditional random field parameterized by random forests , to estimate their local ancestry in the largest assembled admixed population to date , with 3 , 692 African Americans , 4 , 915 Asian Americans , and 3 , 777 Hispanics . The majority of MS-associated human leukocyte antigen ( HLA ) alleles , including the prominent HLA-DRB1*15:01 risk allele , exhibited cosmopolitan ancestry . Ancestry-specific MS-associated HLA alleles were also identified . Analysis of the HLA-DRB1*15:01 risk allele in African Americans revealed that alleles on the European haplotype conferred three times the disease risk compared to those on the African haplotype . Furthermore , we found evidence that the European and African HLA-DRB1*15:01 alleles exhibit single nucleotide polymorphism ( SNP ) differences in regions encoding the HLA-DRB1 antigen-binding heterodimer . Additional evidence for increased risk of MS conferred by the European haplotype were found for HLA-B*07:02 and HLA-A*03:01 in African Americans . Most of the 200 non-HLA MS SNPs previously established in European populations were not significantly associated with MS in admixed populations , nor were they ancestrally more European in cases compared to controls . Lastly , a genome-wide search of association between European ancestry and MS revealed a region of interest close to the ZNF596 gene on chromosome 8 in Hispanics; cases had a significantly higher proportion of European ancestry compared to controls . In conclusion , our study established that the genetic ancestry of MS-associated alleles is complex and implicated that difference in MS prevalence could be explained by the ancestry of MS-associated alleles .
Multiple sclerosis ( MS ) is an autoimmune disease of the central nervous system that results in demyelination and tissue loss . Association studies in White , non-Hispanic populations have discovered human leukocyte antigen ( HLA ) alleles conferring strong risk and protective effects and 200 non-HLA genetic risk variants conferring modest risk of MS[1 , 2] . Evidence that HLA class II alleles interact to confer greater risk of MS have been found[3] . Together , identified MS genetic risk factors are estimated to explain up to 30% of total heritability , of which most is accounted for by HLA alleles[2 , 4] . The prevalence of MS varies across the globe but is highest in White , non-Hispanic populations . There is evidence that African Americans are at higher risk for developing the disease , and along with Hispanics , may have a more severe disease course . Incidentally , countries with majority White , non-Hispanic individuals and experience highest MS prevalence are located at higher latitudes . Past studies have not only established the association between ultraviolet radiation and MS prevalence , but have also found evidence supporting the causal role of low vitamin D on MS risk . In this study , we investigate another hypothesis—that the difference in MS prevalence across the globe can be explained by European ancestry . If European ancestry can explain this difference , then MS-associated alleles in admixed individuals can either be European or confer increased risk on a European haplotype compared to a non-European haplotype . We investigate this by analyzing the genetic ancestry of MS-associated alleles in a large combined cohort totaling 1 , 471 MS cases and 10 , 913 controls including African American , Asian American , and Hispanic individuals . Previous studies have been able to replicate the association of the HLA risk allele HLA-DRB1*15:01 in nearly all populations[5] . Additional HLA alleles have been found to be associated with MS in non-European populations , such as HLA-DRB1*15:03 in African Americans and HLA-DRB1*04:05 in the Japanese population[6] . Limited replication has been achieved for non-HLA genetic risk variants in other populations[7–9] . We found that most MS-associated alleles are cosmopolitan , but there is evidence that European risk alleles may confer more risk than non-European risk alleles , most notably for the major risk allele HLA-DRB1*15:01 . Thus , there is evidence that the difference in MS prevalence could be explained by European ancestry . We also tested for the association of European ancestry with MS across the genome in African Americans , Asian Americans and Hispanics , and found a signal of association on chromosome 8 in Hispanics .
We performed multidimensional scaling ( MDS ) analysis on genotype data from 21 , 647 subjects to generate components used to control for population stratification in later analyses ( Fig 1A , S19 Table ) . This analysis was done separately for African American samples which were genotyped using the Illumina Immunochip ( Fig 1B , S19 Table ) . The first three components were sufficient to differentiate global ancestries and broadly categorize samples as African Americans , Asian Americans , or Hispanics . Component 2 was correlated with African ancestry in African Americans ( R = 1 . 00 , p < 0 . 01 ) , component 1 was correlated with Native American ancestry in Hispanics ( R = -0 . 95 , p < 0 . 01 ) , and component 1 was correlated with East Asian ancestry in Asian Americans ( R = 0 . 99 , p < 0 . 01 ) . We used fastSTRUCTURE to estimate global admixture proportions for individuals from each admixed population . After eliminating White , non-Hispanic individuals and Hispanics with less than 5% Native American ancestry , a total of 3 , 692 African Americans , 4 , 915 Asian Americans , and 3 , 777 Hispanics comprised the final dataset ( Table 1 ) . African Americans were estimated to be 76 . 1% African and 23 . 9% European on average , Asian Americans were estimated to be 92 . 2% East Asian and 7 . 8% European on average , and Hispanics were estimated to be 68 . 4% European , 28 . 8% Native American , and 2 . 8% African on average , in line with published estimates[10] . The average global admixture for MS cases and controls is shown in Fig 2 ( S20 Table ) . We observed significant differences in global admixture proportions between cases and controls across all populations . African American cases had 5 . 0% increased African ancestry compared to controls ( p < 0 . 01 ) ; Hispanic cases had 5 . 4% increased Native American ancestry ( p = 0 . 02 ) and 11 . 3% decreased European ancestry ( p < 0 . 01 ) compared to controls . Asian American cases had 23 . 0% increased European ancestry compared to controls ( p < 0 . 01 ) . In previous studies , up to eleven regions within the major histocompatibility complex ( MHC ) have been identified to exhibit statistically significant independent effects of association with MS in White , non-Hispanic populations: six HLA-DRB1 , one HLA-DPB1 , one HLA-A , two HLA-B alleles , and one signal in a region spanning from MICB to LST1[11] . We tested each of these regions , in addition to regions spanned by DQB1 and HLA-C and the broader regions class I , II , and III , for evidence of increased European ancestry in MS cases compared to controls . Results are summarized in Tables 2–4 and shown in Fig 3 ( S21 Table ) . In African Americans , cases exhibited increased European ancestry at the MHC region compared to controls , after accounting for global admixture proportion differences , with genes in the class I region and the MICB-LST1 region reaching statistical significance ( p < 0 . 05 ) . In Hispanics , the direction of association was the same as in African Americans , but none of the regions reached statistical significance . In Asian Americans , the cases had decreased European ancestry at the MHC region compared to controls , with the regions HLA-DQB1 and HLA-DRB1 demonstrating evidence for statistical significance ( p < 0 . 05 ) . We investigated the ancestry of MS-associated HLA alleles to determine whether ancestry associations observed at the regions within the MHC could be explained . We first identified HLA alleles associated with MS in each admixed group using additive multivariate logistic regression , adjusting for the first three MDS components . We observed 14 alleles in African Americans , 15 alleles in Hispanics , and 4 alleles in Asian Americans that reached nominal significance of association ( p < 0 . 05 ) . HLA-DRB1*15:01 , the strongest genetic association with MS observed in White , non-Hispanic individuals , to date , was a top signal across all three admixed populations , consistent with previous findings[5] . As expected , the African allele HLA-DRB1*15:03 was significantly associated with MS in African Americans[12] . In African Americans , we further replicated the association of HLA risk alleles previously established in the White , non-Hispanic population: HLA-DRB1*03:01 , HLA-A*02:01 , HLA-DRB1*14:01 , and HLA-B*38:01 at nominal level significance ( p < 0 . 05 ) [11] . In both Hispanics and Asian Americans , HLA-DRB1*15:01 is the only established HLA risk alleles in White , non-Hispanics that was replicated . Fig 4 ( S22 Table ) compares the p-values of significant MS-associated HLA alleles across different populations . With our sample sizes , we estimate close to 100% power of detection for African Americans and Hispanics and 80% power for Asian Americans . Assuming the MS HLA alleles found in the European population are also associated with MS in admixed populations , then 6 , 7 , and 4 HLA alleles are expected to be detected in African Americans , Hispanics , and Asian Americans respectively , post quality control . Next , we estimated the admixture proportions of all the nominally-associated alleles using local ancestry estimates from RFMix . Analysis of HLA alleles and corresponding admixture proportions are shown in Tables 5–7 , and Fig 5 ( S23 Table ) . Ancestry estimates for HLA alleles previously established to be ancestry-specific were in strong agreement: 98 . 4% East Asian for the East Asian allele HLA-DRB1*04:05 in Asian Americans ( n = 692 alleles ) , 96 . 2% European for the European allele HLA-DRB1*01:01 in Hispanics ( n = 395 alleles ) , 96 . 4% Native American for Native American allele HLA-DRB1*14:02 in Hispanics ( n = 454 alleles ) , and 99 . 5% African for African allele HLA-DRB1*15:03 in African Americans ( n = 881 alleles ) [13] . Most MS-associated HLA alleles are cosmopolitan across the admixed populations . The MS risk allele HLA-DRB1*15:01 , which is more common in Europeans , was estimated to be 63 . 7% European in African Americans ( n = 512 alleles ) and 96 . 4% European in Hispanics ( n = 534 alleles ) [14] . However , it is striking that HLA-DRB1*15:01 is 92 . 9% East Asian in Asian Americans ( n = 1 , 228 alleles ) . We searched for MS-associated HLA alleles that are potentially ancestry-specific , imposing a 96% ancestry cutoff because we were able to correctly estimate the ancestry of HLA alleles of known ancestry as 96% or greater . Briefly , we considered an MS-associated allele as a candidate ancestry-specific allele if at least 96% of its ancestry comes from a single ancestry across all admixed populations in which it exists , and/or is missing in the rest of admixed populations . An allele could be missing because it does not exist in other ancestries ( e . g . African HLA-DRB1*15:03 ) , or because it did not pass quality control for imputation . Using this approach , we classified HLA-DRB1*14:02 and HLA-DRB1*16:02 as Native American alleles , HLA-DRB1*15:03 as an African risk allele , HLA-DRB1*12:02 as an East Asian allele , and HLA-B*55:01 , HLA-B*27:05 , and HLA-A*01:01 as European alleles . Given that African Americans exhibit two-way admixture and many MS-associated HLA alleles in African Americans are relatively admixed , we studied the differential risk of HLA alleles in African Americans based on ancestry . We first performed a case-control study of the prominent MS risk allele HLA-DRB1*15:01 in African Americans to determine whether there were any differences in risk conferred by HLA-DRB1*15:01 alleles of European and African origin . We removed 12 alleles from the analysis , of which 6 were from cases and 6 were from controls , whose HLA-DRB1*15:01 allele was not inferred to be completely European or African . Table 8 shows the final number of alleles by ancestry and by case status . The risk of MS conferred by the European HLA-DRB1*15:01 allele was determined from logistic regression to be three times higher compared to the African HLA-DRB1*15:01 allele ( OR = 3 . 00 , 95% CI: 1 . 90–4 . 76 , p = 2 . 49 × 10−6 ) , after adjusting for the first 3 MDS components . We restricted the logistic regression to alleles from individuals with one copy of HLA-DRB1*15:01 so that the association was not confounded by number of HLA-DRB1*15:01 alleles . We continued the same analyses for other alleles in Table 5 . Alleles with a sample size less than 50 or with a predominant ancestry of more than 90% are excluded from the analysis . This analysis further revealed that European HLA-B*07:02 ( OR = 1 . 66 , 95% CI: 1 . 12–2 . 47 , p = 1 . 18 × 10−2 ) and HLA-A*03:01 ( OR = 1 . 54 , 95% CI: 1 . 04–2 . 29 , p = 2 . 97 × 10−2 ) conferred a greater risk of MS compared to their African counterparts at p < 0 . 05 . However , for the risk allele HLA-DRB1*03:01 , the European allele is protective ( OR = 0 . 64 , 95% CI: 0 . 43–0 . 96 , p = 3 . 03 × 10−2 ) compared to the African allele . Hence , this provides additional evidence that the European haplotype confers more risk of MS compared to the African haplotype for other HLA alleles , although this is not true for every allele ( S1 Table ) . SNP2HLA imputes SNPs and amino acids ( AA ) for the exons of HLA alleles , with a 1-to-1 mapping between a SNP and AA subsequence ( see Methods ) . Given that European HLA-DRB1*15:01 conferred three times the odds of MS compared to African HLA-DRB1*15:01 , and without evidence that this finding was due to HLA-DQB1*06:02 ( S2 and S3 Tables ) , we compared the most representative SNP and AA subsequences for European and African HLA-DRB1*15:01 alleles to look for differences . A large majority ( 94 . 1% ) of European HLA-DRB1*15:01 alleles shared the same SNP and AA subsequences , whereas African HLA-DRB1*15:01 subsequences were more diverse . Data in S4–S7 Tables summarize the numbers of SNP and AA subsequences and S8 and S9 Tables show the genetic coordinates and AA positions for the imputation of HLA-DRB1 subsequences . Fig 6 shows the comparison of the most frequent ( 94 . 1% ) SNP and AA subsequence for European HLA-DRB1*15:01 alleles against the top two most frequent ( 59 . 4% and 27 . 8% respectively ) subsequences for African HLA-DRB1*15:01 alleles , respectively . All differences between the European subsequence and the most frequent African subsequence were within exon 1 . When compared against the second most frequent African subsequence , differences were found in exons 1 , 3 , and 6 . We evaluated the association of European ancestry with MS for 200 established non-HLA genetic risk loci identified in White , non-Hispanic individuals . Following quality control ( QC ) , 165 MS risk variants were available in African Americans , 167 MS risk variants in Hispanics , and 154 MS risk variants in Asian Americans for analysis . We tested each risk variant for association with MS and tested each genetic locus for association between European ancestry and MS . Data in S10–S12 Tables summarize the results for each admixed population , respectively . Increased East Asian ancestry in MS cases compared to controls for SNPs rs405343 ( p = 5 . 53 × 10−13 ) and rs6670198 ( p = 6 . 13 × 10−8 ) was observed in Asian Americans . No other genetic risk locus showed evidence of increased ancestry in cases compared to controls in any admixed population after adjustment for multiple tests . The risk allele T for SNP rs405343 was significantly associated with MS ( OR = 2 . 55 , 95% CI: 1 . 70–3 . 83 , p = 6 . 87 x 10−6 ) in Asian Americans; however , the risk allele T for SNP rs6670198 showed no evidence for association . A small proportion of MS risk alleles overall demonstrated a nominal level of association at p < 0 . 05: 13 SNPs in African Americans , 21 SNPs in Hispanics , and 28 SNPs in Asian Americans . With our sample sizes , the powers of detection for African Americans , Hispanics , and Asians are estimated to be 21 . 5% , 26 . 5% , and 11 . 7% , respectively . Assuming the established MS non-HLA alleles are also associated with MS in admixed populations , then 35 , 44 , and 18 non-HLA alleles are expected to be detected in African Americans , Hispanics , and Asian Americans respectively , post quality control . We determined whether European ancestry , both globally and locally at the non-HLA genetic risk loci , was correlated with a cumulative genetic risk score in African American , Asian American , and Hispanic MS cases . S1 Fig ( S25 Table ) shows results for each admixed population . Globally , no evidence for significant correlation was observed in African Americans ( R = 0 . 04 , p = 0 . 47 ) , Hispanics ( R = 0 . 06 , p = 0 . 30 ) , or Asian Americans ( R = 0 . 25 , p = 0 . 05 ) ; similar results were observed for local ancestry in all populations . Admixture estimates showed that the majority of the non-HLA variants investigated here were cosmopolitan; local admixture was reflective of global admixture patterns ( Fig 7 , S24 Table ) . We searched across the genome in African Americans , Asian Americans , and Hispanics to identify regions where individuals with MS had a higher proportion of European ancestry compared to controls using the test statistic in Eq 1 . The Q-Q plots in S2A and S2B Fig show that the admixture mapping test statistics are approximately normally distributed except at the tails . The test statistics are least normally distributed for Asian Americans , which exhibits the most imbalance between cases and controls . The strongest peak of association observed was identified in a single region at chromosome 8 from 207 , 207–314 , 620 ( GRCh37 ) in Hispanics that corresponds to an increase in European ancestry in cases compared to controls ( S13–S15 Tables and Fig 8 ) . This is the only peak that reached genome-wide significance with a Bonferroni adjusted p-value of 3 . 36 × 10−2 . The closest gene to this region is ZNF596 , a zinc finger protein 9 . 8 kb downstream that is most highly expressed in the brain and cerebellum out of 20 different human tissues whose total RNA was sequenced[14] .
The genetic contribution to MS susceptibility is very complex; most studies have focused on populations of Northern European descent , and to date , the involvement of genes within and outside the MHC region has been established . Admixed individuals are derived from distinct ancestral populations; global and local genetic ancestry estimates can be used to test for association between the genome , a genetic locus or specific allele and a phenotype of interest[12 , 15 , 16] . This is one of the first studies to examine the relationship between genetic ancestry , HLA and non-HLA alleles and MS in three admixed populations: African Americans , Hispanics , and Asian Americans . Within the MHC , we were first able to replicate the association of some previously established HLA risk alleles with MS[11]; HLA-DRB1*15:01 was the most significant finding across all three admixed populations[5] . Here , the odds ratios ( ORs ) for HLA-DRB1*15:01 observed in admixed populations ( 1 . 88–2 . 45 ) were slightly lower than described in previous reports for White , non-Hispanic individuals ( 2 . 92 ) [11] , but the direction of effect is consistent . In African Americans , we further replicated the association and direction of effect of HLA alleles previously established in the White , non-Hispanic population: HLA-DRB1*03:01 , HLA-A*02:01 , HLA-DRB1*14:01 , and HLA-B*38:01 at nominal level significance ( p < 0 . 05 ) [11] . Additionally , we replicated the African HLA risk allele HLA-DRB1*15:03 in African Americans[9] . A similar study by Isobe , et al . also replicated the association of HLA alleles HLA-DRB1*15:01 , HLA-DRB1*03:01 , HLA-DRB1*15:03 , and HLA*02:01 . Although HLA-DRB1*14:01 was not found by Isobe to be significantly associated ( P-value = 0 . 070 ) , its protective effect is consistent with what is observed in this study . In summary , we detected association for 5 of the 6 established HLA MS alleles expected to be replicated under power calculations , and this supports the hypothesis that the MS genetic risk in African Americans partially overlaps with that of Europeans[17] . In both Hispanics and Asian Americans , HLA-DRB1*15:01 is the only established HLA risk allele in White , non-Hispanics that was replicated[11] , which suggests a smaller overlap in MS genetic risk between Hispanics and Asian Americans with that of Europeans . At a nominal level of significance ( p < 0 . 05 ) , analysis of the HLA alleles identified five candidate risk alleles and four candidate protective alleles for African Americans , nine candidate risk alleles and four candidate protective alleles for Hispanics , and two candidate risk alleles and one candidate protective allele for Asian Americans . All directions of effect ( risk or protective ) of candidate MS HLA alleles are the same if found in more than one admixed population . In total , four of the nine protective HLA alleles novel in this study for MS belong to class I genes and five are class II DRB1 alleles . It is plausible that the lower prevalence of MS in some admixed populations could be partially explained by the effects of protective alleles . Of the significantly associated HLA haplotypes and alleles reported by Mack , et al . in Europeans , three were nominally associated with MS in at least one admixed population in this study[18] . In particular , the HLA-DRB1*03:01 and HLA-A*02:01 alleles in African Americans exhibited similar ORs and direction of effect ( Table 5 ) . However , the HLA-C*03:04 allele in Asian Americans conferred risk ( OR = 1 . 69 ) instead of a protective effect ( Table 7 ) . It is plausible that this disagreement is because an overwhelming majority ( 95 . 7% ) of HLA-C*0304 alleles in Asian Americans are of East Asian origin in this study , while the investigation by Mack , et al . was in European Americans ( Fig 5C , S23 Table and Table 7 ) . The exon differences observed between European and African HLA-DRB1*15:01 suggests that future high-resolution HLA analysis could further explain the differences in risk and protective effects that is due to ancestry . The entire MHC region spanning 29 , 570 , 005–33 , 377 , 701 ( GRCh37 ) had a higher proportion of European ancestry in MS cases compared to controls for both African American and Hispanic populations . In Asian Americans , the MHC region had a higher proportion of East Asian ancestry in cases compared to controls . Interestingly , the local MHC ancestry associations observed in the current study for African Americans and Hispanics contrasted with global ancestry—African American and Hispanic cases demonstrated less European ancestry compared to controls when the whole genome was taken into consideration , and Asian American cases demonstrated more European ancestry compared to controls . To investigate these associations further , we characterized the admixture proportions of MS-associated HLA alleles . Fig 5 ( S23 Table ) shows that a majority of HLA alleles , including HLA-DRB1*15:01 , were inferred to exist in multiple ancestries and could thus be considered cosmopolitan . African American cases were not significantly European at the class II region compared to controls likely due to the contribution of the common African allele HLA-DRB1*15:03 . In Asian Americans , HLA-DRB1*15:01 and HLA-C*03:01 conferred risk of MS and accounted for 68 . 6% of HLA alleles associated with MS . Together , these two alleles had an average of 94 . 7% East Asian ancestry which helps explain why cases tended to have a higher proportion of East Asian ancestry compared to controls within the MHC region . We find it noteworthy that the European HLA-DRB1*15:01 allele confers three times the odds of MS compared to the African HLA-DRB1*15:01 allele in the African Americans we studied . A similar effect has been observed for European HLA-B*07:02 and HLA-A*03:01 . Together these findings provide evidence that in some genetic regions , the European haplotype could confer more risk of MS than haplotypes derived from other ancestries . In these cases , it is plausible that disease-causing genetic variants can come from only one ancestral population . However , it must be noted that this has not been found to be true for all admixed MS-associated alleles we examined ( S1 Table ) , and that for alleles such as the African MS risk allele HLA-DRB1*15:03 , the African haplotype confers more risk than the European haplotype . These findings together further highlight the complex genetic ancestry of MS-associated alleles in admixed populations . Given that HLA-DRB1*15:01 is in very strong linkage disequilibrium with HLA-DQB1*06:02 in Europeans , we investigated whether the increased risk of MS in African Americans conferred by European HLA-DRB1*15:01 could possibly be due to HLA-DQB1*06:02 , despite the limitation that HLA-DQB1 did not pass our imputation quality cutoff ( average R2 = 0 . 53 across all DQB1 alleles ) . As expected , 99 . 5% of HLA-DRB1*15:01 haplotypes that include HLA-DQB1*06:02 in African Americans are of European ancestry . Counts of all observed DRB1*15:01-DQB1 haplotypes are shown in S16 and S17 Tables . S1 Table shows that HLA-DQB1*06:02 was not associated with MS in African Americans ( OR = 1 . 14 , 95% CI: 0 . 68–1 . 92 , p = 0 . 72 ) . Further , S3 Table shows that comparison of European HLA-DQB1*06:02 alleles with African HLA-DQB1*06:02 alleles , in the absence of HLA-DRB1*15:01 , did not demonstrate evidence for a significant association ( OR = 0 . 48 , 95% CI: 0 . 23–1 . 00 , p = 0 . 07 ) ; the direction of effect is , in fact , protective . Results from the current study are consistent with a previous report showing the association of MS with the HLA-DRB1*15:01-DQB1*06:02 haplotype is due to the DRB1 locus independent of DQB1*06:02[19] . A comparison of the most commonly imputed SNP and AA subsequences between European and African HLA-DRB1*15:01 alleles revealed mismatches at exons 1 , 3 , and 5 . Each of these exons help encode the DR beta 1 heterodimer , with exon 1 encoding the leader peptide and exon 5 encoding the cytoplasmic tail of the membrane protein . Exon 3 , together with exon 2 , encode the two extracellular domains[20] . Further investigation into whether genetic variation in these exons have functional consequences for peptide presentation in the context of MS is warranted . Our case study of HLA-DRB1*15:01 illustrates how admixture mapping can be broadly applied to better characterize risk alleles in admixed populations . Consistent with previous attempts to replicate the association of non-HLA genetic risk variants , we also failed to replicate association of most non-HLA genetic risk variants across all three admixed populations , except for rs405343 and rs6670198 in Asian Americans , which exhibit the same direction of effect as in whites[8 , 9 , 21] . Without correction for multiple testing with significance established at p < 0 . 05 , we replicated the association of 13 SNPs in African Americans , 21 SNPs in Hispanics , and 28 SNPs in Asian Americans ( S10–S12 Tables ) . For African Americans and Hispanics , we replicated less associations than is expected under power calculations . For Asian Americans , more associations were replicated than is expected . The majority of non-HLA MS risk variants identified so far appears to be cosmopolitan and their observed ancestry proportions are reflective of global admixture proportions ( Fig 7 , S24 Table ) . European global ancestry and European local ancestry at the non-HLA genetic risk loci was not correlated with the unweighted genetic risk score comprised of the non-HLA variants ( S1 Fig , S25 Table ) . Although our investigation showed that the majority of non-HLA MS genetic risk variants reported for the White , non-Hispanic population do not demonstrate strong associations with MS in African Americans , Asian Americans , and Hispanics , our study is under-powered to detect most associations . Besides lacking power due to small sample and effect sizes , there are multiple other explanations for why we may fail to replicate many associations of the non-HLA genetic risk variants with MS[9] . One explanation is that differences in minor allele frequencies reduced the power to detect associations in admixed populations . Another explanation is that the smaller haplotype blocks of African Americans and Hispanics may have caused many non-HLA genetic risk variants to fail tagging the putative causative variant of MS . Lastly , the absence of replication could simply be due to genetic heterogeneity across populations , which further justifies the need for GWAS in non-White populations . A genome-wide search for European ancestry differences between MS cases and controls in all three admixed populations resulted in one region of chromosome 8 from 207 , 207 to 314 , 620 ( GRCh37 ) in Hispanics only . The closest gene to this region is ZNF596 , a zinc finger protein 9 . 8 kb away that is highly expressed in the brain and cerebellum . Lesions in brain tissue as well as brain atrophy are pathological hallmarks of MS[22] , and available data suggest Hispanics may have a more severe disease course than White , non-Hispanic individuals[23]; however , these findings await replication . Further investigation of this region in a larger independent dataset and full interrogation of nearby genes and determining whether ZNF596 could be involved in MS pathogenesis from a functional perspective are warranted . Some important strengths of this study included comprehensive analyses of a large , well-characterized dataset comprised of 12 , 384 admixed MS cases and controls with high quality genetic data , the application of rigorous quality control procedures , genetic imputation methods for both SNP and HLA loci , probabilistic graphical modeling for local admixture estimation across the genome , and non-parametric statistical testing to identify local admixture differences between cases and controls that accounts for global differences . In the current study , the combined analysis of SNP and HLA genotypes in African Americans revealed for the first time , strong evidence that the European HLA-DRB1*15:01 allele confers three times the MS risk compared to the African HLA-DRB1*15:01 allele . This finding indicates increased risk attributed to the European 15:01 allele could be due to functional differences within DRB1 itself , or possibly due to variant ( s ) present on the European HLA-DRB1*15:01 haplotype that are not found on the African haplotype . Some limitations must also be acknowledged . The diagnosis of MS cases in this large dataset occurred over a twenty-five year period and in different clinical settings; both prevalent and incident cases were included . Although all cases fulfilled established diagnostic criteria , is not known whether local genetic ancestral proportions ( of particular importance in the current study ) would be expected to change for cases diagnosed at different time points; larger investigations would be needed . We performed MDS analysis of genotype data to broadly categorize samples as African Americans , Asian Americans , or Hispanics for case-control analysis; careful matching on self-reported race/ethnicity was not possible for all individuals . MDS components were therefore used in each analysis to control for potential confounding; however , it is possible that population stratification could still contribute to some of our findings . The Asian MS case sample utilized in the current study was small compared to the other groups , reflecting the low prevalence of disease in this population , which reduced power to detect to modest effects . In conclusion , results from the current study reveal a complex picture of genetic ancestry for MS-associated alleles in African Americans , Asian Americans , and Hispanics . Our study shows that the higher prevalence of MS in populations of northern European ancestry cannot simply be explained by the European ancestral origin of genetic risk factors . Rather , any difference in prevalence due to genetics might be partially explained by a combination of European risk alleles exerting greater risk ( i . e . HLA-DRB1*15:01 ) compared to non-European risk alleles , or the presence of protective alleles in individuals of non-European ancestry . However , this does not rule out the possibility that observed prevalence differences could result from the influence of environmental risk factors or socioeconomic status , including differences in access to neurologists and diagnostic protocols using MRI , that may be population-specific .
Institutional Review Board approval was obtained for this study by the UC Berkeley Committee on Protection of Human Subjects ( CPHS ) ( 2010-03-928 ) ; PROTOCOL TITLE: Genetic and non genetic risk factors for MS; UC San Francisco Human Research Protection Program Institutional Review Board ( IRB ) ( 10–05039 ) ; PROTOCOL TITLE: Environmental and genetic risk factors for pediatric multiple sclerosis; Kaiser Permanente Southern California IRB ( 5962 ) ; PROTOCOL TITLE: MS Sunshine Study; and Kaiser Permanente Northern California IRB ( CN-03CScha-05-H ) ; PROTOCOL TITLE: Genetic and Non-Genetic Predictors of Risk for Multiple Sclerosis . Written informed consent was obtained for all study participants at these sites . Genotype data from a total of 21 , 647 subjects were collected from the Northern and Southern California Kaiser Permanente memberships , the U . S . Pediatric MS Network , the Genetic Epidemiology Research on Aging ( GERA ) cohort , and International Multiple Sclerosis Genetics Consortium ( IMSGC ) . Table 9 shows the starting number of MS cases and controls by dataset . All cases met the diagnostic criteria for MS[24 , 25] . Subjects from Northern California Kaiser Permanente and U . S . Pediatric MS Network were genotyped on the Illumina Human660W-Quad BeadChip , Infinium Human OmniExpress BeadChip , and Infinium Human OmniExpress Exome BeadChip . Subjects from Southern California Kaiser Permanente were genotyped on OmniExpress platforms . The 1 , 265 African American subjects from IMSGC were genotyped using the Illumina Immunochip and combined with other African Americans to study the ancestry of the MHC region[8] . Note that IMSGC subjects were not genotyped genome-wide and were thus excluded from the genome-wide studies in this paper . Genotyping details for the GERA cohort are described elsewhere[26] . All genetic coordinates were converted to NCBI Build 37 before analysis . BEAGLE was used to obtain phased data for African Americans , Asian Americans , and Hispanics independently , using GRCh37 genetic map positions in centimorgans converted from GRCh37 genetic coordinates by BEAGLE utility software . Genetic map positions capture genetic linkage information and is used by RFMix for defining windows for local ancestry assignment . The reference panel used for phasing was constructed from selecting individuals from 1000 Genomes with ancestries present in each admixed population[27 , 28] . The ancestries represented in our dataset were European ( present in all groups ) , African ( present in African Americans and Hispanics ) , East Asian ( present in Asian Americans ) , and Native American ( present in Hispanics ) . Genome-wide imputation of the dataset against the entire 1000 Genomes phase 3 reference panel was carried out using IMPUTE2[27 , 29] . For HLA imputation , SNP2HLA was used to perform 2-field imputation of alleles for HLA-A , HLA-B , HLA-C , DRB1 , and DQB1 using an admixed reference panel from the 1000 Genomes Project , comprised of 165 Native Americans , 155 Africans , 251 East Asians , and 303 Europeans[27 , 30 , 31] . The reference panel was tailored to contain ancestries represented by the target population to enhance imputation accuracy , and HLA alleles in each admixed population were imputed independently as previously described[32] . SNPs were filtered for minor allele frequency ( > 0 . 01 ) and missingness on SNPs and samples ( > 0 . 10 ) before and after imputation with IMPUTE2 . Genotype probabilities from IMPUTE2 were converted to hard genotype calls using > 0 . 6 as the threshold , and SNPs were filtered for info score > 0 . 30 . Additionally , A/T and C/G SNPs were discarded prior to local ancestry inference to avoid strand ambiguity . Related individuals ( π^>0 . 25 ) were removed from further analysis , resulting in a total of 20 , 588 samples . For HLA imputation using SNP2HLA , we removed alleles with R2 scores less than 0 . 80 and with allele frequencies below 0 . 005 from further analysis , filtering out 40 , 66 , and 63 HLA alleles to result in 70 , 47 , and 77 HLA alleles for African Americans , Asian Americans , and Hispanics , respectively . All quality control ( QC ) steps were performed using the PLINK software and R v3 . 3 . 1 ( www . r-project . org ) [33] . Population structure was assessed using MDS and fastSTRUCTURE prior to genotype imputation in order to divide the samples into African American , Asian American , or Hispanic groups for further analysis[34] . MDS components captured ancestry to identify individuals likely to be African American , Asian American , or Hispanic , using reference populations from the Human Genome Diversity Project ( HGDP ) [35] . Subjects that cluster with the European reference samples were identified as White , non-Hispanic and subsequently removed . Then , fastSTRUCTURE was used for each group to estimate global admixture proportions for individuals using independent SNPs and a HGDP reference panel tailored to the target population , with default parameters . A cutoff of at least 5% Native American global ancestry for Hispanics was imposed to further remove White , non-Hispanic individuals who were removed based on MDS . The 1 , 163 candidate Hispanic individuals who did not meet this requirement had an average 0 . 7% Native American ancestry and 96% European ancestry . We inferred local ancestry genome-wide separately for African Americans , Asian Americans , and Hispanics using RFMix software analysis of imputed and phased genotype data , and a reference panel from the 1000 Genomes Project tailored to the target population[27 , 36] . The 1000 Genomes reference panel was selected over the HDGP reference panel as the appropriate reference because it has the required high genotype density for local ancestry inference . RFMix was run on recommended input parameters of 5 minimum number of reference haplotypes per tree node and 3 EM iterations . The number of generations of admixture used as input parameters for RFMix were 5 , 6 , and 11 for Asian Americans , African Americans , and Hispanics , respectively , according to previous estimates for populations in the United States [37] . Association testing between case status and genetic ancestry was performed using the nonparametric test statistic proposed by Montana and Pritchard for admixture mapping[38] . Briefly , the term z-l , d ( k ) represents the average local ancestry of cases at locus l for ancestry k and z-l , c ( k ) is similarly defined for controls . The term q-d ( k ) represents the genome-wide average of ancestry k among cases and q-c ( k ) is defined similarly for controls . Genome-wide ancestry estimates for this statistic are taken from local ancestry estimates from RFMix . This test statistic can be used to test for ancestry association at a single locus or at a region . Under the null , the test statistic follows the normal distribution and a P value can be obtained through a z-test . The variance Var ( z-l , d ( k ) -z-l , c ( k ) ) of the test statistic at a given locus was empirically estimated as the sum of variance of average ancestry among cases and controls . The standard deviation follows as the square root of the variance . This estimation corresponds to estimating the standard deviation of the average treatment effect , with disease status as treatment and ancestry as outcome[39] . All terms of the test statistic were estimated from local ancestry estimates from RFMix . Complete details are described elsewhere[38] . Multivariate logistic regression was applied to evaluate the association of genetic variants with MS , using an additive model and adjusting for the first three MDS components to control for population stratification[8 , 9] . ORs were used to characterize effect sizes of MS risk alleles . The Wilcoxon test was used to evaluate significance of global admixture proportion differences between cases and controls . All analyses were performed using PLINK and R v3 . 3 . 1 ( www . r-project . org ) [33] . Multiple hypothesis testing was addressed with Bonferroni correction . Bonferroni correction was used to establish significance for the study of non-HLA alleles , and adjusted p-values were provided for all multiple testing scenarios except when the number of tests is ten or less . For genome-wide association studies , a significance level of α = 0 . 05 with 15 , 282 tests results in a genome-wide significance level of 3 . 27 × 10−6 . Bonferroni correction was applied independently for the studies of African Americans , Hispanics , and Asian Americans . Since local ancestry assignments span multiple loci , we reduced the burden of multiple hypothesis testing for ancestry association across the genome by only testing one locus per window defined by RFMix for inferring local ancestry , resulting in a total of 15 , 282 tests genome-wide . Complete details of how RFMix defines windows for local ancestry inference is described elsewhere[36] . Power calculations are performed with the Genetic Association Study Power Calculator ( http://csg . sph . umich . edu/abecasis/cats/gas_power_calculator/ ) , which implements calculations from Skol et al . [40] . We assume an additive disease model , a MS prevalence of 0 . 1% in the United States , significance level of 5% , and disease allele frequency of 10%[41] . For HLA alleles , we assume a relative risk of 2 , and a relative risk of 1 . 2 for non-HLA alleles . SNPs and AAs imputed by SNP2HLA for European and African HLA-DRB1*15:01 alleles in African Americans were aligned to the UCSC Genome Browser GRCh38 RefSeq Genes track , and the European subsequences were compared to the African subsequences . Note that “subsequence” refers to only the imputed SNPs and AAs , and not to contiguous DNA or AA sequence . | Multiple sclerosis ( MS ) is an autoimmune disease that is mostly found in populations with northern European ancestry . Our study investigates whether there is evidence that the difference in MS prevalence around the globe could be explained by European MS genetic risk factors in African Americans , Hispanics , or Asian Americans . Our work first established that most alleles associated with MS are not necessarily European , but are in fact , cosmopolitan . However , we also observed in African Americans that European HLA-DRB1*15:01 conferred three times the odds of MS compared to the African allele . The allele HLA-DRB1*15:01 has been shown to be a major genetic risk factor in Europeans and other admixed populations . In addition , we observed genetic variations between European and African HLA-DRB1*15:01 alleles that , based on location , could influence the function of antigen-binding proteins involved in MS . Consequently , it is plausible that ancestry could explain the risk or protective effects of other MS-associated alleles . Additionally , our study found on chromosome 8 in Hispanics a region where MS cases have more European ancestry than controls , implicating there may be new MS risk alleles to be discovered in Hispanics . In conclusion , our study found evidence that the difference in MS prevalence could be explained by European ancestry and established that the ancestry of MS genetic risk factors is complex . | [
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] | 2019 | Admixture mapping reveals evidence of differential multiple sclerosis risk by genetic ancestry |
Mucosa-associated invariant T ( MAIT ) cells represent a large innate-like evolutionarily conserved antimicrobial T-cell subset in humans . MAIT cells recognize microbial riboflavin metabolites from a range of microbes presented by MR1 molecules . MAIT cells are impaired in several chronic diseases including HIV-1 infection , where they show signs of exhaustion and decline numerically . Here , we examined the broader effector functions of MAIT cells in this context and strategies to rescue their functions . Residual MAIT cells from HIV-infected patients displayed aberrant baseline levels of cytolytic proteins , and failed to mobilize cytolytic molecules in response to bacterial antigen . In particular , the induction of granzyme B ( GrzB ) expression was profoundly defective . The functionally impaired MAIT cell population exhibited abnormal T-bet and Eomes expression patterns that correlated with the deficiency in cytotoxic capacity and cytokine production . Effective antiretroviral therapy ( ART ) did not fully restore these aberrations . Interestingly , IL-7 was capable of arming resting MAIT cells from healthy donors into cytotoxic GrzB+ effector T cells capable of killing bacteria-infected cells and producing high levels of pro-inflammatory cytokines in an MR1-dependent fashion . Furthermore , IL-7 treatment enhanced the sensitivity of MAIT cells to detect low levels of bacteria . In HIV-infected patients , plasma IL-7 levels were positively correlated with MAIT cell numbers and function , and IL-7 treatment in vitro significantly restored MAIT cell effector functions even in the absence of ART . These results indicate that the cytolytic capacity in MAIT cells is severely defective in HIV-1 infected patients , and that the broad-based functional defect in these cells is associated with deficiency in critical transcription factors . Furthermore , IL-7 induces the arming of effector functions and enhances the sensitivity of MAIT cells , and may be considered in immunotherapeutic approaches to restore MAIT cells .
Mucosa-associated invariant T ( MAIT ) cells are a recently described subset of unconventional , innate-like T cells that are highly abundant in mucosal tissues , liver and circulation of healthy humans [1–4] . MAIT cells express a semi-invariant T cell receptor ( TCR ) , including Vα7 . 2 coupled with restricted Jα segments ( Jα33 , Jα12 , or Jα20 ) , and limited Vβ repertoires [5 , 6] . Together with their semi-invariant TCR , human MAIT cells are also defined by their high expression of CD161 , the IL-18 receptor α subunit ( IL-18Rα ) , and the transcription factor ZBTB16 [7] , also known as promyelocytic leukemia zinc finger protein ( PLZF ) [8 , 9] . The vast majority of MAIT cells are either CD8αα or CD8αβ , with some CD4/8 double-negative ( DN ) , and minor CD4+ populations [8–11] . Human MAIT cells acquire innate-like antimicrobial activity in the fetal intestinal mucosa pre-natally , prior to the establishment of the commensal microflora [12] . MAIT cells recognize antigens in complex with the MHC-Ib-related protein ( MR1 ) [2 , 4] , which displays an extraordinary level of evolutionary conservation among placental and marsupial mammals [4 , 13 , 14] . MR1 presents microbial vitamin B2 ( riboflavin ) metabolites from a wide range of microbes [15 , 16] , including unstable intermediates that are formed from non-enzymatic condensation of the early intermediate of riboflavin biosynthesis 5-amino-6-D-ribitylaminouracil ( 5-A-RU ) with host- or microbe-derived glyoxal or methylglyoxal [15 , 17] . MR1 captures these otherwise unstable compounds and presents them to MAIT cells [17] . Once activated by antigens , MAIT cells can rapidly kill infected cells [18 , 19] , inhibit intracellular microbial growth [20] , and produce pro-inflammatory cytokines including IFNγ , TNF , and IL-17 [8 , 10–12 , 21] . Certain innate cytokines , including IL-12 and IL-18 , can stimulate MAIT cells to produce IFNγ independently of the MR1-TCR interaction [22 , 23] . These findings are strongly supportive of the notion that MAIT cells perform critical functions in the immune system , also beyond their role as antimicrobial T cells , particularly at mucosal sites . Despite the great advances of antiretroviral therapy ( ART ) in the management of HIV disease , infected patients are still at an increased risk of microbial co-infections such as Mycobacterium tuberculosis , non-typhoidal Salmonella and Streptococcus pneumoniae [24–27] . Such microbial co-infection burdens are particularly apparent in individuals who are diagnosed at advanced stages , lack access to ART , and those who are non-adherent to therapy and clinical care . Although MAIT cells do not directly recognise viral antigens , indirect involvement of these cells in viral immunopathogenesis can occur , as we originally and others recently described for HIV-1 infection [11 , 21 , 28–31] . MAIT cell numbers and Th1/17 cytokine production are severely and persistently reduced in chronic HIV-infected patients [11] . The polymicrobial reactivity and breadth of the MAIT cell functional profile most likely contribute to the reported role of MAIT cells in the protection against diverse bacterial and mycobacterial infections in animal models , as well as in severe bacterial infections and pulmonary tuberculosis in humans [8 , 20 , 32–35] . MAIT cell defects may therefore predispose HIV-infected patients to an increased risk of acquiring microbial co-infections . Furthermore , the loss of MAIT cells is potentially irreversible if the disease is not treated at a very early stage [11 , 21 , 28–31] . In most settings of HIV-1 infection early diagnosis and treatment is challenging , and this necessitates a strategy where MAIT cells can be rescued through adjunctive immunotherapies . IL-7 is a pleiotropic cytokine that has strong survival and homeostatic effects towards T cells , particularly the memory T cell populations with which MAIT cells show similarities ( reviewed in [36] ) . IL-7 has attracted interest in the context of HIV-1 disease , and was proposed as a potential cytokine intervention therapy in treatment failure as well as in approaches to purge the viral reservoir ( reviewed in [37] ) . Furthermore , IL-7 was recently shown by Tang et al . to enhance MAIT cell Th1/17 cytokine production in response to polyclonal stimulation [38] . In the present study , we investigate the cytolytic function of MAIT cells in the context of HIV-1 infection , the basis for dysfunction of MAIT cells in this disease , and possible approaches to rescue their function . Our findings indicate that arming of cytolytic capacity in MAIT cells is severely defective in HIV-1 infected patients , and that the broad-based functional defects in these cells are associated with deficiency in critical transcription factors . Furthermore , IL-7 induces the arming of effector functions and enhances the sensitivity of MAIT cells in healthy donors , and can partially reverse the functional and transcription factor defects in MAIT cells from HIV-1 infected patients . Thus , inclusion of IL-7 may be considered in immunotherapeutic approaches to restore MAIT cell numbers and function in conditions associated with loss and dysfunction of these cells .
The expression levels of the cytolytic proteins perforin ( Prf ) , granzyme ( Grz ) A , GrzB , and granulysin ( Gnly ) , as well as the degranulation marker CD107a , were investigated in unstimulated MAIT cells obtained from 20 HIV-uninfected healthy controls ( Fig 1A and 1B ) , and compared with those of non-MAIT , conventional CD4+ and CD8+ T cells ( Fig 1B ) . The majority of MAIT cells expressed Prf and GrzA , whereas Gnly was expressed only by a proportion of MAIT cells and displayed high inter-donor variability ( Fig 1B ) . Interestingly , MAIT cells did not express GrzB at steady state ( Fig 1B ) . This pattern of cytolytic protein expression by MAIT cells was significantly different from non-MAIT , conventional CD4+ and CD8+ T cells ( Fig 1B ) , consistent with recent studies [18 , 19] . In addition , GrzA and Gnly in MAIT cells were co-expressed with the pore-forming protein Prf ( S1A Fig ) . We next determined MAIT cell cytolytic protein expression profile following overnight stimulation with mildly PFA-fixed E . coli in 20 healthy individuals , as we have previously shown that such stimulation triggers robust expression of pro-inflammatory cytokines in MAIT cells [11 , 12] . Following stimulation , MAIT cells expressed high levels of the degranulation marker CD107a , coupled with loss of Gnly and GrzA expression , a concomitant upregulation of GrzB and Prf , as well as IFNγ production ( Fig 1C ) . Furthermore , the high Prf and GrzB expression levels were predominantly found within the CD107a+GrzAlo MAIT cell population ( Fig 1D ) , indicating that MAIT cells exocytose these cytolytic proteins following bacterial stimulation . Interestingly , not all CD107a+GrzAlo MAIT cells produced IFNγ ( Fig 1D ) , suggesting that some functional heterogeneity within the MAIT cell population may exist . MAIT cell degranulation occurred rapidly , with detectable CD107a expression within two hours following bacterial feeding , followed by the appearance of GrzAlo MAIT cells , and then finally GrzB upregulation within 24 h post-stimulation with optimal upregulation at 72 h post-stimulation ( Fig 1E ) . Together , these results indicate that MAIT cells rapidly mobilize their cytolytic granules upon antigen stimulation , and upregulate GrzB expression to become fully armed effector T cells . Recent studies show that MAIT cells express the innate-like T cell transcription factor PLZF and the Th17 master transcription factor RORγt , which are likely to be responsible for the effector memory-like and Th17-like phenotype in MAIT cells , respectively [3 , 8 , 9] . However , the MAIT cell expression profile of other T cell transcription factors is unknown , including T box transcription factor 21 ( TBX21 , or T-bet ) , Eomesodermin ( Eomes ) , and Helios . Therefore , the intracellular expression of PLZF , RORγt , T-bet , Eomes , and Helios was investigated in peripheral blood MAIT cells from 10 healthy donors . As expected , MAIT cells expressed PLZF and RORγt ( Fig 2A ) . PLZF and RORγt co-expression in CD8+ T cells , total T cells , and to a lesser extent , in DN T cell populations accurately identified the MAIT cell population ( S1B Fig ) , whereas far fewer of either PLZF+RORγt- or PLZF-RORγt+ cells from any T cell population were MAIT cells ( S1B Fig ) . In addition , MAIT cells expressed the classical effector T cell transcription factors T-bet and Eomes , as well as Helios , with low expression levels for T-bet , high levels for Eomes , and intermediate levels for Helios ( Fig 2A ) . MAIT cells also appeared to express lower levels of T-bet coupled with higher levels of Eomes ( T-betdim Eomeshi ) when compared to conventional T cells and CD3- CD161+ lymphocytes ( predominantly NK cells ) ( Fig 2B ) . The MAIT cell expression level patterns for transcription factors were distinct to those expressed by conventional CD4+ and CD8+ T cells ( Fig 2A ) , and were homogeneous across the predominant DN and CD8+ MAIT cell subsets , although lower expression levels were observed in the minor CD4+ MAIT cell subset ( Fig 2C ) . A recent study showed that IL-7 can enhance MAIT cell production of Th1/17 cytokines following CD3/CD28 stimulation [38] . Here , we assessed whether IL-7 could enhance MAIT cell antimicrobial cytotoxic potential in healthy individuals . Following a 48 h stimulation with IL-7 alone , the expression levels of Prf and GrzA were elevated and GrzB expression was induced , and this occurred in the absence of concurrent production of Th1/17 cytokines ( Fig 3A and 3B ) . Such induction of cytolytic effector molecules by MAIT cells reached their maxima when incubated with 5–25 ng/ml of IL-7 ( S2A Fig ) . There was no significant effect of IL-7 on Gnly expression in resting MAIT cells ( S2B Fig ) . The induction of cytolytic effector molecule expression in MAIT cells by IL-7 was MR1-independent as determined by MR1 blocking using the 26 . 5 mAb ( S2B Fig ) . Interestingly , IL-7 enhanced the expression of PLZF , RORγt , T-bet , Eomes , and Helios in MAIT cells examined in eight healthy individuals ( Fig 3A and 3B ) . In contrast , there was no upregulation of Ki67 expression following IL-7 treatment , indicating that IL-7 did not trigger proliferation of MAIT cells ( S2C Fig ) . We next examined the effect of IL-7 treatment on MAIT cell effector responses following overnight stimulation with a suboptimal dose of mildly fixed E . coli ( MOI 0 . 01 ) . IL-7 treatment significantly enhanced expression of MAIT cell cytotoxic effector molecules and pro-inflammatory cytokine production as compared to MAIT cells exposed to bacteria alone ( Fig 3C and 3D ) . In addition , IL-7 boosted the sensitivity of MAIT cells and allowed degranulation , GrzB upregulation , and IFNγ production at an antigenic dose up to 1000-fold lower when compared to IL-7-untreated MAIT cells ( Fig 3E ) . The enhancement of MAIT cell effector function in response to E . coli stimulation reached its maximum when treated with 5–25 ng/ml IL-7 ( S2D Fig ) . IL-18 and IL-12 have been shown to stimulate MAIT cell effector function [19 , 22 , 23] . We therefore compared these cytokines with IL-7 in their capacity to arm MAIT cell effector function . In three HIV-uninfected donors , IL-7 was similar or superior to IL-18/IL-12 in arming and enhancing MAIT cell effector functions alone or following bacterial stimulation ( S3A and S3B Fig ) . The exception to this pattern was IFNγ , as IL-12/IL-18 triggered direct activation of this effector function both alone and together with E . coli stimulus ( S3A and S3B Fig ) . Furthermore and contrary to IL-7 treatment , IL-18/IL-12 seemed to enhance the decrease in MAIT cell numbers following bacterial stimulation ( S3C Fig ) . This observation is in line with previous studies where IL-18 and IL-12 triggered direct effector responses and were implicated in MAIT cell loss [30 , 39] . Because IL-7 treatment armed MAIT cells to become GrzB-expressing effector T cells , we investigated the effect of IL-7 on MAIT cell-mediated killing of bacteria-fed cells . Here , we utilized an in vitro model system where human MR1-expressing 293T ( 293T-hMR1 ) cells were fed mildly fixed E . coli and co-cultured with MAIT cells . Untreated MAIT cells were not able to significantly kill bacteria-fed target cells , whereas IL-7 treatment boosted MAIT cell killing of target cells by about 10-fold ( Fig 4A and 4B ) . In resting IL-7 untreated cells , there was a correlation between degranulation and GrzB co-expression ( CD107a+ GrzB+ ) by effector MAIT cells and target cell killing following exposure to E . coli ( S3D Fig ) . This pattern indicated that the lackluster killing of target cells by IL-7 untreated MAIT cells was due to the low levels of degranulation and GrzB ( Fig 4 ) . In contrast , MAIT cells that were treated with IL-7 expressed GrzB , readily degranulated and had even higher GrzB levels upon co-culture with bacteria-fed target cells ( Fig 4A ) . Both IL-7-treated and-untreated MAIT cell killing of target cells was ablated by anti-MR1 , suggesting that MAIT cell killing is predominantly MR1-dependent ( Fig 4A and 4B ) . Taken together , these results indicate that IL-7 arms MAIT cells to become effector T cells and potently induces MR1-dependent killing capacity through the upregulation of GrzB expression as well as other effector proteins , and this occurs concomitantly with elevated expression of transcription factors including T-bet and Eomes . The capacity of MAIT cells to produce pro-inflammatory cytokines is severely decreased in untreated chronic HIV-1 infection [11] . However , it remains unknown whether MAIT cell cytotoxic capacity is also impaired in this condition . To address this , we compared the expression of cytolytic proteins in unstimulated MAIT cells from 20 healthy controls and 25 ART untreated HIV-1 infected patients ( Table 1 ) . Levels of GrzA and Prf expressed by MAIT cells in HIV-1 infected patients were modestly , but significantly , lower than those in uninfected healthy controls ( Fig 5A , p = 0 . 0007 and p = 0 . 0008 , respectively ) . Interestingly , the levels of GrzB expression in MAIT cells from infected patients were significantly higher when compared to healthy controls ( p = 0 . 0004 ) , a pattern in line with the notion that these residual MAIT cells are partially activated , consistent with our previously published data [11] . There was no significant difference in the levels of Gnly in MAIT cells between HIV-1 infected patients and healthy controls ( median ( IQR ) = 16 . 3 ( 7 . 3–28 . 6 ) % and 14 . 5 ( 7 . 2–26 . 0 ) % respectively; p = 0 . 98 ) . The modest changes in expression of GrzA , Prf , and GrzB in unstimulated MAIT cells from these patients were not significantly restored following long-term ART ( n = 18; Fig 5A ) ( median ( IQR ) duration of ART = 38 . 5 ( 28–49 ) months ) . Next , we investigated the responses of MAIT cells in terms of GrzB arming and cytolytic potential following a 24 h bacterial stimulation ( Fig 5B ) . All measured facets of MAIT cell cytotoxic potential examined were impaired in chronic HIV-1 infection , including reduction in the levels of MAIT cells expressing CD107a+GrzAlo ( p = 0 . 0006 ) , CD107a+GrzB+ ( p<0 . 0001 ) , and CD107a+Prf+ ( p = 0 . 0036 ) phenotypes in response to bacteria ( Fig 5B and 5C ) . The severe deficiency of GrzB-expressing MAIT cells following bacterial stimulation was particularly striking given that this cell population had slightly upregulated GrzB levels at steady state ( Fig 5A ) , indicating that MAIT cells from HIV-1 infected patients have severely compromised ability to upregulate GrzB de novo following new microbial encounters . There were no significant correlations between MAIT cell cytotoxic potential and cytokine production with CD4 counts ( CD107a+GrzAlo Spearman’s r = 0 . 22 , p = 0 . 32; CD107a+GrzB+ r = 0 . 29 , p = 0 . 20; CD107a+Prf+ r = -0 . 04 , p = 0 . 88; CD107a+IFNγ+ r = -0 . 03 , p = 0 . 91 ) , plasma viral loads ( CD107a+GrzAlo Spearman’s r = 0 . 15 , p = 0 . 53; CD107a+GrzB+ r = 0 . 02 , p = 0 . 92; CD107a+Prf+ r = 0 . 05 , p = 0 . 83; CD107a+IFNγ+ r = -0 . 02 , p = 0 . 94 ) , nor with time since HIV diagnosis ( CD107a+GrzAlo Spearman’s r = -0 . 17 , p = 0 . 44; CD107a+GrzB+ r = 0 . 09 , p = 0 . 69; CD107a+Prf+ r = -0 . 26 , p = 0 . 26; CD107a+IFNγ+ r = -0 . 22 , p = 0 . 38 ) . Long-term ART partially restored all evaluated aspects of MAIT cell cytotoxic potential ( Fig 5C ) . However , it is important to note that in treated HIV-infected individuals the levels of GrzB up-regulation were still significantly lower ( p<0 . 0001 ) , and levels of Prf tended to be lower ( p = 0 . 063 ) , when compared to healthy controls . There were no significant correlations between the magnitude of MAIT cell cytotoxic capacity and cytokine production recovery after ART with duration of ART ( CD107a+GrzAlo Spearman’s r = 0 . 20 , p = 0 . 42; CD107a+GrzB+ r = 0 . 14 , p = 0 . 59; CD107a+Prf+ r = 0 . 30 , p = 0 . 25; CD107a+IFNγ+ r = -0 . 01 , p = 0 . 99 ) . In healthy individuals , the vast majority of MAIT cells express low but detectable levels of T-bet and high levels of Eomes ( T-betdimEomeshi; Fig 2B and Fig 6A ) . However , in HIV-1 infected patients there was a significant expansion of a MAIT cell population expressing neither transcription factors at detectable levels ( T-betnegEomesneg ) , and this was only partially reduced following long-term ART ( n = 14 ) ( Fig 6A ) . Detailed investigation revealed that the T-betnegEomesneg MAIT cell population also expressed significantly lower levels of PLZF , RORγt , and Helios when compared to the T-betdimEomeshi MAIT cell population ( all p<0 . 0001; Fig 6B ) . More importantly , the expansion of the T-betnegEomesneg MAIT cell population in HIV-infected patients was strongly correlated with MAIT cell depletion in the periphery ( Fig 6C ) , loss of MAIT cell cytotoxic potential ( CD107a+GrzAlo and CD107a+GrzB+; Fig 6D and 6E , respectively ) , and impaired IFNγ production ( Fig 6F ) in response to bacterial stimulation . Next , we investigated whether this aberrant MAIT cell transcription factor profile could be generated in vitro following a strong chronic antigenic exposure . A six day culture of PBMCs from healthy donors ( n = 3 ) with mildly fixed E . coli increased the frequency of T-betnegEomesneg MAIT cells ( Fig 6G ) . Similar to MAIT cells in HIV-infected patients with this phenotype , these in vitro-generated T-betnegEomesneg MAIT cells also expressed lower levels of PLZF and RORγt ( Fig 6G ) . The T-betnegEomesneg MAIT cells also expressed lower levels of GrzB . Finally , the aberrant T-betnegEomesneg MAIT cells proliferated less when compared to T-betdimEomeshi MAIT cells ( Fig 6G ) . The potential of IL-7 treatment to restore MAIT cell functional defects in HIV-1 infected patients was evaluated in vitro . Interestingly , GrzA and Prf upregulation following IL-7 treatment in samples from healthy controls ( n = 8 ) and HIV-1 infected patients ( n = 6 ) was not significantly different ( Fig 7A ) . However , whereas GrzB upregulation occurred in MAIT cells from both groups , it was weaker in HIV-1 infected patients suggesting that the cytotoxicity arming effect of IL-7 in these patients may be less distinct ( p = 0 . 0293 , Fig 7A ) . In a second round of experiments the ability of IL-7 to support the MAIT cell response in HIV-1 infected patients to a 24 h bacterial stimulation was evaluated . IL-7 treatment significantly improved all measured phenotypic aspects of MAIT cell cytotoxic potential including the generation of CD107a+GrzAlo , CD107a+GrzB+ , and CD107a+Prf+ phenotypes , as well as the production of IFNγ by MAIT cells ( n = 6 ) ( Fig 7B ) . Next , we investigated whether the improvement of MAIT cell effector functions by IL-7 treatment might be linked with restoration of the abnormal MAIT cell transcription factor profile in nine ART-untreated HIV-1 infected patients . Importantly there was no difference in CD127 levels by T-betnegEomesneg and T-betdimEomeshi MAIT cells ( S4A Fig ) . Next , PBMCs were cultured with IL-7 for a maximum of 48 h to minimize introducing potential confounders , including global cellular proliferation , activation-induced cell death , and HIV-1 replication that may result from a long-term IL-7 exposure . The frequency of T-betnegEomesneg MAIT cells showed a trend towards a decrease during this culture ( n = 9 , p = 0 . 0732; Fig 7C ) . Short-term IL-7 treatment also reduced the already low frequency of T-betnegEomesneg MAIT cells in seven HIV-uninfected healthy controls ( p = 0 . 0156; S4B Fig ) . We next evaluated whether plasma levels of IL-7 in vivo were associated with MAIT cell levels in 31 individuals enrolled in a second cohort of HIV-infected patients recruited from the same site ( Table 1 ) . The clinical parameters of cohort 2 were not significantly different when compared to those of cohort 1 . Furthermore , patients in cohort 2 saw a similarly significant depletion of MAIT cells , and a similarly significant increase in the levels of Vα7 . 2+CD161- T cells in peripheral blood ( S5A Fig ) as previously reported [11] . There was also a significant increase in MAIT cell activation as evaluated by expression of CD38 , HLA-DR , CD57 , and TIM-3 ( S5B Fig ) , and an inverse correlation between the levels of MAIT cells in circulation and MAIT cell CD38 expression ( S5C Fig ) . Consistent with our previous study and other studies [11 , 21 , 29 , 31] , there were no significant correlations between MAIT cell levels and either CD4 counts and plasma viral loads ( Spearman’s r = 0 . 074 , p = 0 . 70; and r = 0 . 22 , p = 0 . 23 , respectively ) . We also did not find any correlation between MAIT cell levels and plasma markers of microbial translocation ( LPS; Spearman’s r = 0 . 018 , p = 0 . 93 ) and innate immune activation ( sCD14; r = -0 . 14 , p = 0 . 45 ) . Having thus validated that cohort 2 was comparable to cohort 1 , the patients in cohort 2 displayed a positive correlation between the plasma levels of IL-7 and MAIT cell frequency and absolute counts in peripheral blood ( r = 0 . 45 , p = 0 . 011 , and r = 0 . 39 , p = 0 . 030 , respectively; Fig 7D ) . Furthermore , plasma IL-7 levels showed a weak positive correlation with the capacity of MAIT cells to respond to PFA-fixed E . coli stimulation ( CD107a+GrzAlo Spearman’s r = 0 . 45 , p = 0 . 11; CD107a+GrzB+ r = 0 . 50 , p = 0 . 072; CD107a+Prf+ r = 0 . 59 , p = 0 . 028; CD107a+IFNγ+ r = 0 . 54 , p = 0 . 050 ) ( Fig 7E ) . While there were weak correlations with CD4 counts ( Spearman’s r = -0 . 34 , p = 0 . 017 ) and plasma viral loads ( r = 0 . 29 , p = 0 . 040 ) , there were no significant relationships between plasma IL-7 levels and CD38 , HLA-DR , CD57 , and TIM-3 expression in MAIT cells ( S6 Fig ) . Taken together , these results suggest that IL-7 plasma levels may directly influence MAIT cell numbers and their capacity to respond to microbial challenge in HIV-infected patients .
MAIT cells are emerging as a significant component of the cellular immune defenses against microbial infection . They are found in circulation and enriched in intestinal mucosa , liver and lung . We and others have shown that patients with HIV-1 infection suffer numerical loss and functional decline of their MAIT cells . This was at first glance unexpected given that MAIT cells are mostly CD8+ or DN T cells with only very few expressing CD4 . Furthermore , the antigens recognized by MAIT cells are of bacterial and fungal origin meaning that the exhausted functional phenotype of MAIT cells may be due to engagement not in antiviral immune responses , but rather in a response against microbes at mucosal barriers . Here , we have shown that the functional defect in MAIT cells also includes the cytolytic potential , with low levels of GrzA and Prf expression and a particularly striking defect in GrzB arming . This is likely to have significant consequences for MAIT cell-mediated control of intracellular microbes where direct cytolysis plays a significant role . MAIT cells play a role in immune defense against mycobacteria [8 , 33] , are involved in tuberculosis [40] , as well as sepsis and severe bacterial infections in humans [35] . Even in the current era of effective ART , HIV-1 infected patients have impaired control of mycobacterial and other non-opportunistic pathogens , with increased risk of developing infections from such pathogens [27] . Bacterial sepsis is now the principal cause of intensive care unit admission and death for HIV-1-infected patients who are admitted to hospital even in western countries [41] . Because of MAIT cells’ abundance , strategic locations at the body barrier sites , and potent antimicrobial activities against diverse pathogenic microbes , the broad numerical decline and severe dysfunction of MAIT cells may significantly contribute to morbidities and mortalities from both AIDS-defining infections and non-AIDS-related infections in HIV-1-infected patients . Importantly , long-term effective ART did not rescue the ability of MAIT cells to arm with GrzB in response to bacterial antigen , indicating that this deficiency may be largely irreversible in HIV-infected people . The development and function of MAIT cells is dependent on expression of the transcription factor PLZF , and we also confirm that they express RORγt consistent with their potential to produce IL-17 . In fact , our data suggest that the combination of PLZF and RORγt expression is sufficiently distinctive such that it can be used to identify this innate T cell population in the absence of the Vα7 . 2 TCR and CD161 combination . In addition , MAIT cells express the two classical effector T cell T-box transcription factors T-bet and Eomes , as well as Helios , with low expression levels for T-bet , high levels for Eomes , and intermediate levels for Helios . This pattern is in keeping with the effector memory-like phenotype of MAIT cells [42 , 43] . Helios is a member of the Ikaros family and is predominantly studied in relation to regulatory T ( Treg ) cell subsets [44 , 45] . Recently , however , the role of Helios beyond Treg subsets has been recognized , including as a marker for T cell activation , proliferation , and helper T cell subsets [46 , 47] . The role of Helios in MAIT cells is currently unclear and warrants further studies . Nevertheless , this pattern indicates that MAIT cells express a unique combination of these critical transcription factors and may have a unique transcriptional program underlying their distinct phenotypic and functional profile . Interestingly , the exhausted characteristics of MAIT cells in HIV-1 infected patients were paired with the appearance of a dysregulated expression pattern of these critical transcription factors . The occurrence of MAIT cells deficient in both Eomes and T-bet correlates strongly with both the functional impairment and the numerical decline of these cells . Of note , such aberrant MAIT cells also had low levels of RORγt , which is in line with our previous observation that MAIT cells from HIV-infected patients were unable to produce IL-17 following bacterial stimulation [11] . This indicates that the defects of MAIT cells are broad-based and occur at the transcriptional level . It is possible that this effect might be due to continuous antigenic burden relating to loss of control of bacterial infections as well as to microbial translocation in HIV-infected patients . Indeed , chronic stimulation with mildly fixed E . coli generated MAIT cells deficient in both T-bet and Eomes . Importantly , these in vitro-generated MAIT cells lacking T-bet and Eomes also had low GrzB levels , consistent with the partially redundant activities of T-bet and Eomes in inducing GrzB in cytotoxic CD8 T cells [48 , 49] . It is however possible that other pathways may be involved in the generation of T-bet and Eomes defective MAIT cells in vivo . IL-7 has strong effects on T cell homeostasis and supports the survival of T cells by upregulating Bcl-2 . These characteristics have made IL-7 attractive for cytokine immunotherapy in humans . MAIT cells express high levels of the IL-7Rα ( CD127 ) [12 , 38] , a finding that opened the possibility that IL-7 may have strong effects on MAIT cells . Interestingly , IL-7 alone in the absence of other stimuli was capable of arming resting MAIT cells from healthy donors into cytotoxic GrzB+ effector T cells . The induction of GrzB is profound , as resting MAIT cells essentially lack expression of this protein . Along with this effect , MAIT cells also further upregulated Prf and GrzA , without inducing any detectable spontaneous cytokine production . In the absence of bacterial antigen the effect of IL-7 is thus specifically to induce the cytotoxic arming of MAIT cells . Importantly , this in turn leads to a significantly increased cytolytic activity against MR1-expressing targets pulsed with bacteria . Perhaps an even more striking and potentially physiologically important effect is the radically enhanced sensitivity of MAIT cells to very low bacterial doses after IL-7 treatment . IL-7 supports strong cytokine production and cytolytic responses at antigen doses that are otherwise non-stimulatory for MAIT cells . These effects are consistent with the observations by Tang et al . , where IL-7 enhanced expression of the TCR , CD8 chains and components of TCR signaling pathway [38] . Altogether , IL-7 may be suitable for immunotherapy approaches aimed at enhancing MAIT cell function in humans . MAIT cells from HIV-infected patients significantly restored their effector functions after a short incubation with IL-7 in vitro . This effect was evident both in terms of arming , i . e . upregulation of in particular GrzB in resting non-antigen activated MAIT cells , and in terms of boosting the anti-bacterial degranulation and IFNγ response in MAIT cells . It should however be noted that the low levels of residual MAIT cells did not allow direct assessment of MAIT cell cytolytic capacity in HIV-1 infected patients . Interestingly , IL-7 has received attention as an adjunctive cytokine immunotherapy in HIV-1 infected patients to help restore immune functions that remain impaired even after successful ART . Particularly interesting were the recent observations by Sereti et al . , that IL-7 treatment helped replenish the mucosal T cell compartment and supported an improved mucosal barrier function as evidenced by decreases in relevant biomarkers of microbial translocation [50] . Our findings in the present study open the possibility that these effects in patients involve the MAIT cell compartment . In such a model the mucosal T cell subsets including MAIT cells improve their numbers and function to alleviate the gut mucosal abnormalities of chronic HIV-1 infection . This possibility is further supported by the weak positive correlation we observe between plasma IL-7 levels and MAIT cell levels in vivo . In summary , the findings in this study indicate that arming of cytolytic capacity occurs rapidly upon detection of bacterial antigen in MAIT cells in healthy donors , and this response is severely defective in HIV-1 infected patients . The broad-based functional defects in MAIT cells in chronic HIV-1 infection are associated with deficiency in the critical transcription factors Eomes and T-bet . Furthermore , our data show that IL-7 induces the arming of effector functions and enhances the sensitivity of MAIT cells in healthy donors , and can partially reverse the functional and transcription factor defects in MAIT cells from HIV-1 infected patients . These findings support the inclusion of IL-7 in immunotherapeutic approaches to restore MAIT cell numbers and function in HIV-1 infection as well as other conditions associated with loss and dysfunction of these cells .
Written informed consent was obtained from all study participants in accordance with study protocols conforming to the provisions of the Declaration of Helsinki and approved by the Regional Ethics Review Board in Stockholm ( Protocols 2007/772-32 , 401/01 , and 2009-1485-31-3 ) . HIV-1 infected patients were from the Karolinska University Hospital Huddinge Infectious Diseases Outpatient Clinic ( Stockholm , Sweden ) ( Table 1 ) [11] . Inclusion criteria were that patients were HIV-1 seropositive and had no history of AIDS-defining illness in the 12 months prior to recruitment . Healthy HIV-uninfected individuals were recruited at the Blood Transfusion Clinic at the Karolinska University Hospital Huddinge . PBMCs were isolated from peripheral blood by Ficoll-Hypaque density gradient centrifugation ( Pfizer-Pharmacia or Axis-Shield ) , and either allowed to rest overnight in complete medium , or cryopreserved in liquid nitrogen until required . PBMCs were cultured in 10 ng/ml recombinant human IL-7 ( R&D Systems ) , a combination of IL-12 and IL-18 ( 10 ng/ml and 100 ng/ml , respectively; PeproTech ) for 24–48 h , as indicated or left untreated at 37°C and 5% CO2 in RPMI medium supplemented with 10% fetal calf serum and 50 μg/ml gentamicin ( Gibco ) ( RF10 medium ) prior to functional assay . MAIT cell functions were determined in vitro using a paraformaldehyde ( PFA ) -fixed E . coli stimulation ( D21 strain , MOI as indicated ) in the presence of 1 . 25 μg/ml anti-CD28 mAb ( BD Biosciences ) [11] . PBMCs were further cultured for 24 h , and in selected experiments , 0 . 4 μg/ml anti-CD107a PECy7 ( BD Biosciences ) was added at the start of bacterial stimulation , and monensin ( Golgi Stop , BD Biosciences ) was added during the last six hours of the stimulation . In selected experiments , cells were stained with Cell Trace Violet ( CTV ) Cell Proliferation Kit ( Life Technologies ) as per manufacturer’s instructions and cultured in RF10 medium with fixed E . coli in the presence of anti-CD28 for six days as described [12] . Vα7 . 2+ T cells were purified from freshly isolated PBMCs using Vα7 . 2-APC antibody , followed by anti-APC microbeads ( Miltenyi Biotec ) and positive selection using MACS Cell Separation ( Miltenyi Biotec ) . The purity of enriched Vα7 . 2+ T cells was typically >95% , with minimum MAIT cell purity of 90% . Vα7 . 2+ T cells were cultured in RF10 medium supplemented with 25 ng/ml recombinant human IL-7 or in RF10 medium alone for 72 h . Human 293T cells stably transfected with human MR1 ( 293T-hMR1 cells; a kind gift from Dr . Ted Hansen ) [4] were incubated with PFA-fixed E . coli at an MOI of 10 for three hours , followed by the addition of anti-MR1 mAb ( 26 . 5; Biolegend ) or IgG2a isotype control ( MOPC-173; Biolegend ) for 60 min prior to the addition of Vα7 . 2+ T effector cells at the indicated effector to target ( MAIT:293T-hMR1 ) ratio . The MAIT:293T-hMR1 ratio was adjusted to take into accounts the overall purity of MAIT cells within the Vα7 . 2+ T cell population as the contaminating Vα7 . 2+CD161- T cells did not mediate cytotoxicity . Target cell apoptosis was detected through the fluorescent inhibitor of caspases ( FLICA ) flow cytometry-based methodology . Briefly , the FLICA reagent ( Vybrant FAM Poly Caspases Assay Kit , Life Technologies ) was added at a final concentration of 0 . 2% ( v/v ) to the MAIT-293T-hMR1 cell culture at the beginning of the assay , and anti-CD107a PECy7 at a total concentration of 0 . 4 μg/ml was also added to detect MAIT cell degranulation . After 24 h of culture , cells were harvested and stained to simultaneously detect MAIT cell cytotoxicity and 293T-hMR1 cell death . Anti-CD3 Alexa Fluor ( AF ) 700 ( clone UCHT1 ) , anti-CD4 APC-H7 ( clone SK3 ) , anti-CD38 PECy7 ( clone HIT2 ) , anti-CD161 PECy5 ( clone DX12 ) , anti-GrzB AF700 ( clone GB11 ) , anti-HLA-DR APC-H7 ( clone L243 ) , anti-RORγt PE ( clone Q21-559 ) , anti-TNF PECy7 ( clone MAb11 ) were from BD Biosciences; anti-CD3 Brilliant Violet ( BV ) 510 and BV785 ( clone OKT3 ) , anti-CD4 BV711 ( clone OKT4 ) , anti-CD8 BV570 ( clone RPA-T8 ) , anti-CD57 Pacific Blue , anti-CD107a PECy7 ( clone H4A3 ) , anti-CD127 BV650 ( clone A019D5 ) , anti-CD161 BV605 ( clone HP-3G10 ) , anti-granulysin PE ( clone DH2 ) , anti-granzyme ( Grz ) A AF700 ( clone CB9 ) , anti-GrzB FITC ( clone GB11 ) , anti-IFNγ BV785 ( clone 4S . B3 ) , anti-IL-17A BV421 and BV711 ( clone BL168 ) , anti-Ki67 BV421 ( clone Ki-67 ) , anti-perforin BV421 ( clone B-D48 ) , anti-T-bet BV605 and BV711 ( clone 4B10 ) , and anti-Vα7 . 2 APC , PE , and PECy7 ( clone 3C10 ) were from Biolegend; anti-Eomes FITC ( clone WD1928 ) , and anti-Helios eFluor 450 ( clone 22F6 ) were from Ebioscience; anti-CD8 Q-dot 655 ( clone 3B5 ) , and live/dead aqua and near infrared fixable cell stain were from Life Technologies; anti-PLZF APC ( clone 6318100 ) , and anti-TIM-3 AF488 ( clone 344823 ) were from R&D systems . Cell surface staining was performed using directly conjugated antibodies and fixed in Cytofix/Cytoperm or in Transcription Factor Fixation/Permeabilization buffer ( both from BD Biosciences ) as appropriate . Intracellular staining was performed using the relevant mAbs in Perm/Wash or Transcription Factor Perm/Wash buffer as appropriate ( both from BD Biosciences ) . Samples were acquired on an LSRFortessa 18-colour flow cytometer ( BD Biosciences ) equipped with 405 , 488 , 561 and 639 nm lasers . Single-stained polystyrene beads ( BD Biosciences ) were used for compensation purposes . Software-based compensation was performed using the compensation platform in FlowJo software version 9 . 6 ( Tree Star ) . Circulating IL-7 was detected in plasma ( diluted 1:4 ) using the Quantikine HS Human IL-7 Assay ( RnD Systems , Abingdon , UK ) , according to the manufacturer’s instructions . Each sample was assayed in duplicate . Significant differences in independent samples were assessed using Fisher’s exact test for categorical variables . Continuous variables were first assessed for normality , and differences in independent samples were assessed using t-test or Mann-Whitney test for continuous variables as appropriate . The Wilcoxon signed rank test or paired t-test as appropriate was used to determine significance between paired samples . The Friedman test followed by Dunn’s post-hoc test was used to detect differences across multiple , paired samples . Correlations were evaluated using Spearman’s rank correlation . Statistical analyses were performed on raw data using Prism version 6 . 0f ( GraphPad ) , and two-sided p-values < 0 . 05 were considered significant . | The mucosa-associated invariant T ( MAIT ) cells recognize antigens that are byproducts of the riboflavin biosynthesis pathway shared by many microbes . These antigens are presented by the MHC class I-like MR1 molecules and trigger rapid activation of MAIT cells in an innate-like fashion with deployment of effector mechanisms including cytokine production and cytolysis . Here , we investigated the MAIT cell response to bacteria in humans infected with HIV-1 , and possible means to restore functionality to these cells . MAIT cell dysfunction in HIV-infected patients included an inability to express components of the cytolytic effector machinery . Impairment of the MAIT cell population involved the loss of expression of the transcription factors T-bet and Eomes . Interestingly , IL-7 had strong effects on MAIT cells , including the antigen-independent arming of cytolytic function and enhanced sensitivity for low levels of bacteria . In HIV-infected patients , plasma IL-7 levels were positively associated with the size of the MAIT cell population , and IL-7 could rescue their function . These findings indicate that MAIT cell impairment in HIV-1 infection is broad-based , includes loss of critical transcription factors , and loss of cytolytic function . Furthermore , the data support the notion that IL-7 is a strong candidate for immunotherapy in diseases associated with MAIT cell loss . | [
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] | [] | 2015 | Arming of MAIT Cell Cytolytic Antimicrobial Activity Is Induced by IL-7 and Defective in HIV-1 Infection |
Cells from all kingdoms of life produce extracellular vesicles ( EVs ) . Their cargo is protected from the environment by the surrounding lipid bilayer . EVs from many organisms have been shown to function in cell–cell communication , relaying signals that impact metazoan development , microbial quorum sensing , and pathogenic host–microbe interactions . Here , we have investigated the production and functional activities of EVs in a surface-associated microbial community or biofilm of the fungal pathogen Candida albicans . Crowded communities like biofilms are a context in which EVs are likely to function . Biofilms are noteworthy because they are encased in an extracellular polymeric matrix and because biofilm cells exhibit extreme tolerance to antimicrobial compounds . We found that biofilm EVs are distinct from those produced by free-living planktonic cells and display strong parallels in composition to biofilm matrix material . The functions of biofilm EVs were delineated with a panel of mutants defective in orthologs of endosomal sorting complexes required for transport ( ESCRT ) subunits , which are required for normal EV production in diverse eukaryotes . Most ESCRT-defective mutations caused reduced biofilm EV production , reduced matrix polysaccharide levels , and greatly increased sensitivity to the antifungal drug fluconazole . Matrix accumulation and drug hypersensitivity of ESCRT mutants were reversed by addition of wild-type ( WT ) biofilm EVs . Vesicle complementation showed that biofilm EV function derives from specific cargo proteins . Our studies indicate that C . albicans biofilm EVs have a pivotal role in matrix production and biofilm drug resistance . Biofilm matrix synthesis is a community enterprise; prior studies of mixed cell biofilms have demonstrated extracellular complementation . Therefore , EVs function not only in cell–cell communication but also in the sharing of microbial community resources .
Vesicles are released externally by cells of bacteria , archaea , and eukaryotes [1–3] . These extracellular vesicles ( EVs ) deliver cargo of RNA and protein that is protected by a surrounding lipid bilayer . Classes of EVs have been distinguished based upon their size , cargo , and mechanisms of biogenesis [1–3] . Functional analysis has shown that EVs play diverse biological roles in delivery of effectors to target cells . For example , during Drosophila wing development , secretion of the morphogenic effector Hedgehog in EVs is required for activation of many of its target genes [4] . For many bacterial pathogens , toxin delivery via EVs causes host cell damage or lysis [1] . In the case of the eukaryotic protozoan Trypanosoma brucei , EVs orchestrate community escape from sources of environmental stress [5] . The purpose of EV secretion is thus tailored to each organism's biology and environmental context . Microorganisms exist predominantly in surface-associated communities called biofilms , which typically have high cell density and include an extracellular polymeric matrix [6] . Biofilm cells are notorious for their resistance to antimicrobial treatments [7] , a property often determined by multiple mechanisms [8] . Our interest is in the eukaryotic microorganism Candida albicans , which poses a severe threat to hospitalized patients with vascular devices due to its capacity for biofilm formation [9 , 10] . Candida species proliferate on the surface of these devices as a biofilm [11–13] . Candida biofilm cells resist available drug therapies [14] , and thus , the only currently effective therapy is removal of medical devices , which is often impossible for critically ill patients [15] . One of the central determinants of C . albicans ( mating type locus [MTL] a/α ) biofilm drug resistance is a mannan–glucan complex in the extracellular matrix [16 , 17] . Our findings reported here show that EVs promote assembly of the mannan–glucan complex that leads to drug resistance . We suggest that drug resistance of other microbial biofilms may also rely upon the efficient sharing of community resources as EV cargo .
We have reported that C . albicans biofilm extracellular matrix includes a significant phospholipid component [18] , a finding that might indicate the presence of EVs in the matrix material . In support of this idea , we observed numerous <100-nm spheres on the surface of biofilm cells ( Fig 1A ) and embedded in the extracellular matrix ( Fig 1B ) . EVs , isolated from biofilm [19 , 20] and imaged by cryoTEM , were enriched for an exosome population based upon size [21] ( Fig 1C ) , though other vesicle types may be included in the preparation . Time course studies revealed that vesicle production peaks at 48 h after biofilm initiation ( Fig 1D ) . These kinetics paralleled the time course of both biofilm cell accumulation and matrix deposition [22] . Our results indicate that C . albicans , like many other microbes [1 , 23] , produces biofilm EVs . EVs are known to be produced by free-living planktonic cells of numerous fungi , including C . albicans [1 , 24 , 25] . We assessed the similarity of biofilm and planktonic EVs through comparisons of their sizes and composition . The present observations with C . albicans are consistent with studies of Saccharomyces cerevisiae [26] revealing the production of two populations of planktonic EVs ( Fig 1E ) . There is a 30–200-nm diameter population that corresponds in size to exosomes and a larger 200–1 , 000-nm diameter population that corresponds in size to microvesicles [26] . In contrast , biofilm EVs comprise predominantly a 30–200-nm diameter exosome-sized population ( Fig 1F ) . Proteomic analysis revealed that planktonic and biofilm EVs have a considerable proportion of distinct cargo , with 34% of the proteome being unique to the biofilm state ( Fig 2A–2C and S1 Table ) . In addition , many proteins shared by vesicles from both sources were 10- to 100-fold more abundant in the biofilm EVs . Our results indicate that EVs produced by biofilms are distinct from those of planktonic cells . The composition of biofilm EVs pointed toward two prospective roles in biofilm extracellular matrix biogenesis . First , vesicle composition shows a high degree of similarity with matrix composition protein ( Fig 2D–2F ) and polysaccharide content ( Fig 2G and 2H ) , suggesting that vesicles may be a major source of matrix material . The protein comparison suggests that up to 45% of the proteins in the biofilm matrix may be delivered by vesicles ( Fig 2F and S2 Table ) . Polysaccharide analysis revealed a predominance of mannan and glucan , two major matrix components , in vesicle cargo by gas chromatography , which identified both components in a percent ratio of 84 . 0 ± 1 . 6/3 . 2 ± 1 . 0 in vesicles and 44 . 3 ± 4 . 2/8 . 8 ± 1 . 2 in the matrix , respectively . The major mannan component of the complex displayed structural similarity to the biofilm matrix mannan–glucan complex by 1H NMR in Fig 2G and S3 Table and 2D 1H-13C NMR in Fig 2H and S4 Table , a determinant of biofilm associated drug resistance [27] . Thus , biofilm vesicles may deliver cargo that forms the extracellular matrix . Comparative analysis of the lipid composition of biofilm EVs and matrix revealed similarity in the sphingolipid and phospholipid components , particularly in phosphatidylcholine , phosphatidylinositol , and phosphatidylethanolamine ( Fig 2I ) . However , the neutral lipid component in the extracellular matrix appeared distinct and likely reflects an additional vesicle-independent mechanism of delivery for the remaining lipid constituents . A second possible role is that vesicle cargo has a catalytic function in matrix macromolecule synthesis . Specifically , one of the enriched functional ontology categories for the biofilm EV proteome was polysaccharide modification ( Fig 2A–2F ) . These observations suggest that biofilm EVs may deposit cargo that contributes directly to matrix structure , and they may also provide catalytic activities that engage in matrix polysaccharide synthesis . We sought to test our hypothesis that biofilm EVs function in matrix biogenesis . The size range of biofilm EVs suggests that they are exosomes [21] , and in other eukaryotes , exosome production is governed by the endosomal ESCRT pathway [21] . In fact , we note that biofilm vesicle cargo includes ESCRT subunits Hse1 and Vps27 ( S1 Table ) . We identified 21 C . albicans ESCRT subunit homologs to S . cerevisiae and created homozygous deletion mutants ( Fig 3A and 3B ) . Sixteen of the mutants showed decreased vesicle production ( Fig 3B ) . We note that exosome production depends upon only a subset of ESCRT subunits in other eukaryotes [3 , 21] in keeping with our observations for C . albicans . The ESCRT mutants with reduced EV production enabled us to test whether biofilm vesicles have a role in biofilm matrix biogenesis and function . We screened the ESCRT vesicle–defective mutants for biofilm matrix–associated phenotypes . All mutants produced a biofilm structure , but a subset had prominent defects . Seven of the ESCRT mutants exhibited hypersusceptibility to the antifungal fluconazole during biofilm growth ( Fig 3C ) . The enhanced susceptibility biofilm phenotype was reversed in each of these ESCRT mutants for which a WT allele was introduced ( despite multiple attempts , we did not successfully construct a VPS2 complemented strain ) . This change in drug susceptibility was biofilm specific , as planktonic susceptibility was similar in WT and these ESCRT mutants ( MIC range 0 . 25–0 . 5 μg/ml ) . The clinical relevance of these observations was confirmed via demonstration of congruent drug-susceptibility phenotypes in the rat vascular catheter biofilm model [28] ( Fig 3D ) . Our previous studies have shown that biofilm matrix sequesters antifungals to promote drug resistance [16 , 17 , 29] , and we verified that the six of the seven drug-susceptible ESCRT mutants were also defective in fluconazole sequestration ( Fig 3E ) . We speculate that the sole ESCRT mutant that did not exhibit altered drug sequestration ( DOA4 ) may reflect a difference in vesicle cargo or perhaps a matrix-independent resistance mechanism . Drug sequestration has been linked to matrix quantity and presence of a mannan–glucan complex ( MGCx ) . Each of the ESCRT mutants with vesicle and drug-susceptibility defects similarly displayed defects in matrix mannan and glucan quantity ( Fig 3F ) . As the vesicles alone did not sequester antifungals ( S1 Fig ) , we reason this phenomenon is due to vesicle matrix delivery . These extracellular matrix defects are also demonstrated visually by the absence of matrix that adorns WT biofilms for each of the seven vesicle mutants ( Fig 3G ) . We considered two models for the relationship between ESCRT function , biofilm EVs , and matrix biogenesis . One model is that biofilm EVs have a direct role in matrix biogenesis; ESCRT defects cause matrix defects by reducing the levels of vesicles or packaging of functionally relevant cargo . An alternative model is that EVs have no role in matrix biogenesis; ESCRT defects cause matrix defects due to indirect effects . The second model stems from the growing appreciation that ESCRT machinery , with its central role in organelle physiology , has impact on diverse aspects of cell biology [30] . We used a “vesicle add-back” protocol to test these models ( Fig 4A ) . Specifically , if vesicles have a direct role in matrix biogenesis , then providing WT biofilm vesicles to a vesicle-defective ESCRT mutant should restore matrix production and matrix-associated phenotypes . Remarkably , the addition of the WT vesicles to drug-susceptible ESCRT mutants increased drug resistance dramatically ( Fig 4B ) . Furthermore , the addition of WT biofilm vesicles restored biofilm matrix architecture and quantities of the key mannan–glucan components ( Fig 4C and 4D ) . These results support the first model: a subset of ESCRT subunits promote matrix biogenesis and function through their role in biofilm EV production . Among the proteins in biofilm EVs , several have previously defined roles in biofilm matrix biogenesis and specifically matrix polysaccharide modification ( S2 Table ) [16 , 27] . We considered a model in which the presence of these proteins as vesicle cargo is central to their functional activity; they are “functional passengers . ” An alternative model is that they are “coincidental passengers” in vesicles and that their true function is vesicle independent . For example , they may function in matrix biogenesis at intracellular sites or after conventional secretion into the extracellular milieu . We deployed our vesicle add-back protocol to test these models , using mutants in cargo proteins putative glycanosyltransferase ( Phr1 ) and putative endo-beta-D-glucosidase ( Sun41 ) , which act in the glucan modification pathway ( Fig 4E ) [16 , 31] . Remarkably , addition of WT vesicles to these drug susceptible cargo mutants restored drug resistance . Control studies in which vesicles from the Phr1 and Sun41 mutants were added to the respective mutants did not alter the fluconazole susceptibility phenotype . These results favor the functional passenger model—that cargo proteins function to confer biofilm drug resistance as vesicle components rather than through some vesicle-independent activity . Our results indicate that biofilm growth of C . albicans results in a distinctive EV population and cargo . These findings echo studies of bacterial and eukaryotic cells that show that EV properties reflect environmental and developmental signals [1 , 3] . Our findings also add a new facet to the understanding of EV function: whereas prior studies have shown a role for EVs in cell–cell signaling , our studies reveal a role for EVs in the sharing of community resources [27] , that of biofilm matrix material . Matrix is a pivotal determinant of C . albicans biofilm drug resistance , and our results reveal EV-dependence for drug resistance both in vitro and in an animal biofilm infection model . Our findings suggest that EV-based therapeutics [32] may be a useful new platform for antibiofilm strategies .
All animal procedures were approved by the Institutional Animal Care and Use Committee at the University of Wisconsin according to the guidelines of the Animal Welfare Act , The Institute of Laboratory Animal Resources Guide for the Care and Use of Laboratory Animals , and Public Health Service Policy . The approved animal protocol number is DA0031 . The parent strain C . albicans SN152 ( MTL a/α ) was used to create homozygous deletion strains ( S6 Table ) using a SOE-PCR-based disruption cassette method , employing histidine and lysine auxotrophic markers [33] . PCR with primers listed in S5 Table was used to verify genotypes . Complementation of mutant strains with a single gene-of-interest copy used selection for arginine prototrophy . Transformants were selected on minimal medium with the corresponding auxotrophic supplements . Both planktonic and biofilm cultures were grown in RPMI 1640 , buffered with 4-morpholinepropanesulfonic acid ( MOPS ) for all experiments described below [34] . One of four in vitro biofilm models was used , including a 96-well or 6-well polystyrene plate , polystyrene roller bottle , or glass coverslip . Biofilm drug susceptibility was assessed using the 96-well flat-bottom polystyrene plate assay [35–38] . Matrix composition assessment utilized the 6-well plate assay . Biofilm architecture was imaged using scanning electron micrograph ( SEM ) using a coverslip biofilm assay . Matrix biochemistry was determined from biofilms growing , using a rolling bottle system [34] . A minimum of three biological replicates were performed for each assay . Biofilm matrix for matrix biochemical analysis was grown using a rolling bottle biofilm model [34] . After 48 h of growth , media was removed , and the Candida biofilms were dislodged from the roller bottle surface by spatula . The intact biofilm was then gently sonicated to remove matrix from cells ( sonication with a 6-mm microtip at 20 kHz with an amplitude of 30% for 8 min ) , followed by centrifugation to separate fungal cells from the matrix . The isolated matrix was then lyophilized . Matrix was similarly isolated from 6-well biofilm plates [16] . EVs were isolated from both planktonic cultures and large-scale biofilms grown in polystyrene roller bottles [34] . The culture media was removed from the bottles , filter sterilized , and concentrated down to 25 ml using a Vivaflow 200 unit ( Sartorius AG , Goettingen , Germany ) equipped with a Hydrosart 30 kDa cut-off membrane . The sample was centrifuged at 10 , 000 × g for 1 h at 4°C to remove smaller cellular debris . The pellets were discarded , and the resulting supernatant was centrifuged again as described above . The resulting supernatant was then centrifuged at 100 , 000 × g for 1 . 5 h at 4°C . The supernatants were then discarded , and the pellet was then resuspended in phosphate-buffered saline ( PBS ) ( pH 7 . 2 ) . Next , the sample was subject to size exclusion chromatography on a HighPrep 16/60 Sephacryl S-400 HR column ( GE Life Sciences ) pre-equilibrated with PBS ( pH 7 . 2 ) containing 0 . 01% NaN3 . All chromatographic separation steps were performed at room temperature on the high-performance liquid chromatography ÄKTA-Purifier 10 system ( Amersham Biosciences AB , Uppsala , Sweden ) . EVs were quantified using a combination of imaging flow cytometry , image confirmation , and fluorescence sensitivity in low-background samples , as previously described [39 , 40] . Prior to analysis , samples were stained with carboxyfluorescein succinimidyl ester ( CSFE ) and 1 , 1'-dioctadecyl-3 , 3 , 3' , 3'-tetramethylindocarbocyanine perchlorate ( Dil ) at 37°C for 90 min . Excessive dye particles were removed from stained vesicles using illustra microspin G-50 columns ( GE Healthcare ) . All samples were analyzed on the ImageStreamX Mk II flow cytometry system from Amnis Corporation ( Seattle , Washington , United States ) at ×60 magnification , with default low flow rate/high sensitivity using the INSPIRE software . The mean particle size of the vesicles dispersions were determined using a Zetasizer Nano-ZS ( Malvern Instruments , Malvern , United Kingdom ) . In order to obtain the optimum light scattering intensity , 10 μl of the vesicles suspension was added to 990 μl of PBS . All the measurements were carried out in triplicate at 25°C [41] . For SEM of biofilms , 40 μl of an inoculum of 108 cells/ml in RPMI–MOPS was added to the coverslips and incubated for 60 min at 37°C . 1 ml RPMI–MOPS was added to each well , and the plates were incubated at 37°C for 20 h . One ml fixative ( 4% formaldehyde , 1% glutaraldehyde in PBS ) was then added to each well prior to incubation at 4°C overnight . Coverslips were then washed with PBS prior to incubation for 30 min in 1% osmium tetroxide . Samples were then serially dehydrated in ethanol ( 30% to 100% ) . Critical point drying was used to completely dehydrate the samples prior to palladium-gold coating . Samples were imaged on a SEM LEO 1530 , with Adobe Photoshop 7 . 0 . 1 used for image compilation [27] . For cryoTEM , 3 μl of sample suspensions were pipetted onto a glow-discharged 200 mesh copper grid with a lacey carbon support film ( EMS , 1560 Industry Road , Hatfield , Pennsylvania , 19440 , US , #LC200-CU ) . Before sample application , the grid was mounted on a tweezer in the Vitrobot ( FEI , 5350 NE Dawson Creek Drive , Hillsboro , Oregon , 97124 , US , model MarkIII ) . In an automated sequence , excess fluid was blotted off , and the grid was plunge frozen in liquid ethane . Once frozen , the grid was mounted in a precooled cryo transfer sample holder ( Gatan , 780 Commonwealth Drive , Warrendale , Pennsylvania 15086 , US , model 626 ) and inserted into the TEM ( Hitachi Ltd . , 4026 , Kuji-cho , Hitachi-shi , Ibaraki , 319–12 , Japan , model HT7700 ) . The samples were observed at 120 kV acceleration voltage , and the sample temperature was kept at −170°C . Enzymatic “in liquid” digestion and mass spectrometric analysis was done at the Mass Spectrometry Facility , Biotechnology Center , University of Wisconsin–Madison . 200 μg of matrix proteins were extracted by precipitation with 15% TCA/60% acetone and then incubated at −20°C for 30 min . The matrix or vesicle preparation was centrifuged at 16 , 000 × g for 10 min , and the resulting pellets were washed twice with ice-cold acetone , followed by an ice-cold MeOH wash . Pelleted proteins were resolubilized and denatured in 10 μl of 8 M urea in 100 mM NH4HCO3 for 10 min , then diluted to 60 μl for tryptic digestion with the following reagents: 3 μl of 25 mM DTT , 4 . 5 μl of acetonitrile , 36 . 2 μl of 25 mM NH4HCO3 , 0 . 3 μl of 1M Tris-HCl , and 6 μl of 100 ng/μl Trypsin Gold solution in 25 mM NH4HCO3 ( Promega Co . , Madison , WI ) . Digestion was conducted in two stages , first overnight at 37°C , then additional 4 μl of trypsin solution were added and the mixture was incubated at 42°C for an additional 2 h . The reaction was terminated by acidification with 2 . 5% TFA to a final concentration of 0 . 3% and then centrifuged at 16 , 000 × g for 10 min . Trypsin-generated peptides were analyzed by nanoLC-MS/MS using the Agilent 1100 nanoflow system ( Agilent , Palo Alto , CA ) connected to a hybrid linear ion trap-orbitrap mass spectrometer ( LTQ-Orbitrap , Thermo Fisher Scientific , San Jose , CA ) equipped with a nanoelectrospray ion source . Capillary HPLC was performed using an in-house fabricated column with an integrated electrospray emitter , as described elsewhere [42] . Sample loading and desalting were achieved using a trapping column in line with the autosampler ( Zorbax 300SB-C18 , 5 μm , 5 × 0 . 3 mm , Agilent ) . The LTQ-Orbitrap was set to acquire MS/MS spectra in a data-dependent mode as follows: MS survey scans from 300 to 2 , 000 m/z were collected in profile mode with a resolving power of 100 , 000 . MS/MS spectra were collected on the five most abundant signals in each survey scan . Dynamic exclusion was employed to increase the dynamic range and maximize peptide identifications . Raw MS/MS data were searched against a concatenated C . albicans amino acid sequence database using an in-house MASCOT search engine [43] . Identified proteins were further annotated and filtered to 1 . 5% peptide and 0 . 1% protein false-discovery-rate with Scaffold Q+ version 3 . 0 ( Proteome Software Inc . , Portland , Oregon ) using the protein prophet algorithm [44] . The C . albicans vesicle and matrix proteomes were analyzed using the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [45 , 46] . Each protein predicted from the C . albicans genome assigned a KEGG Ontology ID ( KOID ) was obtained , and the specific pathway and superpathway membership information retained . This was then correlated with the experimental proteome data , and the number of proteins expressed within a given pathway was then determined . Tabulated proteins were presented as a percentage out of the total number of proteins predicted to belong to a given pathway from the C . albicans genome , as determined by KEGG . The visualization of relative quantities of biofilm proteins was also done using KEGG protein functional categorization . On the basis of this hierarchical classification scheme , Voronoi treemaps were constructed [47] . This approach divides screen space according to hierarchy levels in which the main functional categories determine screen sections on the first level , subsidiary categories on the second level , and so forth . The polygonic cells of the deepest level represented functionally classified proteins and were colored according to relative abundance of each protein that was determined based on total counts of corresponding trypsin-digested peptides . Lipids were extracted from the desalted lyophilized EV or matrix powder with a mixture of CHCl3/MeOH ( 2:1 , by vol ) containing 0 . 1 g/l BHT . The sample was vortexed , incubated in the dark for 2 h at room temperature , and then centrifuged . The separated layer of organic solvents was removed , and the pellet was washed with 2 ml of CHCl3/MeOH ( 2:1 , by vol ) and centrifuged . The collected lipid extracts were combined and dried under a stream of nitrogen . After drying , the sample was reconstituted in 0 . 5 ml of CHCl3/MeOH ( 2:1 , by vol . ) and subjected to TLC separation on 20 cm × 20 cm silica gel Si60 plates . Neutral lipids were separated in hexane/ethyl ether/AcOH ( 90:20:1 , by vol ) , which yielded triacylglycerols , sterol esters , free fatty acids , and a pool of immobile phospholipids . The latter group was scrapped off the plate , extracted from the silica gel , and subjected to another TLC separation in CHCl3/MeOH/AcOH/H2O ( 50:37 . 5:3 . 5:2 , by vol ) . This step yielded four classes of glycerolipids ( phosphatidylcholine , phosphatidylethanolamine , phosphatidylserine , and phosphatidylinositol ) and one class of sphingolipids ( sphingomyelins ) . Lipids were visualized under UV light after spraying plates evenly with a 0 . 2% solution of fluorescein in EtOH . All isolated lipid classes were scraped off their silica gel plates and re-extracted with CHCl3/MeOH ( 4:1 , by vol ) containing 0 . 1g/l BHT . Samples were vortexed , incubated overnight at room temperature , and then centrifuged in order to remove silica gel particles . 100 μl of 0 . 05 mg/ml pentadecanoic acid was added to each sample and the organic solvents were evaporated under nitrogen . Next , isolated lipids were subjected to methylation in the presence of 0 . 5 ml of 14% BF3 in MeOH . Vials containing the processed lipids were boiled . After cooling , the samples were mixed with 1 ml hexane and 0 . 5 ml H2O , vortexed , and centrifuged . The top hexane layer containing methyl ester derivatives was transferred to a new clean glass tube , dried under nitrogen , resuspended in 100 μl hexane , and transferred to GC vials . Fatty acid methyl esters were identified by gas chromatography using a Hewlett-Packard 5890 equipped with a capillary column coated with DB-225 ( 30-m length , 0 . 25-mm internal diameter , 0 . 25 μm; Agilent Technologies , Inc . , Wilmington , Delaware ) . Peaks were identified by a comparison of retention times with a set of authentic fatty acid standards provided by Supelco . The abundance of fatty acids was calculated from the relative peak areas [18] . Delipidated vesicle and matrix pellets containing carbohydrates and proteins were washed twice with acetone , dried under a stream of nitrogen , and reconstituted in 3 ml of 20 mM bis-Tris/HCl ( pH 6 . 5 ) loading buffer . Aliquots were chromatographically desalted on a HiPrep 26/10 Desalting column ( GE Healthcare Life Sciences , Uppsala , Sweden ) and then separated on an anion exchanger HiPrep 16/10 DEAE FF column ( GE Healthcare Life Sciences ) equilibrated with 20 mM bis-Tris/HCl ( pH 6 . 5 ) . Carbohydrate positive flow-through fractions were pooled together , lyophilized , resuspended in 15% acetonitrile in 150 mM ammonium bicarbonate , and applied to gel filtration on a HighPrep 16/60 Sephacryl S-300 HR column ( GE Healthcare ) . All chromatographic separation steps were performed at room temperature on the high-performance liquid chromatography ÄKTA-Purifier 10 system ( GE Healthcare Life Sciences ) . Sugars were converted to alditol acetate derivatives according to the procedure described previously [48] . Monosugar alditol derivatives were identified and quantified by GLC-FID on a Shimadzu GC-2010 system ( Shimadzu Co . , Kyoto , Japan ) using a ( 50% cyanopropylphenyl ) methylpolysiloxane column ( #007–225; 30 m × 0 . 25 mm with 0 . 25 μm film thickness , ) ( Quadrex Co . , Woodbridge , Connecticut ) . The samples were dissolved in 100 μl water and precipitated by addition of 900 μl EtOH . After centrifugation , the precipitate was dried , dissolved in D2O ( 99 . 9% D , Sigma-Aldrich ) , and lyophilized . The sample was then dissolved in 280 μl D2O ( 99 . 96% D , Cambridge Isotope Laboratories ) containing 0 . 5 μl acetone and placed into a 5-mm NMR tube with magnetic susceptibility plugs , matched to D2O ( Shigemi ) . NMR experiments were recorded at 65°C on an Agilent Inova-600 spectrometer equipped with a 5-mm cryoprobe . The 1-D proton experiment was acquired in 8 transients with water presaturation . The 2-D COSY experiment was collected with gradient enhancement in 400 increments of 8 transients each . The 2-D TOCSY and NOESY experiments were acquired with water presaturation in 128 increments of 16 transients each . Spinlock time in TOCSY was 80 ms , and mixing time in NOESY was 200 ms . The gradient-enhanced 1H-13C HSQC experiment with adiabatic 180° carbon pulses and multiplicity editing was acquired in 128 increments of 64 transients each , with a spectral width of 18091 Hz in the carbon dimension . The gradient-enhanced 1H-13C HMBC experiment with adiabatic 180° carbon pulses was acquired in 128 increments of 128 transients each , with a spectral width of 18 , 091 Hz in the carbon dimension . Chemical shifts were measured relative to DSS at 0 ppm in both proton and carbon scales by setting the chemical shift of internal acetone to 2 . 218 ppm ( proton ) and 33 . 0 ppm ( carbon ) . Chemical shifts assignments reported in S3 and S4 Tables were performed based on literature values reported elsewhere [49] . In vitro biofilm drug susceptibility to the antifungal fluconazole ( at a concentration of 1 , 000 μg/ml ) was assessed using a tetrazolium salt XTT reduction assay [16] . The percent reduction in biofilm growth compared to untreated controls is reported . Assays were performed in triplicate , and the significance of differences were assessed by one-way analysis of variance ( ANOVA ) with the posthoc Bonferroni and Holm methods [50] The CLSI M27 A3 broth microdilution susceptibility method was determine fluconazole activity against planktonic Candida strains . A visual turbidity endpoint was 24 h of grown was utilized . An external jugular vein rat catheter infection model was utilized for in vivo biofilm assessment [28 , 37 , 38] . Quantitative cultures of C . albicans after 24 h of in vivo growth was utilized to measure viable biofilm cell burden . For drug treatment experiments , fluconazole at a concentration of 250 μg/ml was instilled and dwelled in the catheter over a 24-h period . The post treatment viable burden of Candida biofilm on the catheter surface was compared to untreated control growth . Three replicates were performed for treatment and control conditions . Radiolabeled fluconazole was used to measure drug concentration in intact biofilms , matrix , and inside biofilm cells using a 6-well biofilm plate assay [37 , 51] . After 48 hrs of biofilm growth , plates were washed and then incubated with 8 . 48 x 105 cpm of 3H fluconazole ( Moravek Biochemicals; 50 μM , 0 . 001 mCi/mL in ethanol ) . Unlabeled fluconazole ( 20 μM ) in RPMI–MOPS was added for an additional 15-min incubation period and then washed to remove unbound fluconazole . Biofilm were collected with a spatula . Matrix and cells were isolated as described above . Intact biofilm , matrix , cell samples were added to a Tri-Carb 2100TR liquid scintillation analyzer after adding ScintiSafe 30% LSC mixture to each sample fraction . Three biologic and technical replicates performed . Values were compared to the reference strain using pairwise comparisons with ANOVA with the Holm-Sidak method . A 100-μl sample of purified biofilm EVs ( equivalent of 1000-ml biofilm culture ) was used to assess fluconazole sequestration . Vesicles were mixed with an equivalent volume of the radiolabeled drug and incubated for 1 h at 37°C . The sample was centrifuged for 10 min at 14 , 000 × g followed by collection of supernatant and washed three times with 1 ml of PBS . The collected vesicle pellet was resuspended in 200 μl of PBS and added to a Tri-Carb 2100TR liquid scintillation analyzer after adding ScintiSafe 30% LSC mixture . Three replicates were used . Biofilms were formed in the wells of 96-well microtiter plates , as described above . After a 5-h biofilm formation period , the biofilms were washed with PBS twice , and purified EVs at concentrations of 21804 ± 1711 EVs/ml were added . For treatment studies , after an additional hour of incubation , biofilm cultures were treated with fluconazole ( 1 , 000 μg/ml ) , followed by the drug treatment protocol described above . For biofilm matrix studies , the samples were incubated for an additional 24 hrs prior to either SEM imaging or matrix isolation for quantitative carbohydrate analysis . | Candida albicans—the most common fungal pathogen in humans—often grows as a biofilm , resulting in an infection that is difficult to treat . These adherent communities tolerate extraordinarily high concentrations of antifungals due in large part to the protective extracellular matrix . The present study identifies extracellular vesicles ( EVs ) that are distinct to biofilms . These EVs deliver the functional extracellular matrix and are essential for resistance to antifungals . Our findings not only reveal a coordinated mechanism by which the defining trait of the biofilm lifestyle arises but also identify a number of potential therapeutic targets . | [
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"albicans"
] | 2018 | Candida albicans biofilm–induced vesicles confer drug resistance through matrix biogenesis |
The diffusible signal factors ( DSFs ) are a family of quorum-sensing autoinducers ( AIs ) produced and detected by numerous gram-negative bacteria . The DSF family AIs are fatty acids , differing in their acyl chain length , branching , and substitution but having in common a cis-2 double bond that is required for their activity . In both human and plant pathogens , DSFs regulate diverse phenotypes , including virulence factor expression , antibiotic resistance , and biofilm dispersal . Despite their widespread relevance to both human health and agriculture , the molecular basis of DSF recognition by their cellular receptors remained a mystery . Here , we report the first structure–function studies of the DSF receptor regulation of pathogenicity factor R ( RpfR ) . We present the X-ray crystal structure of the RpfR DSF-binding domain in complex with the Burkholderia DSF ( BDSF ) , which to our knowledge is the first structure of a DSF receptor in complex with its AI . To begin to understand the mechanistic role of the BDSF–RpfR contacts observed in the biologically important complex , we have also determined the X-ray crystal structure of the RpfR DSF-binding domain in complex with the inactive , saturated isomer of BDSF , dodecanoic acid ( C12:0 ) . In addition to these ligand–receptor complex structures , we report the discovery of a previously overlooked RpfR domain and show that it binds to and negatively regulates the DSF synthase regulation of pathogenicity factor F ( RpfF ) . We have named this RpfR region the RpfF interaction ( FI ) domain , and we have determined its X-ray crystal structure alone and in complex with RpfF . These X-ray crystal structures , together with extensive complementary in vivo and in vitro functional studies , reveal the molecular basis of DSF recognition and the importance of the cis-2 double bond to DSF function . Finally , we show that throughout cellular growth , the production of BDSF by RpfF is post-translationally controlled by the RpfR N-terminal FI domain , affecting the cellular concentration of the bacterial second messenger bis- ( 3′-5′ ) -cyclic dimeric guanosine monophosphate ( c-di-GMP ) . Thus , in addition to describing the molecular basis for the binding and specificity of a DSF for its receptor , we describe a receptor–synthase interaction regulating bacterial quorum-sensing signaling and second messenger signal transduction .
Quorum sensing is a form of bacterial cell–cell communication that enables populations of bacteria to synchronize their gene expression in order to coordinate group behaviors such as bioluminescence , sporulation , genetic competence , biofilm formation , motility , and virulence factor expression ( reviewed in [1 , 2] ) . Quorum sensing is mediated by signaling molecules known as autoinducers ( AIs ) that bacteria secrete and detect . While gram-positive bacteria communicate using peptide AIs ( reviewed in [3 , 4] ) , gram-negative bacteria use a panoply of small molecule AIs , including the diffusible signal factors ( DSFs ) ( reviewed in [5] ) , which are the focus of the studies presented here . DSFs ( Fig 1A ) are a family of fatty acid AIs produced and detected by a wide range of gram-negative bacteria , including important pathogens [6] . DSFs regulate virulence factor expression , antibiotic resistance , and additional traits important for adaptation within biofilms and biofilm-associated infections [7–11] . While DSFs can differ in their acyl chain length , branching , and substitution , a common chemical feature shared among all DSFs is a cis-2 double bond , which is required for signaling activity ( reviewed in [12] ) . The commonality of the cis-2 double bond as well as the structural diversity in DSFs is evident when comparing the canonical DSF ( cis-11-methyl-2-dodecenoic acid ) , which was discovered in Xanthomonas campestris pv . campestris , with both the Burkholderia DSF ( BDSF ) ( cis-2-dodecenoic acid ) , which was first identified in Burkholderia cenocepacia , and the Pseudomonas DSF ( PDSF ) ( cis-2-decenoic acid ) , which was discovered in Pseudomonas aeruginosa ( Fig 1A ) [7 , 13 , 14] . The enzyme RpfF catalyzes the synthesis of DSF family signals through the dehydration of 3-hydroxyacyl thioesters attached to acyl carrier protein ( ACP ) , producing the cis-2 double bond ( Fig 1B ) . Subsequent hydrolysis of the cis-2 acyl thioester by RpfF releases the free fatty acid DSF AI from ACP [15 , 16] . While structural studies have examined DSF synthesis [17–19] , the structural basis of DSF–receptor interactions are unexplored . The DSF receptor RpfR is conserved in numerous gram-negative bacteria , including , among others , Escherichia coli , B . cenocepacia , Cronobacter turicensis , Serratia marcescens , Yersinia enterocolitica , and Enterobacter cloacae . RpfR was predicted to contain three domains , namely Per-Arnt-Sim ( PAS ) , diguanylate cyclase ( DGC ) , and phosphodiesterase ( PDE ) domains ( Fig 1C ) [20–22] . PAS domains are ligand-binding domains present in all kingdoms of life , and they are capable of detecting a multitude of signals , including small molecules , light , redox , as well as the conformational state of other proteins ( reviewed in [23 , 24] ) . Therefore , the RpfR PAS domain was predicted to bind DSF [22] . DGC domains , such as that found in RpfR , produce the bacterial second messenger bis- ( 3′-5′ ) -cyclic dimeric guanosine monophosphate ( c-di-GMP ) , whose increased concentration is associated with biofilm formation and sessile behavior . PDE domains hydrolyze c-di-GMP to linear 5′-phosphoguanylyl- ( 3′ , 5′ ) -guanosine ( pGpG ) , reducing the cellular concentration of c-di-GMP , which commonly triggers biofilm dispersal and virulence factor expression ( reviewed in [25] ) . BDSF binding to RpfR was previously shown to trigger its PDE activity , decreasing the intracellular concentration of c-di-GMP and favoring biofilm dispersal ( Fig 1D ) [20 , 22] . Here , we present a structure–function analysis of RpfR , revealing detailed mechanistic insight into DSF sensing . Additionally , we identified receptor-mediated control of DSF production via a direct interaction of RpfR with the DSF synthase RpfF . The foundation of this work are four X-ray crystal structures . The first two structures presented are those of the RpfR PAS domain in complex with BDSF or the saturated inactive isomer of BDSF , dodecanoic acid ( C12:0 ) . Structural comparison of these models along with in vivo functional analysis reveals the molecular basis for BDSF-binding specificity and the role of the DSF cis-2 double bond in signal perception . Additionally , we discovered that in contrast to prior predictions [22] , RpfR in fact contains an overlooked N-terminal domain that binds to RpfF , inhibiting DSF synthesis . Consistent with its function , we refer to the RpfR N-terminal domain as the RpfF interaction ( FI ) domain . To explore the mechanism of RpfR-mediated RpfF inhibition , we determined the X-ray crystal structures of the RpfR FI domain alone and in complex with RpfF . These crystal structures , along with extensive in vivo and in vitro studies , reveal the mechanistic basis of this regulation and its contribution to restraining BDSF synthesis and elevating the intracellular concentration of c-di-GMP . Since DSF signaling commonly regulates cellular behaviors , including biofilm formation , biofilm dispersal , swarming motility , extracellular protease production , antibiotic resistance , and other virulence-associated phenotypes in important human and plant pathogens [9 , 20 , 26–32] , the mechanistic insight into DSF sensing and synthesis presented here set the stage for developing inhibitors important for human health and agriculture .
To gain insight into the molecular recognition of BDSF by RpfR , we crystallized and determined the structure of the C . turicensis RpfR PAS domain ( Fig 2A , S1 Table ) . Without adding fatty acid to the crystallization experiment , we observed prominent electron density in the PAS domain core that was consistent with a 12-carbon fatty acid ligand ( Fig 2A–2C ) . Intriguingly , even when an excess of BDSF was included during crystallization , the electron density was consistent with a fatty acid that did not contain a cis-2 double bond ( Fig 2C ) . These data suggested that RpfRCt ( PAS ) copurified with a tightly bound fatty acid likely originating from the E . coli overexpression host . Indeed , using liquid chromatography–mass spectrometry ( LC-MS ) , we determined that the ligand is the saturated isomer of BDSF , C12:0 ( S1 Fig ) , which E . coli is known to produce endogenously [33] . Thus , we built and refined the 1 . 5 Å resolution X-ray crystal structure of RpfRCt ( PAS ) –C12:0 ( Fig 2A–2C ) . While C12:0 is an inactive isomer of BDSF , the RpfRCt ( PAS ) –C12:0 structure provided the first insight into how fatty acids interact with RpfR and , as shown below , proved to be important for comparative analysis . In the RpfRCt ( PAS ) –C12:0 structure , the C12:0 carboxylic acid group forms multiple hydrogen bonds with a set of conserved hydrophilic residues ( S169 , N172 , Y183 , and R187 ) at one end of the ligand-binding pocket ( Fig 2B ) . At the other end of the pocket , the C12:0 hydrophobic acyl tail is surrounded by conserved hydrophobic residues ( Fig 2A and 2B , S2A Fig ) . While the RpfRCt ( PAS ) –C12:0 structure provided insight into RpfR fatty acid binding , a mechanistic understanding of how RpfR recognizes BDSF demanded determination of the bona fide RpfRCt ( PAS ) –BDSF structure . BDSF was previously demonstrated to trigger RpfRCt phosphodiesterase activity [20] . To obtain RpfRCt ( PAS ) bound to the functionally active ligand BDSF , rather than the inactive ligand C12:0 , we overexpressed and purified the RpfRCt ( PAS ) domain from E . coli engineered to express BDSF . It is notable that while E . coli contains a highly conserved rpfR homolog named the gene modulating RNase II ( gmr ) , it lacks a DSF synthase and , to our knowledge , does not produce a DSF AI [21 , 34] . We speculate , however , that E . coli Gmr PDE activity could be regulated by C12:0 . Regardless , E . coli was previously demonstrated to synthesize BDSF when transformed with an expression plasmid containing rpfFBc [15 , 30] . Therefore , we purified RpfRCt ( PAS ) from E . coli coexpressing RpfFBc . The purified RpfRCt ( PAS ) was then denatured and LC-MS used to identify the released ligand ( S3 Fig ) . Indeed , the bound ligand was BDSF , confirming that we had purified the RpfRCt ( PAS ) –BDSF complex . The RpfRCt ( PAS ) –BDSF complex was crystallized and its structure determined to a resolution of 2 . 3 Å ( Fig 2D–2F , S1 Table ) . Comparison of the RpfRCt ( PAS ) –BDSF and RpfRCt ( PAS ) –C12:0 structures reveals that the ligands adopt different conformations , resulting from the absence or presence of the cis-2 double bond in C12:0 or BDSF , respectively . Furthermore , while RpfRCt arginine ( Arg ) 187 makes a single H-bond to C12:0 , it adopts a different rotameric configuration in the presence of BDSF , forming an additional H-bond between its δ nitrogen and the BDSF carboxylic acid ( Fig 2B and 2E ) . Based on the measured distances and atom types ( Fig 2B and 2E ) , the position of BDSF in the RpfRCt ( PAS ) -binding pocket appears to be influenced by an interaction between BDSF and the conserved residue asparagine ( Asn ) 202 ( Fig 2E , S2A Fig and S4 Fig ) . Specifically , we propose that the Asn202 side chain amide nitrogen interacts with the electron deficient Cβ ( C3 ) of BDSF . Below , we explore the physiological importance of the RpfRCt ( PAS ) –BDSF interactions observed in the crystal structure . Relative to wild-type B . cenocepacia , strains with RpfR proteins containing mutations predicted to disrupt the binding of BDSF to RpfRBc ( PAS ) should be less sensitive to BDSF , exhibit lower PDE activity , display elevated levels of c-di-GMP , and have increased competitive fitness in biofilms due to elevated biofilm production . We engineered mutations RpfRBc–S168A , –N171A , –R186A , and–N201A ( corresponding to the above-described and conserved RpfRCt BDSF-interacting residues S169 , N172 , R187 , and N202 [S2A Fig] ) in the chromosomal copy of rpfR and competed them 1:1 with wild-type under a daily cycle of biofilm formation , dispersal , and reattachment [10 , 35] . Consistent with the interactions observed in the RpfRCt ( PAS ) –BDSF crystal structure , each mutation produced large and significant fitness advantages , with selective coefficients ( s ) ranging from 0 . 58 to 1 . 17 ( Fig 2G ) . Furthermore , each of these mutations resulted in a significant increase in cellular c-di-GMP relative to the wild-type strain ( Fig 2H ) . While it is possible that the site-directed mutations affected RpfR stability and , in turn , the ability of RpfR to respond to BDSF , we found that purified full-length wild-type RpfRBc , RpfRBc–S168A , –N171A , –R186A , and–N201A were comparably soluble ( S5 Fig ) . Finally , in line with the fact that the RpfRBc ( PAS ) BDSF-binding mutants displayed increased competitive fitness in the in vitro biofilm life cycle assay and elevated levels of c-di-GMP , we note that RpfRBc ( PAS ) is subject to positive selection under conditions favoring biofilm growth , such as in a cystic fibrosis patient for which increased biofilm production proves advantageous [11] . Previous studies identified three RpfR domains: PAS , DGC ( GGDEF ) , and PDE ( EAL ) [20–22] ( Fig 1C ) . We observed that the undescribed region of RpfR ( residues 1–117 ) was highly conserved among all RpfR homologues ( S2B Fig ) . This led us to hypothesize the presence of a new domain located N-terminal to the BDSF-binding PAS domain . Indeed , we found that a construct containing the first 95 residues of RpfRCt ( RpfRCt[1–95] ) was soluble and well folded , as determined by size exclusion chromatography ( Fig 3A ) . As described below , RpfRCt ( 1–95 ) was amenable to crystallographic analysis . We determined the X-ray crystal structure of the RpfRCt ( 1–95 ) to a resolution of 1 . 2 Å using the single-wavelength anomalous dispersion ( SAD ) method ( Fig 3B , S1 Table ) . RpfRCt ( 1–95 ) adopts a Profilin-like fold consisting of an N-terminal α-helix and a central six-stranded antiparallel β-sheet with a single α-helix connecting β3 to β4 ( Fig 3B , S2B Fig and S6A Fig ) [36 , 37] . Distance-matrix alignment ( DALI ) and PDBeFold searches of the Protein Data Bank ( PDB ) show the closest RpfRCt ( 1–95 ) structural homologues to be PAS , Ca2+channels-chemotaxis receptors ( Cache ) , and cyclic GMP-specific phosphodiesterase-adenylyl cyclase-FhlA ( GAF ) domains; however , canonical PAS domains contain five-stranded β-sheets ( S6B Fig ) [23] , and Cache domains are periplasmic domain proteins that contain an additional N-terminal α-helix that extends through the membrane [38] . Like RpfRCt ( 1–95 ) , GAF domains contain six-stranded antiparallel β-sheets [23 , 39]; however , unlike GAF domain proteins , RpfRCt ( 1–95 ) does not possess a pair of interacting α-helices below its β-sheet ( S6C Fig ) . Consistent with the fact that RpfRCt ( 1–95 ) is neither a PAS , Cache , or GAF domain , protein BLAST ( BLASTP ) searches using the RpfRCt ( 1–95 ) and RpfRBc ( 1–94 ) amino acid sequences return neither PAS , Cache , nor GAF domain proteins [40] . Based on the above structural and sequence analysis , we conclude that while the RpfR N-terminal domain is structurally similar to PAS , Cache , and GAF domains , it is a new domain with a Profilin-like fold . As detailed below , this RpfR domain binds to and negatively regulates RpfF; thus , we refer to it as the RpfF interaction ( FI ) domain . Initial evidence suggesting that RpfR ( FI ) and RpfF interact came from studies in which an RpfRBc construct containing both the FI and PAS domains ( RpfRBc[FI–PAS] ) and RpfFBc were coexpressed in E . coli to obtain RpfRBc ( FI–PAS ) bound to BDSF . As discussed above , RpfFBc was employed in these experiments because it was previously shown to produce BDSF when overexpressed in E . coli [15 , 30] . During our experiments to obtain BDSF-bound RpfRBc ( FI–PAS ) , RpfRBc ( FI–PAS ) containing an N-terminal hexahistidine ( His6 ) affinity tag copurified with nontagged RpfFBc ( S7 Fig ) . As this interaction was not observed when His6-tagged RpfRCt ( PAS ) was purified following coexpression with RpfFBc , we hypothesized that RpfRBc/Ct ( FI ) binds to RpfFBc . To test this hypothesis , we coexpressed RpfFBc and RpfRCt ( FI ) and purified the RpfFBc–RpfRCt ( FI ) complex ( Fig 4A ) . Based on the fact that RpfR ( FI ) and RpfF form a complex , we hypothesized that RpfR ( FI ) regulates RpfF enzymatic activity . To test this hypothesis , we generated E . coli 4′-phosphopantetheinyl ACP ( holo-ACPEc ) and charged it with C12:0 . C12:0-charged ACPEc ( C12:0–ACPEc ) is a substrate for the analysis of in vitro RpfF thioesterase activity [15 , 17] , which we then measured in either the absence or presence of RpfRBc ( FI ) ( Fig 4B ) . In the absence of RpfRBc ( FI ) , C12:0–ACPEc was readily converted by RpfFBc to holo-ACPEc . In the presence of RpfRBc ( FI ) , conversion of C12:0–ACPEc substrate by RpfFBc was significantly reduced ( Fig 4B ) . These results indicate that RpfR ( FI ) Bc inhibits RpfFBc thioesterase activity . To understand how RpfR ( FI ) inhibits RpfF thioesterase activity , we determined the RpfFBc–RpfRCt ( FI ) X-ray crystal structure to a resolution 2 . 0 Å ( Fig 5 , S1 Table ) . RpfFBc–RpfRCt ( FI ) is a heterohexamer consisting of three RpfRCt ( FI ) and RpfFBc protomers . The heterohexamer is generated by 3-fold crystallographic symmetry of the asymmetric unit containing RpfFBc–RpfRCt ( FI ) . Each RpfRCt ( FI ) protomer simultaneously interacts with two RpfFBc protomers near their homodimerization interfaces ( Fig 5A–5C ) . This interaction places RpfR ( FI ) Ct in close proximity to the RpfFBc substrate tunnel entrance ( Fig 5C and 5D ) . It is also worth noting that the RpfFBc–RpfRCt ( FI ) interfacial residues are conserved ( S2B and S8 Figs ) , and this interaction is likely common in bacteria encoding both proteins . When comparing the structure of RpfFBc alone ( PDB:5FUS ) [17] with the structure of RpfFBc–RpfRCt ( FI ) , perhaps the most surprising observation is that RpfFBc–RpfRCt ( FI ) contains no bound fatty acid ( S9A Fig ) . In the previously determined crystal structure of RpfFBc , C12:0 originating from the E . coli expression system was identified as a ligand in the RpfFBc substrate tunnel [17] . Attempts to remove C12:0 prior to biochemical and structural studies were unsuccessful , suggesting that C12:0 may be tightly bound [17] . Consistent with the absence of bound fatty acid in RpfFBc–RpfRCt ( FI ) , structural alignment of RpfFBc–RpfRCt ( FI ) with RpfFBc shows that in the complex , phenylalanine ( Phe ) residues 44 and 88 have adopted a conformation in which they would sterically clash with bound fatty acid if it were present ( S9B Fig ) . Finally , superposing the structures of RpfRCt ( FI ) alone with the structure of RpfRCt ( FI ) in complex with RpfFBc ( Fig 5B ) reveals that RpfRCt ( FI ) undergoes minor conformational changes primarily at the RpfFBc binding surface . The most significant of these changes occur in RpfRCt ( FI ) in which the N-terminus of strand β3 extends by one residue , the β2–β3 loop shifts to form contacts with two molecules of RpfFBc near their homodimerization interface , and the β4–β5 loop becomes buried in the RpfFBc interface ( Fig 5B ) . Based on the proximity of RpfR ( FI ) Ct to the RpfFBc substrate tunnel and its ability to inhibit RpfF thioesterase activity , we propose that RpfRCt ( FI ) functions to sterically block acyl-ACP substrates from entering the RpfF active site . To measure the regulatory effect that RpfR has on RpfF BDSF synthesis in vivo , we employed a B . cenocepacia BDSF bioassay and mass spectroscopy to monitor the extracellular accumulation of BDSF in wild-type and mutant strains . More specifically , we compared the extracellular concentration of BDSF in cultures of B . cenocepacia strains that were either wild-type ( strain HI2424 ) , had the entire rpfR gene deleted , or contained an in-frame deletion of the rpfR FI domain ( Fig 6A and 6B ) . The rpfR and rpfR FI domain deletion strains had significantly increased extracellular levels of BDSF compared to the wild-type strain . Consistent with these in vivo BDSF bioassay results and the above biochemical data , the B . cenocepacia rpfR deletion strain produced elevated levels of c-di-GMP relative to the wild-type strain under biofilm growth conditions , likely resulting from the deletion of the RpfR PDE domain ( Fig 6C ) . Moreover , the RpfR FI domain deletion strain displayed significantly reduced levels of c-di-GMP , consistent with the elevated levels of BDSF stimulating RpfR PDE activity .
The defining feature of the DSF family of AIs that distinguishes them from other fatty acids is their cis-2 double bond ( Fig 1A ) [12] . The cis-2 double bond dramatically affects DSF receptor–binding affinity and biological activity . BDSF was shown to tightly bind RpfRBc ( Kd = 877 nM ) , while C12:0 ( Kd = 800 μM ) and trans-2 dodecenoic acid ( Kd = 150 μM ) were found to weakly interact with the receptor [22] . Consistent with these results , BDSF was active in a B . cenocepacia BDSF bioassay , while C12:0 and trans-2 dodecenoic acid were inactive [41] . Despite great interest in DSF-signaling systems , the mechanism of molecular recognition employed by DSF receptors such as RpfR to distinguish DSF AIs from other cellular fatty acids , including the trans-2 and saturated isomers of DSF AIs , was unknown . As detailed below , we propose that the BDSF cis-2 double bond establishes RpfRCt-binding specificity and affinity by enabling unique ligand–receptor contacts and , in contrast to more flexible fatty acids such as C12:0 , by paying a lower entropic cost upon receptor binding . Structural comparison of RpfRCt ( PAS ) –C12:0 and RpfRCt ( PAS ) –BDSF reveals mostly subtle conformational changes localized to the RpfRCt ( PAS ) domain ligand-binding side chains ( Fig 2B and 2E ) . One conformational difference is RpfRCt–R187 , which makes an additional H-bond to the BDSF carboxylic acid than it makes to the C12:0 carboxylic acid ( Fig 2B and 2E ) . Interestingly , RpfRCt–R187 can mediate this additional H-bond because it adopts a different rotameric configuration in the BDSF-bound structure . Much of the RpfRCt–R187 side chain is solvent exposed , and we speculate that it could play a role in regulating the activity of the receptor C-terminal enzymatic PDE domain upon BDSF binding . Based on the measured distances and atom types ( Fig 2B and 2E , S4 Fig ) , BDSF appears to be interacting with the conserved RpfRCt amino acid Asn202 . As an α , β-unsaturated carboxylic acid , BDSF contains an electron deficient Cβ ( C3 ) . We propose that the more electron rich N202 amide nitrogen interacts with the electron deficient Cβ of BDSF . This interaction cannot occur for the fully saturated C12:0 and would be significantly weaker for trans-2 dodecenonic acid because its Cβ would be suboptimally positioned further away from N202 . Additionally , in some RpfR proteins , there is a tyrosine corresponding to RpfRCt–Y183 , whose hydroxyl interacts with the N202 side chain amide N-H ( Fig 2E ) . This interaction could further increase the electron density on the N202 amide nitrogen , strengthening its interaction with Cβ ( C3 ) of BDSF . Finally , it is important to note that due to the presence of the cis-2 or trans-2 double bond in BDSF and trans-2 dodecenoic acid , respectively , they are more rigid than their saturated isomer C12:0 . Theoretically , there is less entropy lost upon receptor binding to BDSF or trans-2 dodecenoic acid than upon binding to C12:0 . Thus , we speculate that in addition to the specific receptor contacts mediated by the BDSF cis-2 double bond , it could contribute to receptor affinity and specificity by lowering the entropic penalty paid in comparison to saturated fatty acids . We have discovered a previously unidentified PAS-like domain at the RpfR N-terminus and demonstrated that it binds directly to RpfF , inhibiting BDSF synthesis in vitro and in vivo ( Fig 4B; Fig 6A and 6B ) , ultimately affecting the cellular concentration of c-di-GMP ( Fig 6C ) . Ongoing studies in our labs are examining the molecular basis of this regulation . Due to the proximity of the RpfR FI domain to the RpfF substrate tunnel entrance ( Fig 5C and 5D ) , in all likelihood , RpfR sterically blocks acyl-ACP binding to RpfF and acyl-ACP substrate access to the RpfF active site . While we have shown that RpfR ( FI ) interacts with RpfF—tuning or restraining the amount of BDSF produced and secreted—we believe that RpfR ( FI ) has also evolved to limit the amount of general acyl-ACP substrate cleavage . It was previously demonstrated that RpfF cleaves a broad range of acyl-ACP substrates , producing free fatty acids , which is energetically wasteful , as many of these would not be DSF AI compounds or serve any other known physiological role [15 , 17 , 42 , 43] . Many bacteria that express RpfF also contain an enzyme , regulation of pathogenicity factor B ( RpfB ) , that salvages free fatty acids by ligating them to coenzyme A ( CoA ) , generating substrates for beta oxidation [43] . RpfB was shown to be important for counteracting RpfF substrate promiscuity , as rpfB mutants displayed RpfF-dependent growth defects [43] . It is important to note that bacteria encoding RpfR do not contain RpfB , and how these bacteria might compensate for RpfF substrate cleavage promiscuity was unknown . We propose that an important role for RpfR ( FI ) is to compensate for the lack of RpfB in these bacteria by tightly regulating RpfF , governing its cleavage of acyl-ACP substrates . Based on the existing data , we propose the following model for RpfR function ( Fig 7 ) . At low-cell density and below a critical concentration of BDSF , the RpfR c-di-GMP PDE has minimal activity [22] , and biofilms can form because c-di-GMP levels are elevated . Why the RpfR PDE domain is minimally active in the absence of BDSF is unknown , but we hypothesize that the RpfR PAS domain may directly interact with the PDE domain inhibiting its activity . Throughout cellular growth , RpfR directly regulates RpfF processing of acyl-ACP substrates . More specifically , the newly discovered RpfR FI domain binds RpfF at its acyl-ACP–binding site , limiting its promiscuous cleavage of acyl-ACP substrates . Ultimately , the BDSF concentration reaches a critical concentration in which its binding to the RpfR PAS domain activates RpfR c-di-GMP PDE activity . This activation converts c-di-GMP to pGpG , triggering biofilm dispersal . It is important to note that PDE domains are typically allosterically activated upon dimerization [44–47] . We propose that BDSF binding to the RpfR PAS domain activates RpfR PDE activity by triggering RpfR dimerization or the conformational rearrangement of catalytically inactive ( autoinhibited ) RpfR dimers . In fact , a similar model was proposed for the regulator of biofilm dispersal of Pseudomonas aeruginosa ( RbdA ) [48] . Finally , what role , if any , BDSF binding to RpfR ( PAS ) plays in controlling the RpfR ( FI ) –RpfF association is unknown; however , if BDSF binding to RpfR ( PAS ) regulates RpfR ( FI ) –RpfF association , in turn controlling RpfF activity , then BDSF , RpfR , and RpfF comprise a feedback loop regulating BDSF synthesis . Determining whether such a feedback loop exists and elucidating the structural basis of its function is necessary if we are to understand the regulatory controls modulating BDSF synthesis and cell–cell communication . Finally , we note that PAS and PAS-like domains structurally similar to the RpfR FI domain are common components of histidine kinases as well as other bacterial signal transduction proteins [23] . It will be interesting to determine whether some of these domains , like the FI domain , function to directly regulate the activity of a target enzyme . We propose that these interactions , like the physiologically important interactions identified here between RpfR and the AI BDSF as well as between RpfR and the BDSF synthase RpfF , could be targeted for the development of signaling agonists or antagonists and could serve as therapeutics modulating critical bacterial developmental processes including biofilm formation , biofilm dispersal , and virulence .
Obtaining holo-ACPEc ( ACPEc with the 4′-phosphopantetheinyl prosthetic group on serine 36 ) requires ACP to be coexpressed alongside the E . coli Acyl Carrier Protein Synthase ( AcpSEc ) . To coexpress ACPEc and AcpSEc , we engineered a construct similar to the one previously described in [63] , by cloning acpPEc and acpSEc into pQlink-H and pQlink-N , respectively [64] . pQlink-H was chosen in order to facilitate ACPEc purification using a TEV protease cleavable His7-tag . Both inserts were amplified from E . coli MG1655 genomic DNA using Phusion High-Fidelity DNA Polymerase . The acpPEc insert was generated using the oligonucleotide pair primer 11 and primer 12 . The acpSEc insert was amplified using the oligonucleotide pair primer 13 and primer 14 . Amplified and gel purified acpPEc was inserted into BamHI and NotI linearized pQlink-H using the Gibson Assembly to generate plasmid pAcpPEc-His7 . Likewise , amplified and gel purified acpSEc was inserted into BamHI and NotI linearized pQlink-N , generating pAcpSEc . A single-expression construct for both proteins was generated by digesting pAcpSEc with PacI and pAcpPEc-His7 with SwaI . Following heat inactivation of the restriction digests at 65 °C for 20 min , both reactions were incubated with LIC-qualified T4 DNA polymerase ( Novagen ) in the presence of either dCTP ( pAcpSEc digest ) or dGTP ( pAcpPEc-His7 digest ) at 25 °C for 30 min . The T4-treated DNA fragments were then combined in a 1:1 ratio and annealed at 65 °C for five min , followed by a 2 min incubation on ice and a 15 min incubation at room temperature . Following the addition of EDTA to a final concentration of 1 . 25 mM , the annealing reactions were transformed into Lucigen SOLO hypercompetent cells ( Lucigen ) , generating pHis7-AcpPEc/N-AcpSEc . Purification of holo-ACPEc was accomplished using several modified protocols [62 , 63 , 65] . pHis7-AcpPEc/N-AcpSEc was transformed into C41 ( DE3 ) chemically competent E . coli cells and grown up in LB medium containing 100 μM ampicillin . Cells were grown to OD600 = 0 . 6 at 37 °C and 220 RPM and induced with 1 mM IPTG . Following induction , cells were grown for an additional 22 h at 18 °C and 200 RPM and then pelleted at 7 , 000 × g for 15 min . The pellet was resuspended in lysis buffer O ( 500 mM NaCl , 50 mM Tris [pH 8 . 8] , 10 mM MgCl2 , 5 mM β-mercaptoethanol , 20 mM imidazole , and 10 μg/mL DNAse ) . Cells were lysed by two passages through a cell disruptor and clarified at 35 , 000 × g for 40 min at 4 °C . Clarified lysate was incubated with His60 Superflow resin equilibrated in buffer O for 1 . 5 h with gentle rocking at 4 °C . The resin was washed once with buffer O and a second time with buffer O containing 40 mM imidazole . His7-ACPEc copurified with AcpSEc following elution with increasing concentrations of imidazole in buffer O . Fractional purity was analyzed with SDS-PAGE . The purest fractions were combined with His6-TEV protease . EDTA was added to a final concentration of 50 mM , and the reaction was incubated at 4 °C overnight . The overnight reaction was then dialyzed against buffer P ( 50 mM NaCl , 25 mM MOPS [pH 7 . 1] , and 1mM β-mercaptoethanol ) to remove imidazole . Dialyzed fractions were incubated with fresh His60 Superflow resin equilibrated in buffer P and allowed to rock at 4 °C for 2 h to remove the His7-tag and His6-TEV protease . The flow-through from the resin was loaded onto a Q Sepherase Fast Flow Column ( Pharmacia ) equilibrated in buffer P . Holo-ACPEc was successfully separate from AcpSEc using an increasing gradient of KCl in buffer P . The purest holo-ACPEc fractions were combined and concentrated using a 3-kDa cutoff filter and loaded onto a Superdex 200 16/70 column equilibrated in buffer Q ( 100 mM NaCl , 20 mM Tris [pH 7 . 5] , and 0 . 87 mM TCEP ) . Peak fractions were analyzed using SDS-PAGE and concentrated to 444 . 4 μM ( extinction coefficient = 1 , 800 M−1 cm−1 [Sigma-Aldrich] ) using a 3-kDa Vivaspin concentrator . Optimal charging reaction conditions were based on those previously reported [15 , 16 , 63] . C12:0–ACPEc was charged with substrate by incubating 142 μM holo-ACPEc with 2 . 5 mM C12:0 , 10 mM ATP , 2 μM AasS , in ACP-charging buffer R ( 100 mM Tris [pH 7 . 8] , 10 mM MgCl2 , and 1 mM TCEP ) for 4 h at 37 °C . Following charging , the reaction was precipitated by the addition of two equivalent reaction volumes of acetone and incubated at −20 °C overnight . The precipitated protein was pelleted at 20 , 000 × g for 30 min . The supernatant was removed , and the pellet was washed two times with two additional reaction volumes of acetone . The pellet was then air dried and dissolved in 20 mM Tris ( pH 7 . 5 ) to a final concentration of 111 μM charged-ACPEc . The thioesterase reaction conditions were chosen based on previously published methodologies [15 , 16] . RpfF thioesterase activity was measured using a 10-μL reaction consisting of 78 μM C12:0–ACPEc substrate , 0 . 64 μM RpfFBc ( or control buffer N ) , and either 6 . 4 μM RpfRBc ( FI ) , 1 . 28 μM RpfRBc ( FI ) , or control buffer D in the thioesterase assay buffer ( 100 mM Tris [pH 7 . 5] ) . This reaction was incubated at 37 °C for 30 min and then heat inactivated at 95 °C for 2 min . Reactions were analyzed with a conformation-sensitive nondenaturing gel containing 20% polyacrylamide , 375 mM Tris ( pH 8 . 8 ) , and 2 . 5 M urea . Gels were stained with Coomassie Brilliant Blue , and band intensities were measured using a LI-COR Odyssey CLx Imager System ( LI-COR Biosciences ) and quantified using Image Studio version 3 . 1 ( LI-COR Biosciences ) . Isogenic mutations were created using methods described by Fazli and colleagues [66] . For single-gene deletions , approximately 1 , 000 bp upstream and downstream of the target gene were amplified using high-fidelity PCR and joined using single overlap extension PCR , using the following conditions: 98 °C for 2 min; 3 cycles of 98 °C for 15 s , 64 °C for 30 s , 72 °C for 1 min; 72 °C for 1 min . After the addition of standard attB1 and attB2 primers , a second round of PCR was performed , using the following conditions: 98 °C for 2 min; 27 cycles of 98 °C for 15 s , 64 °C for 30 s , 72 °C for 2 min; 72 °C for 7 min . This approximately 2 , 000 bp fragment was then gel purified and inserted into a pDONPREX18Tp-SceI-PheS plasmid containing a trimethoprim ( Tp ) resistance cassette using Gateway cloning . For single-nucleotide mutations , the target gene was cloned into the same plasmid and site-directed mutagenesis was used to create the intended point mutation . The resulting gene-replacement vectors were electroporated into competent DH5α E . coli and introduced by conjugation into B . cenocepacia via triparental mating . Matings were performed by combining 200 μL of overnight cultures of the DH5α strain containing the gene replacement vector , 200 μL of S . 17 E . coli containing the conjugation helper vector pEVS104 , and 50 μL of the recipient B . cenocepacia strain into a cell pellet , resuspending the pellet in 30 μL of 10 mM MgSO4 and spotting onto tryptic soy agar ( TSA ) plates . The cell mixture was scraped from the plate after 24 h at 37 °C using an inoculating loop , resuspended in 1 mL of PBS , and plated at different dilutions onto Vogel–Bonner minimal medium ( VBMM ) agar containing 100 μg/mL Tp . Four Tp-resistant colonies were selected and grown first in tryptic soy broth , followed by VBMM broth containing 0 . 1% chlorophenylalanine before being plated onto four TSA plates . 100 colonies from each plate were picked using pipette tips and patched onto both TSA and TSA-Tp100 . Four candidates for each mutation were selected by sensitivity to Tp and sequenced using whole genome sequencing according to Baym and colleagues [67] on an Illumina NextSeq 500 to a minimum average of 30x coverage . The correctly made mutants were confirmed to be otherwise isogenic using the variant calling program Breseq v . 0 . 31 [68] . Freezer stocks were revived overnight and then grown for 24 h in M9 minimal medium + 3% galactose ( GMM ) at 37 °C . Equal volumes of each competitor were added to 3% GMM containing three 7 mm polystyrene beads , and a planktonic sample of that mixture was serially diluted and plated on half-strength T-soy X-gal plates to enumerate starting CFU/mL . Samples taken from a bead at subsequent 12-h time intervals over 48 total h were serially diluted and plated in half-strength T-soy X-gal plates to enumerate CFU/bead . Fitness was calculated as the difference in Malthusian parameters between the mutant and wild type ancestor in units of time−1 , as follows: ln ( Nm1/Nm0 ) − ln ( NWT1/NWT0 ) , in which N is cell number and m is mutant and WT is wild type at time 0 or 1 ( e . g . , Nm1 is the number of mutant cells at time 1 ) [69] . Four independent cultures of each strain ( WT , ΔrpfR , ΔrpfF , and ΔFI ) were inoculated into 2 mL Luria broth ( LB ) in test tubes from frozen stocks and grown at 35 °C , 200 RPM overnight ( approximately 14 h ) . The next day , cultures were diluted 1:500 into 10 mL fresh LB in 50 mL flasks in quadruplicate and grown at 35 °C , 200 RPM for 12 h . After growth , 1 mL of culture was removed from each flask and placed into 2 mL tubes and 20 μL of culture was used to measure cell density by dilution plating . The cultures were centrifuged at max speed ( 15 , 000 × g ) at room temperature for 1 min . Supernatants were removed and placed into new 2-mL tubes , and the solutions were acidified using 12 M HCl until the pH was less than 4 . 0 . Three hundred μL of ethyl acetate was added to each sample , and the tubes were vortexed for 5 min . The samples were then centrifuged for 10 min at 8 , 000 × g at room temperature to separate organic and aqueous phases . The top ( organic ) phase was removed and placed into new 1 . 5-mL tubes . The resulting organic solution was evaporated using a heated vacuum centrifuge , and the dried pellet was resuspended in 100 μL 1:1 methanol/water , placed in mass spectrometry vials , and analyzed by liquid chromatography-mass spectrometry on a Xevo TQ-D Triple Quadruple mass spectrometer ( Waters ) coupled with an UPLC system ( Acquity , model BSM ) . Liquid chromatography separation was carried out on an Acquity UPLC BEH reverse-phase column ( 1 . 7 μm , 2 . 1 mm × 150 mm , Waters ) . Solvent A was 10 mM ammonium formate in water . Solvent B was 100% methanol . 10 μL of sample was autoinjected into the column and subjected to solvent A and B gradients as follows: t = 0 minutes , 10% solvent B; t = 4 minutes , 98% solvent B; t = 7 . 01 minutes , 10% solvent B at a flow rate of . 200 mL/min for a total of 10 min per sample . Under these conditions , BDSF had a retention time of 5 . 6 min . BDSF was detected in selected reaction monitoring ( SRM ) in negative ionization mode following the m/z 198 → 197 at 30 eV . The signal for BDSF in biological samples was defined as the observed peak area on the chromatography trace determined by the MassLynx software ( Waters ) . Chemically synthesized BDSF ( Adipogen , San Diego , CA ) was used to determine retention time and optimize fragmentation patterns . Freezer stocks were revived overnight in T-soy broth and then grown for 24 h in M9 minimal medium + 3% galactose ( GMM ) at 37 °C . 1 . 25 mL of each strain was added to 125 mL 3% GMM in a flask containing 100 7-mm polystyrene beads and incubated at 100 rpm at 37 °C for 12 h . While harvesting , flasks were incubated on ice for 10 min . For the biofilm phase , the planktonic culture was discarded , and the beads were washed with 60 mL of cold PBS . These were then divided into four 50 mL centrifuge tubes containing 20 mL of cold PBS each . Each tube was vortexed for 30 s to remove the attached cells , and the PBS from all four sets was combined . The samples were then serially diluted and plated in half-strength T-soy X-gal plates to enumerate CFU/flask and then centrifuged at max speed for 15 min at 25 °C . Pellets were then resuspended in 500 μL of ice-cold extraction buffer ( methanol:acetonitrile:dH2O 40:40:20 + 0 . 1 N formic acid ) . The suspensions were transferred to 1 . 5-mL microfuge tubes and incubated at −20 °C for 1 h , followed by 95 °C for 10 min . The tubes were then centrifuged to pellet the cell debris . 400 μL of the liquid phase was transferred to another microfuge tube and 16 μL of neutralization buffer ( 15% ammonium bicarbonate ) was added . The tubes were stored at −80 °C . Quantification of c-di-GMP using mass spectroscopy was then carried out , as previously described [70] . Freezer stocks were revived overnight in T-soy broth and then grown for 24 h in M9 minimal medium + 3% galactose ( GMM ) at 37 °C . 1 . 25 mL of each strain was added to 125 mL 3% GMM and incubated at 100 rpm at 37 °C for 12 h . While harvesting , flasks were incubated on ice for 10 min . The samples were then serially diluted and plated in half-strength T-soy plates to enumerate CFU/flask and then centrifuged at max speed for 15 min at 4 °C . Pellets were then resuspended in 500 μL of ice-cold extraction buffer ( methanol:acetonitrile:dH2O 40:40:20 + 0 . 1 N formic acid ) . The suspensions were transferred to 1 . 5-mL microfuge tubes and incubated at −20 °C for 1 h , followed by 95 °C for 10 min . The tubes were then centrifuged to pellet the cell debris . 400 μL of the liquid phase was transferred to another microfuge tube and 16 μL of neutralization buffer ( 15% ammonium bicarbonate ) was added . The tubes were stored at −80 °C . Quantification of c-di-GMP using mass spectroscopy was then carried out , as previously described [70] . Unknown lipids were extracted from RpfRCt ( PAS ) for analysis , as described previously [17 , 71] . A 2:1 mixture of chloroform and methanol was added to purified RpfRCt ( PAS ) in buffer I in a 4:1 ratio . The solution was then mixed vigorously until RpfRCt ( PAS ) had precipitated . The different phases were allowed to separate , and the chloroform layer was removed for analysis . Lipid released from purified RpfRCt ( PAS ) was determined by the analysis of the purified protein extract on an Agilent 6120 LC-MS system equipped with an EMD Millipore Chromolith SpeedROD analytical RP-HPLC column ( 50 x 4 . 6 mm ) . A 0 . 5 mL solution of RpfRCt ( PAS ) in buffer I was extracted using a 2-mL mixture of chloroform and methanol ( 2:1 ) . The bottom organic layer was separated and concentrated using N2 flow . The remaining residue was taken in 100 μL of acetonitrile/water ( 1:1 ) , and the solution was centrifuged to remove any precipitate . 50 μL of the supernatant ( or 25 μL of the standards in acetonitrile/water [4:1] ) were analyzed by LC-MS using a gradient of 10%–100% acetonitrile in water containing 0 . 1% formic acid in 10 min at a flowrate of 1 mL/min . The identification of the lipid was determined by the presence of the negative ionization [M-H]− corresponding to either BDSF− ( m/z calculated for C12H21O2− = 197 . 2 ) or C12:0- ( m/z calculated for C12H23O2− = 199 . 3 ) anions as observed in the extracted ion chromatogram of the lipids m/z . Lipid released from purified RpfRCt ( PAS ) that was coexpressed with RpfFBc , was identified by following the same extraction protocol described above . For LC-MS analysis , a gradient of 40%–100% acetonitrile in water containing 0 . 1% formic acid in 10 min at a flowrate of 1 mL/min was used to improve the separation between BDSF and C12:0 signals . Starter cultures of individual strains to be tested were incubated overnight at 37 °C and 200 RPM in 10 g LB ( IBI Scientific ) per 1 L diH2O . In order to remove residual BDSF , starter cultures were pelleted at 15 , 000 RPM at 25 °C for 10 min . Supernatants were removed from pelleted cells , which were twice resuspended in fresh LB . 25 mL of sterile LB was inoculated with 50 μL of starter culture and grown for 33 h at 37 °C and 200 RPM . Aliquots of the culture were removed at the specified times . To obtain cell-free supernatants , culture samples were centrifuged for 5 min at 15 , 000 RPM at 25 °C . Supernatants were separated from the pelleted samples and centrifuged for an additional 5 min at 15 , 000 RPM at 25 °C and stored at −20 °C . Aliquots were diluted and grown on LB agar plates overnight at 37 °C in order to determine the number of colony forming units ( CFU ) at the specified time . BDSF production was measured with the B . cenocepacia H111 pAN-L15 reporter strain using a modified protocol similar to those reported in [20 , 41] . The reporter strain was grown for 18 h in LB supplemented with 100 μg/mL kanamycin and 80 μg/mL chloramphenicol at 37 °C and 200 RPM to an OD600 = 1 . 6–2 . 5 . The reporter strain was pelleted at 3 , 000 × g for 30 min at 25 °C and resuspended twice in fresh LB supplemented with 100 μg/mL kanamycin and 80 μg/mL chloramphenicol . 100 μL of reporter strain was added to individual wells of a 96-well flat clear-bottom black polystyrene TC-treated microplate ( Costar ) . Cell-free supernatants from individual donor strain samples were diluted 1:10 ( v/v ) in fresh LB supplemented with 100 μg/mL kanamycin and 80 μg/mL chloramphenicol . 100 μL of the diluted donor strain cell-free supernatant was added to a well containing 100 μL of the reporter strain and incubated at 30 °C for 22 h . Following incubation , 50 μL decyl aldehyde ( Sigma-Aldrich ) was added to the lid of the microplate . Samples were shaken for 1 min at 200 RPM prior to measuring cell density ( OD570 ) , and light counts per second ( CPS ) for each sample were measured using a Perkin Elmer Envision 2014 plate reader equipped for advanced luminometry to determine relative light units ( RLU ) for each sample . RLU is defined as CPS/OD570 . Relative Bioluminescence is defined as RLU/CFU . Full-length rpfRBc ( corresponding to amino acids 1–667 ) was amplified using Phusion High-Fidelity DNA Polymerase from WT B . cenocepacia HI2424 genomic DNA and the oligonucleotide pair primer 7 and primer 16 . The PCR amplified insert was gel purified and cloned into a SapI/XhoI linearized pTB146 vector using In-Fusion ( Takara Bio , USA ) to generate pHis6-SUMO-RpfRBc ( full ) . Individual BDSF-binding site mutations ( S168A , N171A , R186A , and N201A ) were introduced into pHis6-SUMO-RpfRBc ( full ) using the QuikChange II Site Directed Mutagenesis Kit ( Agilent Technologies ) and the mutagenic primer pairs S168AF , S168AR , N171AF , N171AR , R186AF , R186AR , N201AF , and N201AR ( S2 Table ) . The full-length wild-type RpfRBc , RpfRBc–S168A , RpfRBc–N171A , RpfRBc–R186A , and RpfRBc–N201A expression vectors were transformed into E . coli strain BL21 ( DE3 ) cells and grown to OD600 = 0 . 60 in LB containing 100 μM ampicillin at 37 °C and 220 RPM , then moved to 25 °C and 200 RPM and induced with 500 μM IPTG . Cells were grown for an additional 16 h at 25 °C and 200 RPM and harvested by centrifugation at 3 , 000 × g for 30 min at 4 °C . Full-length wild-type RpfRBc , RpfRBc–S168A , RpfRBc–N171A , RpfRBc–R186A , and RpfRBc–N201A were purified in an identical manner . The pelleted cells were resuspended in buffer T ( 100 mM NaCl , 50 mM MOPS [pH 7 . 0] , 10 μg/mL DNAse , and 1 mM PMSF ) and lysed by two passages through a French press at approximately 25 , 000 PSI . The lysate was clarified at 35 , 000 × g for 60 min at 4 °C . 100 μL His6-Ulp1 was added to 500 μL clarified lysate and incubated at 4 °C for 1 h . Following the incubation , the reaction was centrifuged at 15 , 000 RPM for 5 min at 25 °C , and the pre- and post-Ulp1 digested samples were evaluated by SDS-PAGE . | Communication between many species of gram-negative bacteria is mediated by a family of cell–cell signaling autoinducers ( AIs ) known as the diffusible signal factors ( DSFs ) . DSFs are fatty acids , containing a signature cis-2 double bond critical for their activity . The DSFs differ from one another by their acyl chain length , branching , and the presence of additional double bonds . We have carried out the first structure–function studies of DSF binding to a receptor , regulation of pathogenicity factor R ( RpfR ) . We have determined X-ray crystal structures of the RpfR DSF-binding domain in complex with an active DSF , cis-2-dodecenoic acid , and in complex with its inactive saturated isomer , dodecanoic acid ( C12:0 ) . These X-ray crystal structures , together with extensive complementary in vivo and in vitro functional studies , reveal the molecular basis of DSF recognition and the importance of the cis-2 double bond to DSF function . In addition , we have discovered a previously overlooked domain at the RpfR N-terminus , and we show that this domain binds to and negatively regulates the DSF synthase regulation of pathogenicity factor F ( RpfF ) . We present X-ray crystal structures of this domain alone and in complex with RpfF , which—together with in vivo and in vitro functional studies—describe how RpfR binds to RpfF , negatively regulating the synthesis of its own AI . | [
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] | 2019 | Structural basis of DSF recognition by its receptor RpfR and its regulatory interaction with the DSF synthase RpfF |
DNA torsional stress is generated by virtually all biomolecular processes involving the double helix , in particular transcription where a significant level of stress propagates over several kilobases . If another promoter is located in this range , this stress may strongly modify its opening properties , and hence facilitate or hinder its transcription . This mechanism implies that transcribed genes distant of a few kilobases are not independent , but coupled by torsional stress , an effect for which we propose the first quantitative and systematic model . In contrast to previously proposed mechanisms of transcriptional interference , the suggested coupling is not mediated by the transcription machineries , but results from the universal mechanical features of the double-helix . The model shows that the effect likely affects prokaryotes as well as eukaryotes , but with different consequences owing to their different basal levels of torsion . It also depends crucially on the relative orientation of the genes , enhancing the expression of eukaryotic divergent pairs while reducing that of prokaryotic convergent ones . To test the in vivo influence of the torsional coupling , we analyze the expression of isolated gene pairs in the Drosophila melanogaster genome . Their orientation and distance dependence is fully consistent with the model , suggesting that torsional gene coupling may constitute a widespread mechanism of ( co ) regulation in eukaryotes .
Transcription involves the separation of the two DNA strands by the RNA Polymerase complex during the initiation phase . The formation of this “transcription bubble” [1] can represent a significant energetic cost , determined by the universal thermodynamic properties of the DNA molecule , and may thus constitute a widespread mechanism of gene regulation . This cost depends strongly on the promoter sequences , which are usually thermodynamically unstable [2] , [3] . But it also depends crucially on the presence of torsional stress [4] giving rise to supercoiling , a mechanical feature present in virtually all biological transactions involving DNA [5] , [6] , and in particular transcription and replication . A negative torsion results in a negative superhelical density , quoted , and destabilizes the double helix , facilitating the spontaneous formation of transient denaturation bubbles even at low temperature . Conversely , the double-helical state is stabilized by a positive torsion [2] . This mechanism is widely relevant to prokaryotic regulation , with most bacteria having a globally underwound genome allowing the spontaneous opening of promoters , while many “thermophilic” organisms constrain this torsional stress to a positive level , which could thus be one of the mechanisms ensuring the stability of the double-helix even beyond the usual melting temperature [7] , [8] . In eukaryotes , free DNA was found to be torsionally unconstrained at the global scale , and the role of supercoiling was often neglected for this reason . However , recent experiments demonstrated the presence of important levels of supercoiling in local “topological” domains [9] , [10] , which probably play a functional role . In vitro experiments have shown the influence of supercoiling in both prokaryotic and eukaryotic transcription , as shown in Fig . 1 . The bacterial promoter of pelE , inserted on a plasmid , is expressed by bacterial polymerase only when the DNA is underwound at a level similar to the in vivo average level of −0 . 06 ( B ) [11] . Eukaryotic RNA polymerase II , in contrast , is able to transcribe the yeast CUP1 promoter on a torsionally relaxed plasmid , but only in the presence of a minimal set of in vivo relevant transcription factors , and in particular TFIIH which contains an ATP-consuming helicase subunit ensuring the formation of the transcription bubble [12] , [13] . But remarkably , when the plasmid is negatively supercoiled , the gene can be transcribed by RNA PolII in absence of any transcription factor [12] , in which case the expression level increases with the applied torsional stress ( Fig . 1D ) . While this mode of regulation is probably not dominant in vivo , it could very well play a role for those genes located in underwound domains . Interestingly , for these two very different systems , the expression rate is proportional to σ2 , i . e . precisely the expected dependence of the promoter opening free energy , arising from the elastic cost of unwinding double-helical DNA [12] ( Fig . S1 ) . Altogether , accumulating data come in support of the long-proposed idea [4] that supercoiling-dependent promoter opening could be an important regulator of transcription , not only in prokaryotes [11] , [14] , [15] but also ( and differently ) in eukaryotes [3] , [12] , [16] . Conversely , an important source of supercoiling in vivo is transcription itself [10] , [17] . In the elongation phase where the RNA Polymerase complex advances along the gene sequence , it has to turn around the DNA axis following the helical geometry of the molecule . In 1987 , Liu and Wang [18] postulated that the frictional drag of this large complex would impede such a rotational movement; rather , the DNA strands would be twisted , resulting in a considerable accumulation of positive superhelical stress ahead of the transcription machinery , and negative behind it . This important stress originates from the transcription unit , and propagates along the DNA molecule over a few kilobases [19]–[22] , where it is progressively released by specific enzymes ( topoisomerases , gyrases ) existing in all organisms [22] , [23] . In vivo measurements suggested that this transcription-induced supercoiling is probably a major determinant of “topological domains” in eukaryotic as well as bacterial chromatin [9] , [10] , [17] . These two reciprocal aspects of transcription-supercoiling coupling have been known for decades . Their combination immediately suggests that the transcription of adjacent genes could be coupled by the propagation of torsional stress along the DNA . This mechanism has already been suggested and experimentally demonstrated in specific examples of both prokaryotic [14] , [24] and eukaryotic [21] , [25] , [26] divergent promoters . Moreover , genome-wide analyses of sequence motifs associated to torsionally-induced DNA structural transitions have illustrated the possible widespread role of torsion in the regulation of nearby promoters in bacteria [15] , [27] . However , there is no systematic and quantitative description on how nearby genes could mutually affect their expression through supercoiling , and how this coupling would then depend for example on the relative orientation and distance of the genes . Since it relies on physical properties of DNA , this effect is likely to universally affect eukaryotic and prokaryotic organisms , although with different effects owing to the different level of supercoiling in these organisms or to their different gene densities . In eukaryotes in particular , some studies suggest that DNA supercoiling could account for co-regulation of neighbor genes [26] . In this paper , we propose a simple theoretical framework for this interaction , which allows exploring the role of different parameters ( promoter orientation and distance , gene length , basal superhelical density… ) on the time-averaged co-expression of neighbor genes . The model focuses on the most generic features of the interaction since they prevail at the genome-wide level . It voluntarily leaves aside several specific aspects of promoters response to supercoiling . The proposed mean-field description is derived from the knowledge-based physical properties of the double-helix , and requires only few adjustable parameters to quantitatively reproduce the behavior of model experimental systems in very different ( prokaryotic or eukaryotic ) organisms . By extrapolating this behavior to different parameters , it allows to predict the differential effect of the torsional coupling in a broad range of conditions and organisms . Interestingly , despite the very different global role of supercoiling in prokaryotic and eukaryotic regulation , the local torsional perturbation is predicted to affect the regulation of nearby genes in both types of organisms ( albeit differently ) , in particular in the case of symmetrically oriented ( divergent or convergent ) genes , as already observed [24]–[26] , [28] . This perturbation differs substantially from usually proposed mechanisms of “transcriptional interference” , which assume that the adjacent genes overlap , or experience a collision or sharing of their transcriptional machineries [28] , [29] . Here , we suggest that even without any molecular contact between the machineries expressing distant genes , the propagation of torsional stress along the DNA could significantly couple ( positively or negatively ) their expression . Finally , we show that the predictions of the model are supported by published expression data of Drosophila melanogaster , where the expression of isolated gene pairs significantly depends on their orientation and distance .
The destabilization of the double-helix by torsional stress is a well-known phenomenon [4] , which was shown to play an important role in the global regulation of both prokaryotic [15] and eukaryotic [30] promoters . As an example , it is involved in the rapid response of bacteria to an external stress , where all promoters must rapidly modify their expression in a coordinated manner [11] , [14] . This mechanism has been quantitatively described using at least two different physical models of DNA , that of Benham and coworkers [2] , [27] and the mesoscopic Peyrard-Bishop-Dauxois model [3] , [16] . Both models are based on measured thermodynamic and elastic properties of the base-pairs [2] , [8] , and estimate the supercoiling-dependent opening free energy of the double-helix . Here , we use a recent efficient implementation of the former model [31] , [32] , and integrate it into a thermodynamic model of transcription [33] , [34] , which then allows to compute the average transcription rate of a promoter of given sequence ( Fig . 1 ) . The melting profile predicted by the DNA model typically exhibits a sharp transition around ( Fig . 1A ) , with the opening probability increasing with the applied negative supercoiling . The proposed framework is based on the hypothesis that the transcription level is proportional to the initiation probability , as estimated from the chemical equilibrium between the bound and unbound states of the transcription machinery . We note however that the formation of the transcription bubble is not a purely thermal process , but is rather facilitated by conformational changes in the RNA polymerase complex , which may depend on the type of polymerase of the organism ( in particular the bacterial polymerase vs . the energy-consuming eukaryotic Polymerase II ) [1] . This non-thermal energy scale is taken into account by introducing an effective temperature , which is then the only adjustable parameter of the transcription model and can be calibrated on in vitro experimental data ( see Fig . 1 and Models section ) . This description neglects a part of the promoter specificity in the initiation stage , and other regulation mechanisms in the subsequent stages of transcription ( see Models ) . Despite these simplifications , the model quantitatively reproduces the expression profiles of the model systems ( Fig . 1 ) . In these experiments , the superhelical level is fixed by the number of superhelical turns imposed in the plasmids where the gene is inserted . In the following of the study , we extrapolate this response curve to promoters located on the chromosome ( s ) , where the external source of supercoiling is different , and where the model then allows to make predictions for a broad range of situations without any additional parameters . This simplicity is a key advantage for our model focusing on the most generic consequences of the torsional coupling between adjacent genes at the genome-wide scale . The reader should however keep in mind that more specific features are not taken into account , in particular the subtle competition between different stress-induced transitions [15] which are known to affect the opening rates of bacterial promoters , and allow for a fine tuning of the supercoiling-dependent regulation with the help of DNA-binding proteins [14] ( see Discussion ) . In the following we focus on the simpler situation where the opening of the initiation site is the only structural transition absorbing the superhelical stress . The superhelical stress involved in transcriptional regulation can have different origins . In prokaryotes , this level is controlled at the global scale by ATP-consuming enzymes [7] , [14] . In eukaryotes , the situation is very different , since nucleosomes cover most of the genomic DNA and store a constrained level of supercoiling [6] , while free DNA is torsionally relaxed in average . However , both types of organisms exhibit local variations of these values in so-called topological domains [9] , [10] , [17] , which could be generated by transcription . While previous studies have focused on the promoter response to a fixed level of supercoiling , in this paper we consider the specific case where the external source of supercoiling is the transcription of a nearby gene along the DNA molecule , and we quantify how its influence then depends on the distance , length and orientation of the genes . The transcribing polymerase acts as a torsional motor that generates positive superhelical stress ahead of the complex , and negative stress behind it [18] , [35] . This stress propagates along the DNA double-helix [10] , [21] , and is progressively released by specific enzymes ( topoisomerases ) , but also , in the case of eukaryotes , by the release of nucleosomes [22] . In this paper , we neglect the dynamic aspects of the process and consider its time-averaged approximation consistent with the thermodynamic model of transcription , which can then be described using a mean-field approach . Assuming that the stress is progressively released outside the gene with uniform efficiency , the resulting time-averaged distribution of superhelical stress decays exponentially from the transcription unit ( see Models and Fig . 2 , upper panel , with different basal levels of supercoiling ) . This profile is consistent with various measurements obtained in vivo with different protocols , involving either the intercalation of a psolaren-based agent in underwound DNA [21] , structural transitions of the double-helix [19] or a supercoiling-sensitive promoter [20] . While the properties of this propagation could be expected to depend on the considered system ( topoisomerase concentration , DNA sequence… ) , these very different in vivo experiments reported remarkably consistent propagation distances of around 1000 bases . Surprisingly , this value was observed not only in prokaryotic , but also in eukaryotic organisms , suggesting that nucleosomes do not modify significantly the propagation distance ( see Discussion ) . We note however than only the psolaren-based experiment [21] was calibrated so as to provide a direct and quantitative measure of the level of superhelical density; other methods were either more indirect [24] or provide only a qualitative estimate of the supercoiling level associated to the employed probe of supercoiling [19] , [20] . Future experiments might therefore allow refining these estimates , and distinguishing the propagation modes in different organisms . In this paper , based on the available experiments , we use the value of 1000 bp for the propagation distance as a parameter in the model , for both prokaryotes and eukaryotes . The amplitude of the perturbation is assumed proportional to the transcript length and the promoter strength , consistent with the idea that the torsional stress accumulates as the polymerase unwinds the two DNA strands along the gene ( one turn every 10 base-pairs ) and confirmed by experimental data [24] . The parameters of the models are adjusted so that the generated levels of supercoiling are compatible with the data of Kouzine et al . [21] . Fig . 2 shows the local distribution of supercoiling , as obtained from the previously described model of transcription for an illustrative gene of 1 kb . The different displayed curves correspond to illustrative basal levels typical of prokaryotes in different growth phases , from −0 . 03 in the ATP-poor stationary phase to −0 . 09 in specific cases of external shock [14] . Higher levels are rather relevant to eukaryotes , where free DNA is torsionally unconstrained in average ( ) , but can also vary along the genome [9] , [10] , with possible causes including transcription and other dynamic processes involving nucleosomes . For simplicity , we used a common gene length of 1 kb in all cases , which is illustrative of many prokaryotic as well as eukaryotic genes . Note that in eukaryotes , the average gene length is often larger ( 5 kb in Drosophila melanogaster , and 10–20 kb in mammals ) , but this number is strongly affected by a minority of very long genes ( up to 2 Mb for humans ) . In contrast , the median length , which reflects the majority of the genes , is closer to 1 kb ( e . g . 1 . 75 kb for D . melanogaster ) . Our illustrations are therefore relevant to most eukaryotic genes , but not to very long genes where the elongation kinetics probably plays an important role . If another promoter is located within a few kilobases of the transcribed gene , the curves of Fig . 1 suggest that the locally generated superhelical stress may modify its opening properties , and thus its transcription level . Actually , one of the methods used to monitor the transcription-induced supercoiling is based precisely on this property , in which case the torsional response of the employed probe promoter must first be calibrated [20] , [24] . By combining these distributions with the supercoiling-dependent transcription rate as described in the previous paragraph , we are able to predict the modification of transcription rate due to the transcriptional interaction ( Fig . 2 , lower panel ) . Unsurprisingly , the transcription is reduced when the promoter is located downstream of the transcribed gene , and increased when upstream; this effect decreases with distance in a non-trivial way due to the nonlinear opening profile of the promoter . With this mechanism depending only on the universal physical properties of the double-helix , it is likely to affect all types of known organisms . However , and importantly , because of the different basal levels of prokaryotes and eukaryotes , the predicted effects are different . In bacteria , the promoters are mostly “open” , and the repressive effect tends to be stronger than the inductive one . In eukaryotes conversely , negative stress generated locally by transcription could significantly increase the expression level of any gene located upstream of the promoter . Fig . 2 shows only the effect of one transcribed gene on the neighbor's promoter . However , we expect that the second gene will in turn also influence the former's promoter , and modify its expression . The level of each promoter is therefore the result of a dynamic equilibrium between the two genes . Applying the model developed in the previous section , this level can be determined numerically with a simple algorithm . Starting with the whole stretch of DNA at the basal supercoiling level of the considered region/organism , we iteratively compute the expression level of each promoter , and adjust the supercoiling profile accordingly until reaching a fixed point . Unsurprisingly , the effect of the interaction depends crucially on the relative orientation of the two genes , as shown on Fig . 3 . The figure shows that its strength is also a function of the distance between the promoters and the basal superhelical density of the organism ( dashed lines indicate the average value of this density for prokaryotes and for free DNA in eukaryotes ) . In the case of divergent promoters ( A ) , each promoter favors the expression of the neighbor , which in turn increases the former's activity . The diagram of the dynamic system shows that the effect is predicted to be stronger for eukaryotic organisms , and decays sharply at a cutoff distance that decreases with the basal superhelical level . Note that the diagram shows the relative change in expression level; in general , for a given promoter sequence , the absolute basal level is higher for lower values of σ0 ( Fig . 1 ) . In contrast , convergent promoters are mutually repressive ( B ) . This type of interaction in well-known in biochemical networks , and can lead either to a global reduction of both expression levels , or to the selective extinction of one of the two genes . This repressive effect is predicted to affect bacteria more strongly than eukaryotic organisms . Finally , for genes in tandem ( C ) , the interaction is more subtle , with an asymmetrical influence leading to a limited increase of the upstream gene and repression of the downstream gene , especially at intermediate basal levels of supercoiling where both effects may coexist . The presence of an interaction between the transcription of neighbor genes is often referred to as “transcriptional interference” in the biological literature , and has been reported in many studies [28] , [29] . We noted that supercoiling has already been evoked as a possible mechanism for divergent promoters , but only in a few studies that specifically address this topic [24]–[26] . In contrast , most general papers on transcriptional interference assume a direct molecular contact between the transcription machinery of the genes , either by collision if the genes or their promoters overlap , or by incorrect termination ( read-through ) , or simply if they share the same individual regulatory protein or polymerase [36] . It is interesting to note that the torsional coupling proposed here implies that any two genes distant of less than ∼3000 bases experience a mutual influence without any interaction of their transcription machineries , simply by propagation of the DNA mechanical deformations . The proposed torsional coupling implies that neighbor genes are not independent , but coupled in an orientation-dependent way . Genome-wide expression analysis studies have demonstrated the co-expression of adjacent genes in yeast [37] as well as plants [38] and mammals [39] . Among these coexpressed pairs , divergent genes were found to be the most frequent as well as more expressed and highly correlated [37] , [38] , [40] , [41] , and also less noisy [41] , while convergent gene pairs were under-represented [29] . A fraction of these divergent pairs are “bi-promoters” , where a single bidirectional promoter controls the two genes of the pair , in which case a transcriptional coupling can indeed be expected without any torsional effect . For the majority of the genes where the promoters are separate , the proposed explanation for the co-expression is that neighbor genes may often belong to the same chromatin domain , with similar expression properties , as identified by biochemical marks [42] . But while the chromatin state does certainly play a crucial role in these correlations , we do not expect this effect to depend on the pair orientations . Several authors argue that divergent promoters are often closer , and the effect should thus be stronger in this case than for tandem and convergent promoters . But the only identified lengthscales associated to chromatin regulation are either larger , with topological and epigenetic domains of 10–1000 kb [9] , [42] , or smaller , with a co-regulation being expected if the two promoters belong to the same nucleosome ( 200 bases ) . Between these two scales , it is difficult to predict how the correlations should depend on the distance; this dependence could even be non-monotonous if genomic sites located 5 or 10 nucleosomes apart ( 1 or 2 kb ) are spatially closest in the fiber and can share their transcription machinery . Moreover , if the different types of pairs are located randomly in the fiber , this effect would only explain a correlation , but not an over-expression of the divergent genes . We suggest that the observed orientation-dependent expression features could be naturally explained by a torsional coupling between the genes . Interestingly , recent genome-wide measurements of supercoiling level showed that regions of gene clusters of several kilobases are subject to negative supercoiling correlated to the transcription level [9] , [10] . A more detailed analysis of specific locations pointed to the particular effect of divergent genes , where the torsional coupling that we model here was directly observed [26] . To investigate the presence of such effects on a wider scale and in different orientations , we analyze the genome-wide expression of gene pairs from RNA-Seq expression data of 24 cell lines of Drosophila melanogaster [43] . We separate the torsional effects from other uncontrolled features , by focusing on “torsionally isolated” pairs of neighbors , i . e . pairs where ( i ) the genes are closeby , with the transcription units ( start or end sites ) less than 5 kb from the other gene's promoter and ( ii ) the two promoters are more than 3 kb away from any gene outside the pair , and therefore likely unperturbed by their transcription-induced torsion . This situation is rare in yeast where the genome is dense ( and even more so in prokaryotes ) , and where short-range torsional interactions may form long chains of coupled genes , making it difficult to distinguish the proposed effect ( see Discussion ) . In contrast , D . melanogaster has about 1400 of these pairs , representing nearly 20% of its genes . Among these pairs , 748 are divergent , 552 are in tandem , and only 103 are convergent . Note that these numbers do not necessarily indicate an evolutionary selection against convergent pairs: even with randomly distributed genes , our selection procedure eliminates more convergent pairs because their outwards promoters are more likely to be close to other genes . If the torsional coupling plays a role in the co-expression , we expect all orientation-dependent features to decay over a distance of around 1000 bases between the genes . Fig . 4 shows that the large majority of both divergent and tandem pairs are indeed located in this range ( upper panel ) , and may thus be transcriptionally coupled . Such a mechanism would increase the expression level as well as the correlation between two genes of a divergent pair , and reduce those of a convergent pair . The fraction of nonzero expression genes ( second row ) is indeed considerably larger for divergent genes , starting from about 80% for close genes , and decreasing to ∼30% at 3000 bases of distance . Importantly , the smooth decrease seems incompatible with other proposed explanations such as bidirectional promoters , but is fully consistent with the idea that the negative torsion would help opening the promoter with a distance-decreasing strength . In tandem and convergent pairs , the open fraction is indeed lower , but the distance dependence is less clear . The average expression ( lower row ) presents similar features . We notice that only closeby divergent genes are above the average level of the genome ( dashed line ) . Since these genes are also the most frequent , they represent the overwhelming majority of transcripts in the considered sample ( third row ) . We identified the pairs that exhibit a correlated expression of the two genes in the 24 independent experiments carried on different cell lines ( details of the employed criterion are given in the Models section ) . The correlation is indeed more frequent in closeby divergent genes , where about 20% of the genes are coexpressed , against 5–10% in tandem genes ( upper panel , red curve , mind the different scale from the black curve ) . The curve decreases even faster than the previous ones , with nearly all correlated pairs separated by less than 1000 bases . Altogether , these expression data consistently suggest that the supercoiling-mediated interaction could play an important role in the control of paired gene expression in vivo .
We have proposed the first quantitative model of the torsional coupling between adjacent genes , which predicts a particularly strong mutual influence of divergent/convergent pairs , albeit with very different consequences in prokaryotes and eukaryotes . How do these results compare to published experimental data ? Only few quantitative studies followed simultaneously the level of supercoiling and transcription , and they involved mainly prokaryotic genes in vitro . In [24] , Opel et al . followed the expression of a pair of divergent bacterial promoters placed on a plasmid , as a function of the global superhelical level ( i . e . along a vertical line in the diagram of Fig . 3A ) . Consistent with our predictions , the expression of the probe gene is triggered at ( wrt in absence of the second gene ) , suggesting that the self-reinforcing pair is able to generate a significant local superhelical stress of even at a relatively high basal level where the expression of each separate gene is normally low ( see Fig . 4 in ref . [24] ) . In eukaryotes , the presence of supercoiling is more localized [9] and complicated by the ubiquitous presence of nucleosomes ( see below ) . Still , in the case of divergent promoters , the role of negative supercoiling in the activity of a promoter was demonstrated in a transfected plasmid [25] and recently directly in a human chromosome [26] . To our knowledge , only one study [28] systematically compared the expression level of a pair of genes in the different configurations ( divergent , convergent , tandem ) , in this case two fluorescent genes controlled by the viral promoter CMV , inserted in two genomic sites of the mouse genome ( and on both strands in each case ) . In the divergent and convergent configurations , the results are consistent in both sites and global orientations of the cassette ( Fig . S4 A ) , suggesting that the effect of the chromatin environment or nearby genes is limited . The expression levels of the two genes are also similar in all cases , consistent with the symmetric construction . The divergently oriented genes are systematically expressed around 4 times stronger than the convergent genes ( with relatively large deviations ) , compatible with the diagrams of Fig . 3 . For genes placed in tandem , where we predict a lower effect of supercoiling , the results are indeed less clear , with the relative expressions depending on the insertion site and strand , maybe reflecting the influence of the chromatin environment ( see Fig . S4 B ) . Altogether , these results clearly suggest at least a partial role of supercoiling . However , the authors did not mention this possibility [28] . They rather suggested a direct interference between the polymerases transcribing the two genes , although it is difficult to predict even qualitatively how this effect would then depend on the gene orientations . Conversely , the data also illustrate the difficulty of identifying the influence of supercoiling on a single construction in absence of a direct local measurement of σ , where it may be hidden by uncontrolled local features or by more specific regulation mechanisms . Our model , aimed at describing the most systematic effects of supercoiling , is applicable to a wide range of experimental systems with a very limited number of parameters , and may thus help to overcome such problems and distinguish similar effects of superhelicity in independent experiments . More specific features may however lead to deviations from our predictions , which might be taken into account in more involved models , and are discussed in the following paragraphs . A first simplification is the exponentially-decaying profile of time-averaged superhelical density resulting from transcription . This profile is in agreement with in vivo experimental observations in both prokaryotes and eukaryotes [19]–[22] . The similarity between the decay length in both types of organisms was unexpected , considering that nucleosomes cover around 80% of eukaryotic genomes , and are able to store a significant amount of negative supercoiling [5] , [21]: their eviction could thus contribute in absorbing the positive stress downstream of a transcribed gene [10] , [21] , [22] , [44] . One possible intuitive explanation is that the total level of supercoiling generated by the elongating polymerase ( one turn every 10 . 5 bases ) is anyway considerably larger than the level possibly absorbed by nucleosomes ( about one turn every 200 bases ) : even after their eviction , most of the stress should still be released by topological enzymes . The dynamic rearrangement of nucleosomes around the transcribed region could also complicate considerably the interaction between adjacent genes , and , for time-averaged quantities , result in non-monotonous curves of propagated torsion rather than the simple exponential decay considered here . These interpretation problems reflect the limitations of our time-averaged description of an intrinsically dynamic process , a limitation also present in the available expression data . It may be refined using time-resolved data which only begin to reveal the details of the process [35] ( see below ) . A second simplification is our nonspecific description of the promoter response to supercoiling . It is well-known that this response depends on the promoter , with non-monotonic expression profiles [24] . For the prokaryotic gene coding for the gyrase enzyme that underwinds DNA , the promoter is even triggered precisely when the DNA is overwound [20] . Such effects deviate from our simple monotonic opening profile . They may be due in part to a sequence-specific contribution to polymerase binding ( see details in Models ) and subsequent steps of transcription ( e . g . promoter escape ) . But another , likely stronger , mechanism is the competition between the opening of the polymerase binding site and structural transitions at distal sites , which involves specific DNA-binding regulatory proteins [14] . Such effects are already present in the in vitro model promoters of Fig . 1 . For the yeast promoter ( C–D ) , the relatively smooth profile results from the simultaneous opening of a distal site in the employed sequence ( around 300 bp ahead of the TSS ) . If this site is removed and the polymerase binding site alone is included in the calculation , the profile is much sharper and deviates from the data . In contrast , for the bacterial promoter of pelE ( Fig . 1 A–B ) , experiments show that transcription occurs only in the presence of the Crp binding protein [11] , otherwise the opening of a very unstable distal site absorbs the negative torsion almost entirely , and prevents the opening of the initiation site ( S . Reverchon , priv . comm . ) . Consistently , if we include the full regulatory sequence in the calculation , only the distal site is opened . The expression profile of Fig . 1D was reproduced by including only the polymerase binding site ( 60 bp ) , suggesting that Crp binds to the melted distal site and closes its bubble , thereby allowing the formation of the transcription bubble . Interestingly , this kind of subtle mechanical interactions was observed on a widespread scale in bacteria [45] , involving a whole class of regulatory proteins which can interact with the polymerase [14] , as well as alternate stress-induced structural transitions of the double-helix ( B–Z or B–H transition , cruciform formation , G-quadruplex… ) [15] , [46] . Together , these effects allow a fine-tuning of the supercoiling-dependent response of promoters , and particularly those of stress-response genes involved in regulatory functions [27] . The modification of the physical properties of the double-helix may allow for a rapid re-programming of the expression pattern of the organism , in particular in response of an external stress or during different growth phases [11] , [14] . Interestingly , a similar regulation mechanism was observed in the human MYC gene , where specific proteins bind to the regulatory sequence FUSE when the latter is melted by negative supercoiling [21] . In eukaryotes , supercoiling could thus also be involved in regulatory mechanisms more complex than considered in the present study , and where nucleosomes are likely to play a crucial role . An important point to notice is that our model only describes the time-averaged properties of gene expression . How these properties relate to the dynamic , i . e . time-dependent mechanisms , is difficult to predict . In particular , an interference between neighbor genes does not necessarily imply that they are actually transcribed simultaneously . If this was the case , e . g . for convergent genes , we would then expect the wave of supercoiling of one gene to hit and block the elongating polymerase of the other gene [35] , without ever reaching its promoter , an effect that is not included in our model . However , a comparison of the timescales involved in the transcription process suggests that this scenario is likely not the dominant effect . Indeed , measured elongation rates are in the range 20–100 bases/second [47] , i . e . the elongation phase takes typically less than a minute for usual genes . In contrast , the supercoiling generated by transcription was shown to take around 30–60 minutes to be released by topoisomerases ( in human cells ) [21] . In most cases , we thus expect that , when one of the gene is transcribed , there is no elongating polymerase on the second gene , and the torsional perturbation can reach its promoter and thus affect its initiation rate for the following ∼30 minutes . For convergent promoters , this rate is reduced , while for divergent genes , if negative supercoiling allows to shortcut the ( possibly rate-limiting ) requirement of transcription factor recruitment [12] , then a transcribed gene could dynamically trigger the expression of its neighbor . However , we also note that many eukaryotic genes are transcribed during short and infrequent events referred to as “transcription bursts” [48] , maybe controlled by other factors such as epigenetic modifications or the stochastic recruitment of transcription factors . If these events are rare ( separated by more than 30 minutes ) , then in average the supercoiling generated by the transcription of one gene can be entirely released before the second gene is expressed , and the two genes are torsionally decoupled and we expect no interaction . If this happens for many genes , it might explain the observations of Fig . 4 , that only 20% of the close divergent gene pairs are coexpressed . However , such dynamic scenarios remain speculative , when only population-averaged expression data are employed in the analysis . In the future , time-resolved single-cell expression data will allow to properly distinguish the dynamic aspects of the torsion-induced coupling between adjacent genes , and will then justify to consider more involved dynamic models , where the supercoiling should affect not only the initiation rate , but also the elongation of the polymerase in the case where the two genes are elongated simultaneously ( in particular convergent genes ) . Such models will be particularly relevant , since divergent pairs were found to exhibit not only higher expression levels , but also lower expression noise in yeast , which may constitute a characteristic feature of this architecture [41] . In the analysis of RNA-Seq data , we focused on the “torsionally isolated” pairs of genes , where the mutual interaction could be most clearly identified . Only in eukaryotes could we find a sufficiently large number of these genes , and we therefore restricted the analysis to Drosophila . It does not mean however that other species are not affected by the interaction , but the small number of these pairs in denser genomes makes it more difficult to test the predictions . This is true in particular for prokaryotes , where the predicted effects are different , but where most promoters are expected to be simultaneously coupled to several other genes , often with different orientations [15] . Even in Drosophila , many genes were disregarded because their promoter was within torsional influence of more than a single gene . This situation is probably also frequent in the less compact mammalian genomes , where many genes were found to be densely clustered [39] . In this case , based on the proposed model , we expect a complex simultaneous transcriptional coupling between the ( potentially many ) genes of the cluster , with each gene affecting directly all promoters in its vicinity , and indirectly the more remote ones . This chain of coupled genes extends until a promoter-less region of ∼3000 bases acts as a “topological insulator” for the transcription . The chain could be very long in the case of dense genomes such as yeast ( or prokaryotes ) , with short-ranged interactions possibly giving rise to collective transitions , as suggested by an analogy to the unidimensional Ising chain . If this transcriptional coupling of adjacent genes plays a functional role , it could thus constitute an eukaryotic equivalent to prokaryotic operons . Although our model theoretically allows to describe such features and numerically compute the result of the collective coupling , we note that the nonlinear interactions between the genes make the behavior strongly dependent on the details of the employed models and computation methods , especially when the number of involved genes increases . With only limited available data , we crucially miss the required precision to embark on the systematic calculation of such effects . We merely note that they would support a functional role for gene clusters , which again differs from the usual idea that closeby genes can only be positively correlated if located in the same chromatin domain . Rather , the orientation-dependence of the torsional coupling could lead to more complex relations between clustered genes . Importantly , these relations extend not only to coding genes , but also to promoters controlling non-coding transcripts . These promoters have attracted considerable attention recently for their possibly widespread role in transcriptional regulation . Interestingly , while short non-coding RNAs have widely recognized functional roles , that of long ones is less clear , and in particular a subclass of long antisense transcripts [49] . It has been suggested that this regulatory role could be played during their transcription , which would interfere with a coding gene . Again , suggested mechanisms are generally based on direct clashes between the polymerases of the coding and non-coding genes [49] , but we expect such clashes to occur for short as well as long RNAs . In contrast , we note that long transcripts are precisely the ones leading to significant amounts of supercoiling . Torsion is thus a potential candidate for a specific mode of action of long non-coding transcripts , which would be particularly strong for antisense ones , and could affect coding promoters even at some kilobases of distance .
Consistently with the time-average approximation of gene expression , the distribution of superhelicity σ generated by a transcribed gene is described with a mean-field approach . The average superhelical density ±σa at either end of the transcription unit is assumed proportional to the promoter strength k and transcript length l , consistent with experimental observations [24] . Outside the gene , this stress propagates , while topoisomerase enzymes have a uniform probability 1/b to release the local excess of torsion σ ( x ) : . This equation yields an exponentially decaying distribution consistent with experimental observation [19]–[22]: ( 1 ) where x0 and are the beginning and the end of the transcribed unit respectively , and the decay length is given by the topoisomerase efficiency 1/b . This efficiency may depend on topoisomerase concentration ( and thus on the organism ) as well as on DNA sequence , in particular through sequence-specific transitions of the double-helix [14] , [15] ( see Discussion ) , but in vivo experiments involving very different organisms and protocols [19]–[22] yielded consistent results in the range of ∼1 kb , which we use as a parameter in the simulations illustrating the model throughout the paper . These simulations ( Figs . 2 and 3 ) involved identical genes of 1000 bases in length and the sequence of the CMV viral promoter ( opening profile in Fig . S2 ) used in the experiments of Fig . S4 [28] , [48] . The parameter α was adjusted to generate levels of supercoiling compatible with the experiments [21] , for the arbitrary unit of expression used in these simulations ( see below ) . The supercoiling-dependent opening free energy of DNA is estimated from a recent efficient implementation [32] of the Benham model [2] , [31] , which estimates the opening probabilities of a sequence for given salt and temperature conditions , from the knowledge-based thermodynamic and elastic properties of the double-helix . We checked the robustness of the computation by comparing the melting profiles obtained with the promoter sequence only , or flanked by random sequences of various lengths , with no significant differences . The typical shape of the free energy curve is shown on Fig . 1A , with a transition between and “over” and “undertwisted” states . For simplicity , the numerical estimations of the torsional coupling included a sigmoidal fit covering the entire crossover: ( 2 ) where is the sequence-dependent threshold of supercoiling-induced destabilization , is the width of the transition and m , v , q are adjustable parameters ( see the solid lines in Fig . 1 A–C ) . For the curves of Fig . 1 A–C , we included the 60 base-pairs sequence ahead of the pelE transcription start site ( thereby excluding an unstable distal site which competes with the polymerase binding site and is stabilized by the binding of Crp , see Discussion ) , and the entire 410 bp-sequence ahead of the CUP1 transcription start site ( as used in the experiments ) , respectively . Note that for extreme positive torsions ( left of the shown curve on Fig . 1A ) , the thermodynamic model predicts a second destabilization of the double-helix ( due to the elastic energy of the double-helical state ) , which contrasts with the “standard” melting behavior facilitated by negative supercoiling . Assuming that this alternate melting behavior does not occur in the cell in presence of topoisomerases , we did not take it into account in the simulations , and used a monotonous fitted dependence ( Eq . 2 ) . Following proposed thermodynamic models of transcription [33] , [34] , the expression level is assumed to be proportional to the initiation probability , as resulting from a chemical equilibrium of bound and unbound states of the transcription machinery . We further assume that the only supercoiling-dependent contribution to the initiation free energy is the opening penalty of the promoter , as computed from the thermodynamic model of DNA described in the previous paragraph . The formation of the transcription bubble involves the binding of the polymerase , with an additional contribution , hence a total initiation free energy: ( 3 ) Throughout the paper , we assume that is independent of σ . This hypothesis has strong support for proteins which bind less than 10–15 basepairs , such as many individual transcription factors [34] . Indeed , for the considered supercoiling levels , the twist deformations of the basepairs ( /bp ) are weaker than the thermal fluctuations at room temperature ( standard deviation /bp ) [8] and can be accommodated without substantial energy cost . This statement is valid up to ∼10 basepairs , after which the correlated twist modification induced by supercoiling becomes larger than the typical deformations generated by the uncorrelated base-pair fluctuations , and may modify significantly the binding properties . This is true in particular for the large RNA Polymerase complex which binds about 30 basepairs of DNA , and where the supercoiling dependence of the initiation free energy may differ from the melting profile . However , this dependence would then be highly specific not only to the supercoiling level but also to the sequence , which would both contribute for instance to the relative position and orientation of the −10 and −35 binding sites of the polymerase [1] . These features may explain the specificity of promoter response to supercoiling [50] . However , since the aim of this paper is to focus on the generic features only , we do not take this dependence into account . The formation of the transcription bubble is not a purely thermal process , but is facilitated by conformational changes within the RNA polymerase complex . This contribution is difficult to estimate precisely , and probably depends on the type of RNA polymerase . In particular , we expect it to differ between bacterial polymerase which requires no external source of energy to initiate transcription , and eukaryotic RNA PolII which contains an ATP-hydrolysis-dependent helicase subunit [1] . We simply assumed that the equilibrium process takes place at an effective temperature Te , which defines an energy scale related to the polymerase energetics; this parameter is then adjusted from expression data . For the prokaryotic polymerase of Fig . 1B ( see below ) , we used the value ( where kB is the Boltzmann constant ) best reproducing the experimental curve . Interestingly , we found that the in vitro expression data of the eukaryotic promoter CUP1 ( Fig . 1D ) are best reproduced by assuming a purely thermal process , . A possible explanation is that these data were obtained in absence of the ATP-consuming transcription factor which ensures the opening of the double helix in vivo . In contrast , the in vivo data of ref . [28] ( Fig . S4 ) are consistent with a value , suggesting that the in vivo expression is made of two contributions: ( i ) the thermal opening of underwound promoters and ( ii ) the assisted opening of relaxed promoters ( about 4 times less frequent than the former ) . Note that because of the relatively large error bars in both experiments , these values are not very precise , but even large modifications would not change the qualitative predictions of the model . For the simulations of Figs . 2 and 3 , we chose a value , compatible with the eukaryotic in vivo expression data of [28] and relatively close to the value found for prokaryotes . The probability to form a transcript , and hence the average transcription rate k of the gene is then given by: ( 4 ) where is the Boltzmann factor defining the effective energy scale . Note that within this framework , the transcription rate fold-change due to supercoiling ( as shown on Fig . 3 ) is independent of , and can thus be computed without detailed knowledge of the binding energetics: ( 5 ) with σ0 the basal supercoiling level of the organism . Together , Eqs . 4 and 1 allow computing the effect of the torsional coupling on the expression of a pair of genes , as a function of their distance , promoter strength and the basal superhelical level ( Fig . 3 ) . We integrated the model numerically with an iterative algorithm . Starting from the transcription rate in absence of local supercoiling ( ) for both genes , the procedure successively adjusts the level of supercoiling ( and thus the transcription level ) of each promoter until numerical convergence ( fixed point ) . This procedure , as well as all analysis and plotting , were implemented in Python , with the Numpy/Scipy [51] and MatPlotLib [52] libraries . The RNA-Seq expression data from 24 D . melanogaster cell-lines was taken from the November 1st , 2013 release of FlyBase ( 2013_06 release , library FBlc0000260 ) , and based on communication [43] . They contained the expression levels of ∼16000 genes , including the ∼1500 non-coding genes ( detailed information is described on the FlyBase website ) . The two genes of a pair were considered as correlated if ( i ) they were simultaneously expressed in at least 6 of the 24 experiments; ( ii ) Pearson's correlation coefficient between the 24 pairs of expression levels is larger than 0 . 5 . A modification of these threshold values changed the absolute number of “accepted” pairs , but not significantly the relative number of divergent vs . tandem or convergent correlated pairs . | During the transcription process , the genetic sequence encoded in the DNA molecule is expressed by an enzymatic complex . This process is often considered as independent for each gene , despite numerous reported cases of one transcribed gene perturbing a neighbor gene's expression , which is then regarded as a side-effect . Here , we suggest in the contrary that such interactions are a widespread feature , resulting from the propagation along the DNA molecule of mechanical stress generated during gene transcription . This torsional stress modifies the facility with which the transcription machinery separates the two strands of the double-helix in order to access the bases , and thus the expression level of any gene located nearby . We develop a quantitative model of this effect , showing that it depends strongly on the orientation of the genes , which is confirmed by the analysis of in vivo expression levels in the drosophila genome . This observation suggests that torsional coupling may play an important role in genetic regulation , and might favor the orientation-dependent co-localization of genes involved in similar functions , which need to be expressed together . | [
"Abstract",
"Introduction",
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] | 2014 | Torsion-Mediated Interaction between Adjacent Genes |
Predictions about the fate of species or populations under climate change scenarios typically neglect adaptive evolution and phenotypic plasticity , the two major mechanisms by which organisms can adapt to changing local conditions . As a consequence , we have little understanding of the scope for organisms to track changing environments by in situ adaptation . Here , we use a detailed individual-specific long-term population study of great tits ( Parus major ) breeding in Wytham Woods , Oxford , UK to parameterise a mechanistic model and thus directly estimate the rate of environmental change to which in situ adaptation is possible . Using the effect of changes in early spring temperature on temporal synchrony between birds and a critical food resource , we focus in particular on the contribution of phenotypic plasticity to population persistence . Despite using conservative estimates for evolutionary and reproductive potential , our results suggest little risk of population extinction under projected local temperature change; however , this conclusion relies heavily on the extent to which phenotypic plasticity tracks the changing environment . Extrapolating the model to a broad range of life histories in birds suggests that the importance of phenotypic plasticity for adjustment to projected rates of temperature change increases with slower life histories , owing to lower evolutionary potential . Understanding the determinants and constraints on phenotypic plasticity in natural populations is thus crucial for characterising the risks that rapidly changing environments pose for the persistence of such populations .
Evidence that climate change influences many properties of wild populations of animals and plants is now ubiquitous [1]–[4] . As a consequence , there is widespread concern about the demographic and evolutionary effects of changing climate for the long-term viability of populations . A popular approach to study the impact of climate change on population viability is the use of “climate envelope models” or “niche models . ” These models take environmental correlates of species presence , combined with climate change projections , to predict range shifts and extinction rates ( e . g . , [5]–[7] ) . However , such projections do not take a population's ability to adapt to changing environmental conditions into account [8]–[10] . Further , since habitat fragmentation potentially constrains range shifts to track the optimal environment , populations of many species will have to adapt in situ to a changing environment to avoid extinction . Such models may therefore not be ideally suited to predict sustainable rates of climate change for existing populations . In contrast , mechanistic population models focus specifically on those population attributes that underlie population persistence . By assessing how phenotypic traits that influence population growth rate are affected by environmental variables , predictions of the fate of populations under varying rates of environmental change can be made [11] , [12] . Recently , Chevin et al . [13] proposed a mechanistic population model that predicts the critical rate of environmental change that allows long-term population persistence by local adaptation . The main novelty of the model lies in the fact that it allows local adaptation by both genetic change ( i . e . , micro-evolution ) and phenotypic plasticity ( the potential for a given genotype to be expressed differently in different environments [14] ) . Since phenotypic plasticity is currently recognized as being responsible for the majority of adaptive phenotypic changes in response to climate change [15]–[18] , this model is an important step forward in predicting effects of climate change on population persistence . The model combines demographic population properties ( e . g . , generation time , maximum intrinsic growth rate ) with quantitative genetic measures ( e . g . , additive genetic variance , strength of stabilising selection on traits sensitive to climate change ) , and allows for phenotypic plasticity by incorporating the effect of the environment on the trait . Since the purpose of the model is to make predictions about the fate of wild populations , the required parameters should ideally also be estimated using data from those same populations . To do so may be challenging , as it requires long-term data describing responses to the environment , as well as extensive pedigree and fitness data , a combination of information typically only found in long-term studies of marked individuals [19] . A long-term population study on great tits ( Parus major ) breeding in Wytham Woods near Oxford ( UK ) offers a rare opportunity to parameterise the model of Chevin et al . [13] for a single population , and hence to investigate the projected effects of climate change on population viability allowing for plasticity and evolution . For many wild bird species—both marine and terrestrial species—reproduction is restricted to a short annual period , in which there is sufficient food available to meet the needs of offspring production . This period varies annually and is set by the responses of lower trophic levels to abiotic factors , which are ultimately shaped to maximise productivity [20] , [21] . Although timing of this period is sensitive to ambient temperature , there is no a priori expectation that different trophic levels respond similarly to change in temperature . Hence , climate change has the potential to upset synchrony between food availability and timing of reproduction in birds , which may have important consequences for population viability [20] , [21] . Successful reproduction in great tits depends to a large extent on synchronization of offspring food demand with a brief annual peak in caterpillar abundance . This can be achieved by individual adjustment of laying date to early spring temperature , which predicts the timing of the peak in food availability [22] . Repeated observation of females breeding in multiple years yields observations of individual laying dates under different spring temperatures , providing a measure of phenotypic plasticity , or the “reaction norm” to temperature [23] , [24] . In addition , long-term monitoring of the annual timing of peak abundance of caterpillars feeding on newly emerged pedunculate oak ( Quercus robur ) leaves provides an estimate of how the optimal great tit laying date changes with temperature . An estimate of the optimum derived from an independent aspect of the environment is preferable to one derived from direct observations of birds , as it is unaffected by a potential constitutive cost of plasticity or differences in intrinsic individual quality of birds with different laying dates . Here we parameterise Chevin et al . 's [13] model with estimates from the long-term study of Wytham Woods' great tits , and so calculate the maximum rate of sustained change in early spring temperature that allows long-term persistence of this population . We also use the model to explore the dependence of population persistence on currently observed phenotypic plasticity , and further to explore the interactions between life-history variation and plasticity as a key element in persistence of populations facing environmental change . Our aim was thus to use the model as an heuristic tool to understand the importance of phenotypic plasticity in adaptation to climate change .
Inter-annual changes in the spring temperature experienced by individuals had , as expected , a pronounced effect on great tit laying date ( χ2 = 101 . 25; Δdf = 1; p<0 . 001 ) with individual females laying an estimated 4 . 98 ( ±0 . 49 standard error [SE] ) days earlier for each 1°C rise in spring temperature ( Figure 1 ) . The within-individual response to spring temperature was similar to the difference in laying date between individuals that experienced different spring temperature , as averaged over all their reproductive attempts ( estimate ± SE = −4 . 31±0 . 50; χ2 = 75 . 39; Δdf = 1; p<0 . 001 ) , indicating that the relationship between annual population average laying date and spring temperature is predominantly caused by phenotypic plasticity ( Figure 1 ) , as found previously [22]; note that any evolutionary response to selection would be captured in the between-individual term . Phenotypic plasticity in response to increasing mean spring temperature has resulted in an advance of average laying date by about 2 wk in the last half century [22] . Caterpillar half-fall date ( an index for timing of peak food availability; see “Materials and Methods” ) also reacted strongly to spring temperature ( χ2 = 90 . 10; Δdf = 1; p<0 . 001 ) , with half-fall date advancing an estimated 5 . 30 ( ±0 . 56 SE ) days per 1°C rise in spring temperature ( Figure 1 ) , a rate only slightly more rapid than the response of great tits over the same period . The effect of spring temperature on half-fall date did not change over time ( spring temperature×year; estimate ± SE = −0 . 05±0 . 04; χ2 = 1 . 57; Δdf = 1; p = 0 . 21 ) , and we thus assume that the reliability of spring temperature as a cue for the optimal laying date has been constant . Overall we conclude that the response in laying date of individual great tits to spring temperature ( corresponding to b in Chevin et al . 's model; see Table 1 ) closely matches the optimal response ( the term represented by B in their model ) . Combining parameter estimates for Chevin et al . 's model ( Table 1 ) , the Wytham great tit population is predicted to be able to adapt to a maximum long-term rate of increase in spring temperature of 0 . 47°C y−1 , i . e . >15 times the rate of temperature change of 0 . 030°C y−1 predicted under a high emissions scenario for this location and time in the annual cycle [25] . However , this estimate does not take uncertainty in parameter estimates into account . To calculate the probability that the modelled critical rate of change ( ηc ) will fall below 0 . 030°C y−1 while accounting for parameter uncertainty , we ran 100 , 000 simulations , with each simulation randomly sampling from a normal error distribution of parameters σ2h2 , γ , T , B , and b . This resulted in an estimated probability of 0 . 001 that ηc falls below 0 . 030°C y−1 ( Figure 2a ) , and hence again very little likelihood of extinction due to predicted temperature change . If we assume that there is no phenotypic plasticity in great tit laying date ( hence: |B−b| = 5 . 30 ) the point estimate of ηc is 0 . 028°C y−1 , with a 60% probability of population extinction ( ηc<0 . 030 ) when the error around the parameter estimates of σ2h2 , γ , and T is taken into account ( Figure 2b ) . Hence , the likelihood of population persistence in a changing environment depends heavily on the presence of phenotypic plasticity , as extinction risk is >500-fold higher in the absence of phenotypic plasticity . We explored the sensitivity of the probability of population extinction for other species with different life histories , assuming similar rates of change in the environment ( see Discussion ) , by varying the demographic and life-history parameters T ( generation time ) and rmax ( maximum rate of annual population growth ) while holding other parameters in the model constant; these effects are illustrated with contour plots in Figure 3a and 3b . This exercise revealed that with a difference in observed and optimal reaction norm equivalent to that seen in Wytham great tits ( |B−b| = 0 . 32 ) , which we take as indicative of a population showing close matching to the environment ( note that , when |B−b| = 0 [perfect tracking of the environment] , ηc is undefined ) , the model suggests little concern about a population being unable adapt to a rate of environmental change equivalent to an increase in spring temperature of 0 . 030°C y−1 , over most of the range of T and rmax ( Figure 3a ) . However , since the fundamental life-history trade-off between survival and reproduction leads , in general , to a negative correlation between T and rmax [26] , [27] , organisms with the slowest life histories ( i . e . , high T , low rmax ) are , even with quite close phenotypic matching ( Figure 1 ) , not far from the region at which risk begins to be appreciable . It is not plausible that great tit life history parameters such as generation time would evolve rapidly enough to the extent that the risk of population extinction would become substantial with the observed phenotypic plasticity . However , by setting phenotypic plasticity to zero ( |B−b| = 5 . 30 ) , we can explore the importance of phenotypic plasticity , and the extinction risk given these rates of environmental change , across the life-history continuum for other birds . Plotting T and rmax values for 13 species of birds [28] in Figure 3b shows a general pattern ( rmax = 0 . 92T−0 . 92 ) under which populations of other species with longer generation times are much less likely to adapt to increasing temperatures in the absence of phenotypic plasticity , assuming that the quantitative genetic parameters determining evolvability ( σ2h2 and γ ) are similar to that of the studied population of great tits ( see also Figure 4 ) . We then explored the sensitivity of our conclusions to varying evolvability of populations while holding other quantities constant . Figure 3c shows that , with the observed life history and phenotypic plasticity in laying date , our conclusions about the ability of this great tit population to adjust to the high emissions scenario projected temperature change of 0 . 030°C y−1 are quite robust to variation in the estimated genetic variance ( σ2h2 ) in laying date and strength of stabilising selection ( γ ) on laying date . In the absence of phenotypic plasticity , the population is at the threshold at which the additive genetic variance ( σ2h2 ) in laying date is insufficient for the population to remain viable ( Figure 3d ) . Equally , if the strength of stabilising selection on the match with the environment were weaker , extinction risk would also be elevated . However , in general it appears that a relatively fast life history provides sufficient potential to considerably reduce the risk of population extinction due to climate change .
In this study we explored the viability of a well-studied wild bird population to changes in climate predicted to the end of this century , by parameterising a mechanistic model by Chevin et al . [13] . We further explored the dependence of population viability on phenotypic plasticity as a form of adaptation to the environment , and the extent to which these conclusions depend on life history , and on evolvability . Our general conclusions are that the importance of phenotypic plasticity in adaptation to climate change is strongly dependent on life history . Short-lived species , with high reproductive rates , are more resilient to expected rates of climate change even with relatively little phenotypic plasticity , and while phenotypic plasticity is likely to be an adaptive response to environmental uncertainty in such species , it is not the only potential form of adaptation to climate change unless generation time encompasses multiple years and the rate of reproduction is slow . While the parameters we fitted to the model were determined by the specific details of our study system , we discuss below the extent to which our conclusions can be generalised . Like all models , the model by Chevin et al . [13] makes assumptions to simplify reality . For example , the model assumes no stochastic variation in optimal timing of reproduction . Stochastic variation occurring over time scales shorter than a species' generation time can only be countered with phenotypic plasticity , and as such the model may underestimate the importance of phenotypic plasticity . Our conclusions should therefore be interpreted with respect to long-term directional climate change only , assuming that population demography is buffered against environmental stochasticity . Such buffering , in the present system , may be accomplished by the fact that generations overlap and adult survival is largely independent of the match with the environment [29] , [30] . This possibility is not accounted for by the model as it assumes non-overlapping generations . Further , if adult survival is independent of the match to the environment , any evolutionary response to directional change is likely to be retarded . Moreover , in applying the model we have assumed that both the response to environmental cues and the dependence of the environment on climate can be extrapolated outside the ranges currently observed . In the case of the three trophic levels studied here ( oaks , caterpillars , and great tits ) the possibility remains that they exhibit differential phenotypic responses or physiological tolerances to increased temperature . If so , it is questionable whether the degree of matching can be assumed to be fixed over time . In this respect it is noteworthy that the model also allows for overcompensation , which would be just as detrimental as under-compensation , and causes a modification of predictions when parameter error is incorporated , as this results in a skewed error distribution of |B−b| ( Figure 2a ) . Although we incorporated error in parameter estimates for our predictions of extinction probability , this does not exclude the possibility that certain parameters and associated errors are systematically over- or underestimated . Estimates of the additive genetic variance for laying date in birds have been derived in several ways , from different study species with a range of life histories ( reviewed in [31]; see also Text S1 for further discussion ) . While there is considerable variability in the estimates , it is likely that many estimates are inflated by a failure to control effectively for common environmental effects between relatives , which can be expected to be considerable for a trait with a strong link to environmentally determined phenology ( see also [32] , [33] ) . In this study we used an estimate of σ2h2 derived from a very low heritability estimate ( 0 . 03 ) from an animal model controlling for several types of environmental variance [31] . We suspect that estimates of the additive genetic variance for time of breeding will be closer to this value than many previous estimates once appropriate environmental control is built into models . Sex-limited expression of traits will reduce the response to selection . While laying date is a phenotype only expressed by pairs of birds , in many , but not all , species it is primarily determined by the female [34] . Hence , the predicted evolutionary response to selection can be over-estimated if sex-limitation is not considered . The strength of stabilising selection on timing of breeding used here ( γ ) is more likely to be an underestimate as this is based on observational data at the level of the population . Two likely additional sources of stabilising selection that are not considered by such data result from , first , the extent to which individuals optimise timing of breeding to the phenology of their local environment . If there are different optima for different locations , then birds in the tails of the population phenotypic distribution may be closer to their local optimum than assumed: hence phenotypes should be measured at the appropriate relative scale . A second effect that will underestimate stabilising selection is the extent to which apparent directional selection on laying date results from phenotypic covariance between other aspects of individual quality and breeding date [35] . Figure 3d suggests that , if the match between organisms and the environment is poor , the outcomes of the model may be sensitive to variation in the strength of stabilising selection , or the additive genetic variance . However , the model assumes a fixed strength of stabilising selection , whereas it might be expected that as the match between a population and a changing environment became poorer , the strength of stabilising selection would increase . Lastly , the estimate of rmax ( 0 . 49 ) employed here may be an underestimate , as this does not include immigrants , which compensate for recruits that have dispersed from the population [28] , [36] . In summary , with the other parameters being relatively straightforward to estimate , any systematic bias in parameter estimates is most likely in the direction such that the potential for micro-evolutionary adjustment to climate change is underestimated . Extrapolating the model using parameters derived from a single great tit population to other bird species suggests that species at the faster end of the life-history continuum would have sufficient evolutionary potential to adapt phenology to a temperature change of the order of 0 . 030°C y−1 ( Figures 3a , 3b , and 4 ) . The predicted rates of change for the study area from United Kingdom Climate Projections 2009 ( UKCP09 ) [25] are broadly comparable to predicted rates of global temperature change , as IPCC [37] scenarios predict similar or less temperature change for this century . However , how representative are the parameter estimates derived from this single population for other species and populations ? Current knowledge suggests that evolutionary potential of most bird species in terms of phenological adaptation should be broadly similar , since heritability for laying date is not likely to be much greater than the value used here [31] , and predictions are not very sensitive to values of γ ( Figures 3c ) . While heritability may decrease under adverse environmental conditions [38] , [39] the opposite may also apply [40] , [41] and at present there is no evidence of climate-related dependence of the heritability of laying date in our study population [40] , [42] . Estimates of the optimal phenotypic response to changing environmental conditions ( in the present study , the optimal response in laying date to temperature [B] , as determined from the response of the timing of caterpillar peak abundance to temperature ) are not widely available . An estimate of B for another very well-studied Dutch population of great tits is lower than the one for our population ( −4 . 01 versus −5 . 30; [43] ) , and this is a population for which the phenotypic response of the birds is also lower ( see [40] for a comparison ) , suggesting that |B−b| would be larger than in the Wytham population . To the best of our knowledge , there are few comparable estimates from other systems , though see [44] . In general , one can expect that optimal responses are determined by the response of lower trophic levels in the food chain [21] , [45] . In that respect , observations for 1 , 558 largely Northern hemisphere wild plant species suggesting an average advance in spring leafing and flowering of 5–6 d per °C [46] , suggest that our estimate of B ( which is also in units of days per °C ) is quite representative of terrestrial systems in the Northern hemisphere . Rates of change in higher trophic levels ( i . e . , b ) may be more variable . A large-scale analysis of data from three decades across environments in the UK by Thackeray et al . [3] suggested that while primary producers and consumers have shown broadly comparable rates of advance with climate change , secondary consumers have on average advanced at only about half the rate . Hence , the general expectation might be that B and b will not be very closely matched , and that a scenario intermediate to the two we modelled ( close match between B and b; no plasticity at all ) is most common . It should be noted that our conclusions are drawn from analysis of plasticity in phenology , and given considerable annual variability , phenological traits may have a very high degree of plasticity . Other traits , for instance thermal tolerance , or migration timing , might show less plasticity , but we are not aware of studies of other classes of trait that would support analysis in the framework used here . Recently a similar approach to calculate the risk of extinction for a Dutch population of great tits yielded a more pessimistic outcome [47] . This is predominantly caused by the combination of lower plasticity , weaker selection , and more extreme climate change scenarios ( up to 0 . 067°C y−1 ) [47] . However , in contrast with our study population , where average offspring recruitment is lower in years with stronger selection on relative laying date [22] and about 13% of annual population growth can be explained by the population's match with the food peak ( unpublished data ) , population growth is hardly affected by the match with the food peak in the Dutch population [30] , [47] , [48] . This illustrates that even when the match with the food peak is the single most important factor explaining relative fitness , other ecological processes that determine population growth or absolute fitness ( e . g . , density dependence ) —the effects of which on population viability in response to climate change are less straightforward to estimate—can potentially mitigate adverse population effects [30] , [48] . In contrast to cases where there is a close tracking of the environment , inability to adjust phenotypically to a gradual shift in optimal timing caused by climate change suggests very high risks of population extinction in species with long generation times ( Figures 3b and 4 ) . Such risks could potentially be buffered with higher evolvability , but we are unaware of any evidence for a link between life history and genetic variance . The greater vulnerability of species with slower life histories contrasts with predictions of Morris et al . [49] who suggested longevity should act as a buffer against climatic variability . This raises the question of whether longer-lived species will have already evolved a sufficiently plastic response in timing of reproduction , to variation in temperature , to cope with the relatively fast directional change that is predicted for the future . This is especially relevant as our results show that their long generation time limits their potential to respond with genetic adaptation to climate change . In conclusion , parameterisation of Chevin et al . 's [13] model with conservative estimates from an extensively studied wild bird population suggests little risk of extinction of that population due to future change in temperature as predicted by climate models . By varying terms in the model we estimated that the absence of phenotypic plasticity would increase the likelihood of population extinction approximately 500-fold . For birds with longer generation times , vulnerability to extinction is considerably higher even for only moderate mismatches of phenotypic plasticity with the rate of environmental change , as they may exhibit insufficient evolutionary potential to adjust to relatively fast change . For those species , phenotypic plasticity in timing of reproduction is likely to be by far the most effective mechanism to cope with constantly increasing temperatures . However , relatively less is known about the determinants and limits on plasticity in such organisms , and increased focus on this area , as well as work on the link between phenotypic plasticity and life history would be very valuable .
Great tits are small ( 14–22 g ) passerine birds , common in large parts of Europe , Asia , and Northern Africa [50] . They are socially monogamous and breed in cavities , but readily accept nestboxes , if provided . Wytham Woods ( Oxfordshire , UK , 51°46′ N 1°20′W ) consists of ca 385 ha mixed deciduous woodland with an excess of nestboxes ( n = 1 , 020 ) available since 1960 . On average 217 nestboxes are occupied annually by great tits [51] , although population size has increased in recent decades . Second broods are rare ( <3% ) and typically excluded from analyses ( e . g . , [22] ) . Data collection in the breeding season ( April–June ) consists of weekly nestbox checks in the laying phase to record first egg date ( here referred to as “laying date” ) and clutch size . Occupied nestboxes are checked every 2 d around the anticipated hatching date to infer hatching date and allow ringing of nestlings ( for future identification ) at a standard age of 15 d . At least 5 d later , nestboxes are checked for successful fledging of nestlings . Parents are caught in the nestbox while feeding nestlings , and identified by their ring , or newly ringed if immigrant . Recruits to the natal population are defined as locally hatched birds that were caught as a parent in subsequent years . For analyses in this paper , we use data collected between 1960–2010 , as field protocols were standardised over this period . Chevin et al . 's model [13] extends an earlier model by Lynch and Lande [11] , by incorporating plasticity in a phenotypic trait ( z , here first egg-laying date ) that mediates adaptation to a changing continuous environmental parameter ( ε , here temperature ) . It predicts the maximum rate with which ε can change ( at a constant rate in time ) to allow long-term population persistence , referred to as the critical rate of environmental change ( ηc ) . In the original model [11] ηc depended only on the phenotypic variance ( σ2 ) in z , the heritability ( h2 ) of z ( together comprising the additive genetic variance for z ) , the strength of stabilising selection ( γ , [52] ) on z , and the maximum intrinsic rate of population growth ( rmax ) . Note that γ refers to selection on unstandardised phenotypic variation , assumes the absence of strong directional selection , and a positive value represents stabilising selection , rather than disruptive selection . The extended model also includes the species' generation time ( T ) , with T being expressed on the same units of time scale as ηc and rmax ( here in years; rmax is measured in years−1 ) . Furthermore , it includes the environmental sensitivity of selection ( B ) , which reflects how the optimal value of z ( laying date ) depends on ε ( temperature ) , and the degree of phenotypic plasticity or reaction norm ( b ) , which quantifies the effect of ε on z , within individuals . Altogether the critical rate of change is modelled as:We refer to Chevin et al . [13] for a more detailed description of the model and its rationale . We used a range of previously published estimates and new analyses to parameterise the model , all of them specific to the Wytham Woods study population . All parameter estimates are listed in Table 1 and , for cases where we used previous estimates from this population , we refer to Figure S1 , Text S1 , and the specific publication for exact methodological details . Some parameters have been estimated multiple times , and can vary because of different data inclusion criteria , different time spans , different assumptions , or different statistical estimation procedures . In such cases we used the most recent estimate of the respective parameter , as these generally used most data , and employed the most appropriate estimation procedures ( see Figure S1 and Text S1 for more discussion ) . We estimated the strength of stabilising selection on laying date ( γ ) with the following equation: − ( ω2+σ2 ) −1 = γ−β2 [53] . The width of the fitness function ( ω ) for laying date was estimated by calculating year-centred laying dates ( i . e . , subtracting annual average laying date , n = 8 , 646 laying dates in 51 y ) , categorising them in 10 equally spaced intervals , and calculating the average number of recruits per breeding attempt for each category . A Gaussian function ( Figure S1 ) was fitted to these average numbers and ω was estimated as the “standard deviation” of the function ( ω = 11 . 62 ) . Phenotypic variance ( σ2 ) in laying date was estimated as the average of all annual values ( σ = 5 . 39 ) . Since the model by Chevin et al . [13] assumes that the population is initially well adapted , we set the strength of directional selection ( β ) at zero , and calculated γ as −0 . 0061 . The assumption of an initially well adapted population , and thus zero directional selection , is required by the model , yet depending on the match with the food peak there can be strong directional phenotypic selection on laying date observed [22] . Since we have no indication that the population is currently poorly adapted , the observed phenotypic selection on laying date may be biased by phenotypic covariance between other aspects of individual quality and laying date ( see also Discussion ) . Using a bootstrapping procedure we estimated the standard error of γ as 0 . 0010 . Note that we use the absolute value of γ in the model . A recent study by Husby et al . [40] showed that the average temperature between 15 February and 25 April ( here referred to as “spring temperature” ) is the best predictor of average annual laying date; we thus used the individual response in laying date to this environmental variable as an estimate of phenotypic plasticity , and the response in the date of standardised caterpillar abundance as an estimate of environmental sensitivity ( see details below ) . A similar exercise to that of Husby et al . [40] had been performed earlier , but based on a longer time series and a slightly different environmental variable , i . e . , “warmth sum” ( the sum of the daily maximum temperatures between 1 March and 25 April , [22] ) . We chose to conduct analyses with the average temperature , as used by Husby et al . [40] , to permit more straightforward comparison between the modelled critical rate of environmental change and predictions about future climate change; see [22] for detailed information on how great tit laying date and peak caterpillar abundance date have changed over time . We used the daily average of minimum and maximum temperatures ( in °C ) that were collected by the Radcliffe Observatory in Oxford , 5 km east of Wytham Woods , for our measure of spring temperature . The date by which 50% of the seasonal total of winter moth caterpillars ( Operopthera brumata larvae , the main source of food for great tit nestlings; [54]–[56] ) had descended from trees to pupate on the ground ( here referred to as “caterpillar half-fall date” ) was recorded in Wytham Woods in the majority of years from 1961 onwards ( n = 43 ) , and gives a good indication of the timing of the peak in caterpillar biomass ( see [22] for more details ) . Given a fixed period between great tit laying date and peak offspring food demand , this serves as a proxy for the optimal response in laying date to spring temperature [22] . Hence , environmental sensitivity of selection ( B ) was accordingly calculated as the slope of the linear function of caterpillar half-fall date in response to spring temperature . Phenotypic plasticity , or the average within-individual response in laying date to changes in spring temperature , was calculated from a dataset restricted to females that bred at least twice ( n = 4 , 742 reproductive attempts of 1 , 874 females , in 51 y ) . The within-individual slope was calculated by using the difference between the spring temperature a female experienced before a specific reproductive attempt with the average of the spring temperatures a female experienced before all her reproductive attempts , as explanatory variable in a model on laying date ( following [57] ) . In the model we also included the average of the spring temperatures a female experienced before all her reproductive attempts as explanatory variable , to account for potential micro-evolution or selective ( dis ) appearance of individuals with higher , or lower , average spring temperature experience . Female identity , year , and sector of the wood ( Wytham Woods consists of nine different sectors with different vegetation types and management regimes , see [58] ) were included as random effects , to correct for an uneven distribution of repeated measures of individuals , inter-annual variation ( not due to spring temperature ) and environmental heterogeneity , respectively . Models were fitted with a normal error distribution and a Markov Chain Monte Carlo estimation algorithm with 100 , 000 iterations , using MLwiN version 2 . 02 [59] , [60] . Significance of explanatory terms was determined using the Wald statistic , which approximates the χ2 distribution . We used projections from the United Kingdom Climate Projections 2009 ( UKCP09 , [25] ) to compare our results against the predicted rate of average temperature change for the Wytham Woods area . To this end , we used the average temperature change predictions for the 25-km grid box that contained Wytham Woods ( number 1 , 547 ) for the 2070–2099 time period , under the low , medium , and high emissions scenario , for the months February , March , and April . We weighted the predictions per month according to their number of days contained in our measure of spring temperature ( see above ) . To calculate an annual rate of change we used the midpoint of 2070–2099 relative to the midpoint of the baseline period ( 1961–1990 ) . This resulted in a predicted rate of increase of spring temperature of 0 . 021 , 0 . 025 , and 0 . 030°C y−1 for the low , medium , and high emissions scenario , respectively . | Predictions about the effect of climate change on organisms often ignore the possibility that organisms can evolve , or that they have an inbuilt capacity to cope with changing conditions . In order to understand the potential for existing populations to adapt to climate change , and the relative risks of extinction , such processes need to be modelled together with projected changes in climate . In this paper , we use data from a long-term study ( 51 years ) of a small bird , the great tit , to model how birds can match the time they breed each year with the time their food is most abundant , and how this match can change with a changing climate . We found that evolution offers the chance for short-lived birds to adapt at the rate of climate change that is expected over the next century , but that the most important way that birds can cope with climate change is their evolved ability to adjust their behaviour depending on the environment they experience ( “plasticity” ) . We extrapolated the model to other bird species , to estimate their relative vulnerability to changing climate . The model shows that longer-lived species ( which also tend to have fewer offspring and take longer to reach sexual maturity ) are more vulnerable to extinction because their evolutionary potential is lower . For such species , the importance of close adjustment to their environment becomes even greater . Hence , knowledge of the causes and limits of individual adjustment to the environment are crucial to predict the fate of populations under climate change . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
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"ecology"
] | 2013 | Quantitative Assessment of the Importance of Phenotypic Plasticity in Adaptation to Climate Change in Wild Bird Populations |
Synonymous constraint elements ( SCEs ) are protein-coding genomic regions with very low synonymous mutation rates believed to carry additional , overlapping functions . Thousands of such potentially multi-functional elements were recently discovered by analyzing the levels and patterns of evolutionary conservation in human coding exons . These elements provide a good opportunity to improve our understanding of how the redundant nature of the genetic code is exploited in the cell . Our premise is that the protein segments encoded by such elements might better comply with the increased functional demands if they are structurally less constrained ( i . e . intrinsically disordered ) . To test this idea , we investigated the protein segments encoded by SCEs with computational tools to describe the underlying structural properties . In addition to SCEs , we examined the level of disorder , secondary structure , and sequence complexity of protein regions overlapping with experimentally validated splice regulatory sites . We show that multi-functional gene regions translate into protein segments that are significantly enriched in structural disorder and compositional bias , while they are depleted in secondary structure and domain annotations compared to reference segments of similar lengths . This tendency suggests that relaxed protein structural constraints provide an advantage when accommodating multiple overlapping functions in coding regions .
The rapid development of comparative genomics approaches along with the fast increase in the number of sequenced genomes provides us with a clearer view on evolutionarily conserved and hence potentially functional genome regions [1] . All the underlying approaches are based on the notion that mutations affecting functionally important regions are deleterious and hence are likely to be eliminated from the population by purifying selection , while mutations affecting ‘junk DNA’ are neutral and can accumulate during evolution [2] , [3] . The increase in the number of sequenced genomes supports the discovery of new functional elements of different types [4]–[8] by enhancing the power and resolution of detecting constrained regions [9]–[13] . However , these depend not only on the number but also on the diversity of species compared [14] . Sequences from closely related organisms might simply not have had enough time to change and hence they can be mistakenly assigned as conserved without functional importance . On the other hand , alignments from distantly related genomes are suitable for detecting constrained genome regions , although they may overlook recently evolved functionalities . A recent comparative genomics study of 29 mammalian species identified constrained elements that cover 4 . 2% of the human genome [15] . Since 20 of the 29 genomes were selected and newly sequenced for the analysis , the power of detecting evolutionary constraints was largely improved compared to previous approaches [16] , [17] . In the resulting robust genomic alignment , the levels and patterns of evolutionary conservation reflected the number and type of different functionalities fulfilled by a given genome region . Lindblad-Toh and colleagues applied phylogenetic codon models to find small windows in known open reading frames ( ORFs ) that exhibited unusually low rates of synonymous substitution and identified a surprisingly large number ( ∼10000 ) of synonymous constraint elements ( SCEs ) within human coding exons [15] . SCEs are protein-coding regions in which synonymous mutation rates are extremely low compared to the average rate of the complete ORF in which they are located , as well as compared to the average rate of the given ORFome , indicating additional sequence constraints beyond those dictated by the structure and function of the protein [15] , [18] . These additional constraints most frequently stem from the demands of regulatory sites involved in translation initiation and transcript splicing . SCEs can also contain target sequences for miRNAs , or sequence-specific DNA-binding proteins such as transcription factors . They could code for another protein segment in shifted reading frames ( dual-coding ) , for functionally important mRNA structures , or for non-coding/regulatory RNAs ( Figure 1 ) . Most of these potential overlapping functions are present among the examples described by Lin MF and colleagues [18] . In these cases , one can imagine that the DNA sequence bears signs of competing demands of 1 ) DNA function , 2 ) RNA function , and 3 ) protein function . The interplay between diverse functionalities could in principle result in DNA regions serving three or even more different needs . Interestingly , in these dual- or multi-functional DNA regions the changes in the amino acid sequence of the encoded protein segments are restricted by the second functionality , which could influence their capability to form structured elements and folded domains . The question is how the corresponding protein segments can overcome these difficulties . In our opinion , such protein regions might show rather relaxed structural constraints , i . e . enrichment in low sequence complexity or , at least , in structural disorder . Structural disorder in proteomes was discovered only a decade ago [19]–[22] , and since then intrinsically disordered proteins ( IDPs ) constitute a new , fast developing field of structural biology [23] . Intrinsically disordered regions ( IDRs ) , which function as ensembles of different conformations [22] , are well predictable based on their unique amino acid composition [20] , [24] , widespread in eukaryotic proteomes [25]–[27] , and are abundant in proteins of signaling and regulatory roles [19] , [28] . From an evolutionary point of view , due to their increased tolerance against mutations , IDRs undergo more rapid changes than globular domains [27] . Additionally , they are frequently subject to enhanced positive Darwinian selection [29] . Although proteins containing long IDRs are evolutionarily more constrained , IDRs themselves are less constrained and more enriched in single nucleotide polymorphisms ( SNPs ) than any regular secondary structure type [30] . The increased tolerance to mutations stems from the lack of defined secondary or tertiary structure and consequently reduced structural constraints , which predisposes IDRs to be more tolerant of restrictions affecting their coding sequences . For instance , multifunctionality in alternatively spliced gene regions that can give rise to distinct protein chains in different reading frames appears to correlate with protein disorder [31] . Here , we describe a comprehensive computational analysis of the structural preferences of protein segments encoded by potentially multi-functional gene regions . This work aims to provide a better understanding of the limitations of the genetic code in terms of encoded complexity through the detailed analysis of genomic sites that take advantage of its redundant nature .
Data on SCEs detected at three different resolutions have been downloaded from the webpage published in support of the 29 mammalian genomes project [15] , [18] . The provided genomic locations apply for the NCBI36/hg18 assembly of the human genome . The analysis was performed on all three datasets of 9 , 15 and 30 codon resolutions ( containing 11882 , 10757 and 8933 SCEs , respectively ) . We have used the programmatic access option of the Ensembl database [32] release 54 to find the protein segments corresponding to the listed SCE genomic locations . The exon segment ( s ) listed for each SCE were mapped onto the protein coding sequences ( CDSs ) of all transcripts of the given gene . A match against the canonical isoform's CDS had preference over the others and only one segment was accepted even in case of multiple matching transcripts . The boundaries of the match with the CDS explicitly defined the SCE-encoded protein regions; all residues with at least one nucleotide overlapping the SCE sequence were taken into account . In the majority of the cases the mapping could be performed directly , however , in some cases we had to use the Basic Local Alignment Search Tool ( BLAST; version 2 . 2 . 25 ) to locate the SCEs on the CDSs due to nucleotide mismatches . In these BLAST searches , soft masking and the dust option were switched off . In the case of segments coming from the 9- and 15-codon resolution datasets , the short option of nucleotide BLAST was applied . For a small fraction of the data ( 135 ( ∼1 . 14% ) , 120 ( ∼1 . 12% ) and 8 ( ∼0 . 1% ) data points for the 9 , 15 and 30-codon resolution datasets , respectively ) no reliable match between the SCE sequence and the corresponding CDSs was obtained due to multiple consecutive gaps . These cases were excluded from further analyses . The IUPred method ( long window option ) [33] was used to predict protein disorder , while regions of low sequence complexity were defined by SEG ( default parameters ) [34] , [35] . Secondary structure was assigned by PSIPRED v3 . 3 ( without using PSI-BLAST profiles ) [36] , and domains were identified by the PfamScan [37] tool using only the more reliable A-class domains/motifs/repeats/families listed in Pfam release 25 . Here , we briefly summarize the considerations that influenced our choice of prediction methods for this study . IUPred is a widely used disorder prediction method , one of the few that are freely available not only as a web server but also as a ready to install software package . It is fast and can smartly handle obstacles , such as letter codes of non-conventional amino acids or extremely long proteins , making it suitable for analyzing proteome-scale data . Most importantly , it is based on clear physical principles that allow for easy understanding and interpretation of its prediction results [33] . IUPred is thought to provide direct proof for the existence of structural disorder , relying purely on residue-residue interaction energies , without being pre-trained on protein disorder datasets [33] , [38] . Additionally , IUPred is considered to be rather conservative , which means that it is not prone to overestimate the abundance of structural disorder . Another feature that makes IUPred an ideal choice for the current study is that , in contrast to many other predictors , it does not take sequence complexity into account when estimating the disordered nature of a protein region , i . e . it is orthogonal to SEG . SEG is a widely used method for the identification of low sequence complexity segments , even applied as a pre-filtering step in BLAST searches [39] . SEG is based on a simple formula that describes the compositional complexity of a given sequence window with defined length and assigns it as low complexity if the calculated value is below a given cut-off [34] , [35] . Due to this , the prediction outputs provided by SEG are also easy to understand and interpret . Finally , PSIPRED is a popular secondary structure prediction method that is reasonably accurate and fast , and besides the web server , it also has a freely available version for local use . PSIPRED can be optionally run without creating PSI-BLAST profiles that enables predictions on proteome-scale data in reasonably short times . The structural properties of each protein segment ( SCE-encoded or reference ) were obtained by retrieving the corresponding values from the predictions of the full-length proteins . This way , the segments were studied in their natural sequence environment and systematic termini biases could be avoided . The following measures were used to describe the structural properties of the segments: 1 ) the fraction of disordered residues ( scoring ≥0 . 5 by IUPred ) , also referred to as disorder content , 2 ) the fraction of residues in low-complexity regions , 3 ) the fraction of residues in regular secondary structure elements ( helix or extended ) , also referred to as secondary structure content , and 4 ) the fraction of residues in any predicted Pfam entities . The segments were also grouped in a binary manner for each predicted structural property ( e . g . disordered/non-disordered ) ; we assigned a segment to a given structural property if at least 50% of its residues were predicted as such . Since PSIPRED failed to predict secondary structure for proteins larger than 10 , 000 residues , we had to exclude the titin gene [Ensembl 54: ENSG00000155657] and its products from our analysis to maintain the consistency of our data . Due to this reason , there were 13 , 9 and 6 SCEs excluded from the 9 , 15 and 30-codon resolution SCE datasets , respectively . For each SCE-encoded protein segment , a segment of equal length was randomly picked from the SCE-containing subset of human proteins in a way that the residue boundaries of the proteins were not exceeded . This way undesired reference segments containing artificially fused termini of two different proteins could be avoided . Consequently , we acquired one set of randomly selected reference segments for each SCE dataset and defined their structural properties as previously described . We looked for direct matches between the 15-codon resolution SCE-encoded sequences and the human DisProt 6 . 02 proteins [40] , and counted the overlaps with the annotated disordered regions . To gain suitable reference values , we randomly selected , for each human DisProt protein , one human canonical protein matching in length ( within +5% ) , and transferred the annotated disordered segment boundaries onto them . Then we matched the SCE-encoded sequences against the randomly selected proteins and counted the overlaps with the segment boundaries . This way , we could maintain the length distribution and the fraction of N- or C-terminal segments of the DisProt set within our random set . The whole procedure was repeated five times to gain multiple reference values . Then we used Yates' chi-square test to compare the median of the reference values ( expected ) to the tested value . We downloaded a set of 211 experimentally verified SFBSs from the SpliceAid-F database [41] that reside in human exons and span more than 4 but less than 50 nucleotides . After filtering out mutant genes and sites with redundant chromosomal locations , we obtained 64 unique binding sites . Out of these , 62 could be successfully mapped onto Ensembl transcripts . The two SFBSs in the FAS gene overlapped with several transcripts coding for two distinct protein chains ( due to two overlapping exons in shifted reading frames ) . Here , we accepted two transcripts per SFBS representing distinct coding frames . The corresponding protein segments were identified for all SFBSs , similarly as for SCEs , and their structural properties were calculated in the same way . The random selection of reference segments of equal length was also performed for SFBSs using the whole human canonical proteome . Since our datasets failed the Kolmogorov-Smirnov normality test , we applied Mann-Whitney U test to compare the properties of SCE-containing proteins ( represented by the 9-codon resolution dataset , the one with the highest number of entries ) with the human canonical proteome , and also to compare the four predicted structural properties of SCE-encoded and SFBS-encoded protein segments to those of their equivalent reference segments . Due to the multiplicity of comparisons between these datasets , Bonferroni corrections were applied , which resulted in lowered significance thresholds of p = 0 . 01 and p = 0 . 0125 , respectively . We also applied Yates' chi-square test to compare the SCE-encoded segment datasets ( observed values ) with their reference sets ( expected values ) using the number of at least 50% assigned segments in case of each structural property . Again , Bonferroni correction was applied when setting the significance thresholds ( p = 0 . 0125 ) . For testing the correlation between the structural properties of the SCE-encoded segments and the detection window size , we applied Spearman's correlation test . To show that the structural properties of the three SCE datasets differ we used Kruskal-Wallis tests . The differences were further analyzed by Dunn's multiple comparison tests . In the case of the SFBS data , the residue-level analysis was performed by Yates' chi-square test . We counted the overall number of residues of predicted disorder/low complexity/domain or secondary structure in SFBS segments and used these ( and their complementary values ) as observed values for testing . The expected values were obtained by multiplying the sum of SFBS segment lengths by the fraction of residues assigned to the given structural property in the whole canonical proteome . Bonferroni corrections were applied on the significance thresholds . GraphPad Prism 6 was used for statistical testing and preparation of Figure 2 . We have used the following Ensemble proteins as examples: HOXA2 [ENSEMBL 54: ENSP00000222718]; canonical BRCA1 [ENSEMBL 54: ENSP00000350283]; shorter BRCA1 isoform translated from the introduced alternative translation start site: [ENSEMBL 54: ENSP00000377288]; canonical FAS [ENSEMBL 54: ENSP00000360942] , non-canonical FAS in alternative reading frame: [ENSEMBL 54: ENSP00000318464]; CBP [ENSEMBL 54: ENSP00000371502] , and p300 [ENSEMBL 54: ENSP00000263253] .
The large collection of human SCEs ( three datasets representing detection resolutions of 9 , 15 and 30 codons ) was adopted from Lin et al [18] . Due to the stringent filtering criteria applied in detecting SCEs , we consider the published dataset as a collection of potentially multi-functional coding regions , and hence did not perform any further filtering steps . The SCEs were mapped onto human proteins and the structural properties of the resulting protein segments ( 11734 , 10628 and 8919 segments in the three datasets , respectively ) were determined by a variety of structure prediction methods . IUPred was used to predict structural disorder , SEG for low sequence complexity , and PSIPRED v3 . 3 for secondary structure . Pfam entities ( domains/families/motifs and repeats; hereafter collectively referred to as domains ) were identified by the PfamScan method . The predictions were always obtained for full-length proteins and the segments of interest were excised subsequently . The fractions of assigned residues were defined in each SCE-encoded protein segment for each structural property . All details on SCE-encoded protein segments are provided in the Supporting Information , Tables S1 , S2 and S3 for resolutions 9 , 15 and 30 codons , respectively . First , we compared the set of SCE-containing proteins with the whole human canonical proteome to identify an adequate reference dataset for statistical comparisons of the SCE-encoded protein segments . SCE-containing proteins were significantly longer , more disordered and enriched in low complexity regions compared to the proteome ( Figure S1 ) . Consequently , we used only this subset of proteins for obtaining reference segments , to ensure that the observed structural differences do not derive from the general distinctive characteristics of proteins containing SCE regions . The reference segments were randomly selected from SCE-containing proteins , preserving the length-distribution of the SCE-encoded segments , and their structural properties were determined as described above . Information on the randomly selected datasets is provided in Tables S4 , S5 and S6 for resolutions 9 , 15 and 30 codons , respectively . The number of segments with 50% or more residues assigned to a given structural property was compared between the SCE-encoded segments and the reference segments ( Figure 2 ) . Statistical comparisons showed that significantly more SCE-encoded protein segments of high resolution ( 9 and 15 codons ) are structurally disordered and compositionally biased than reference segments , while there are less SCE-encoded protein segments assigned with secondary structure and annotated domain regions ( Yates' chi-square tests ) . In case of the low , 30-codon resolution , however , the differences between the numbers of SCE and reference segments calculated for relative domain overlaps and structural disorder were below the threshold of statistical significance ( Figure 2A , 2C ) . The fractions of residues positively assigned with the structural properties were also directly compared between the SCE-encoded and reference segments using Mann-Whitney U test ( Figure S2 ) . The results of this approach were in agreement with the results described above and confirmed the previous analysis . Data on these statistical analyses are provided in Tables S7 and S8 . Three different datasets were obtained by varying the window size when screening the genome for SCEs [18] . The above described differences between the structural properties of the SCE and reference datasets seemingly increased with decreasing window size , i . e . increasing resolution ( Figure 2 ) . To further investigate this relationship , we applied different statistical approaches . First , we made an attempt to choose one descriptive value for each structural property that represents the distribution of the data well , which was then correlated with the window size used for SCE detection . We used the third quartile ( 75th percentile ) for structural disorder , the median for secondary structure , and the 90th percentile for low sequence complexity . Because of their binary nature , data on domain content could not be represented by a single value and hence were not correlated with the window size ( small segments are located either within or outside of domains but rarely at the borderlines ) . Spearman's correlation showed that each structural property can be described as a monotonic function of the detection window size . Disorder and low sequence complexity content increased with decreasing window size and therefore gave a negative Spearman's rank correlation coefficient ( r = −1 in both ) , while the correlation between secondary structure content and window size was positive ( r = 1 ) . These values demonstrate the monotonic relationship between the structural properties and window size , but , since there are only three data points corresponding to the three windows applied , we additionally used a direct approach to analyze the differences between the whole datasets . For each investigated structural property , we applied Kruskal-Wallis test to see whether the three datasets significantly differ . Dunn's multiple comparison tests were used to further study these differences and they showed that each dataset significantly differs from the other two , considering both low sequence complexity and secondary structure content . The 9- and 15-codon resolution datasets did not differ significantly in disorder and domain residue content . However , the 9- and 30-codon resolution datasets showed significant difference in all four properties ( Table S9 ) . Since the reference datasets showed only negligible differences in their structural properties ( Figure 2 , Figure S2 ) , we can assume that the above described significant structural differences stem from the multi-functional nature of SCEs and are not due to the difference in their length distributions . This correlation between window size and detected structural properties is expected due to the short length of regulatory elements . In fact , most regulatory elements on both , the DNA- ( e . g . transcription regulatory sites ) or RNA- ( e . g . translation initiation and splicing regulatory sites ) levels are usually less than 15 nucleotides in length , which is shorter than the window size of the highest resolution detection . This means that at larger window sizes the actual SCE covers only a small fraction of the window ( 15 and 30 codons ) , i . e . the measured structural property represents a mixture of synonymously constrained and single constrained regions , making it difficult to sort them out . Considering this , the gradual diminution of structural bias with window size supports our original assumption that protein-coding sequences under selection for overlapping functions are subject to locally reduced structural constraints . The presence of this relationship in our datasets also provides good support for our approach and indicates its specific nature . We directly matched the 15-codon resolution SCE-encoded protein sequences onto human proteins in DisProt 6 . 02 , the database of experimentally verified disordered protein segments . We found 67 matches that completely ( 40 ) or partially ( 27 ) overlapped with the annotated disordered segments . Applying equivalent random reference sets ( see Methods ) instead of DisProt , we obtained 23 , 29 , 40 , 41 and 43 matches ( median = 40 ) , i . e . , DisProt regions contain significantly more SCEs than expected by chance ( Yates' chi-square test , p = 2 . 693E-05 ) . The SCE datasets used for the above statistical analyses were generated by the in silico detection of low synonymous mutation rates in the genome which resulted in a large amount of data providing suitable statistical power for the analyses . Unfortunately , the size of the datasets did not allow for individual observations and experimental verification of the potential secondary functionalities in the identified regions . Therefore , a smaller set of experimentally validated exonic SFBSs was used to probe into the structural properties of protein segments overlapping with multi-functional coding regions . The frequent occurrence of splicing regulatory sites in the coding regions of human mRNAs is one of the most prominent factors contributing to the large number of detected SCEs [18] , which makes them ideal candidates for a more detailed analysis . A set of human exonic SFBSs verified in binding and splicing assays has been downloaded from the SpliceAid-F database and filtered for length and redundancy . Finally , 64 single-nucleotide resolution binding regions were mapped onto protein-coding Ensembl transcripts ( out of these , only three overlap with SCEs , so we can consider these datasets as independent ) and the corresponding protein segments were subjected to similar structural analyses as previously described for SCEs ( details are provided in Table S10 ) . The comparison of the structural properties of SFBS-overlapping protein segments with the corresponding reference set showed enrichment in structural disorder and depletion in predicted secondary structure . Due to the considerably smaller size of this dataset , the observed tendencies are not as pronounced as in the case of SCEs , but they are still statistically significant ( Mann-Whitney U tests; p-value = 0 . 003 and p-value = 0 . 011 for disorder enrichment and secondary structure depletion , respectively ) . In domain annotations and low sequence complexity content , on the other hand , they showed no significant difference from the reference ( Mann-Whitney U tests; p-value = 0 . 090 and p-value = 0 . 422 , respectively ) . A general bias in experimental data towards domain regions of proteins is probably the cause of the slight enrichment of SFBS-overlapping protein regions in domain residues . This “domain-bias” in experimental research is possibly the result of the preferential investigation of mRNAs which carry mutations potentially causing splicing defects that affect the functionality of the encoded protein and thus cause disease . The SpliceAid-F database is rich in data derived from splicing assays carried out with mutated genes , supporting this explanation . In contrast to disordered regions , functional domains are more sensitive to alterations , including splicing defects as well as single-residue changes . This is due to the fact that the functionality of domains depends usually strictly on structure and the change of one critical residue can result in the loss of structural stability and impair function . IDRs , on the other hand , are more robust and , because their functionally important residues are only located in short stretches ( short linear motifs ) , less affected by missense mutations . In accord , we can assume that in our SFBS set the relatively frequent overlaps with domain annotations are caused by the bias in selecting mRNA segments for experiments , and not by the biased nature of SFBS in general . The SFBS-encoded protein regions did not differ significantly from the random set in their low sequence complexity content ( Mann-Whitney U test; p-value = 0 . 422 ) , which is again probably due to the domain bias and the fact that the default window size of the SEG algorithm is 12 residues , more than twice the size of protein fragments overlapping with SFBSs ( mean = 5 . 5 residues , median 4 = residues ) . This latter problem , unfortunately , cannot be overcome by substantially decreasing the window size of SEG for our purpose , because it would compromise the reliability of the method . We additionally compared the structural properties of the SFBS-encoded protein segments and the human proteome at the single-residue level . The SFBS-overlapping protein residues show an almost two-fold enrichment in structural disorder ( Yates' chi-square test; chi-square = 114 . 161; p = 0 ) and an approximately 1 . 5-fold enrichment in low sequence complexity ( chi-square = 10 . 909; p = 9 . 6E-04 ) . Also , they display a strong depletion in secondary structure of approximately 2/3 ( chi-square = 32 . 1; p = 1 . 0E-08 ) and 1 . 5-fold enrichment in residues with domain annotations ( chi-square = 66 . 613; p = 0 ) . The second functionality of SCEs - besides protein coding - is defined in only a few cases . Here , we list some well-known examples of different types of overlapping functionalities together with their protein structural properties . The Hox genes are rich in SCEs , primarily because of the large number of expression regulatory elements embedded in their coding exons [18] . In HOXA2 , protein coding overlaps with two distinct synonymously constrained regions ( both detected at all three resolution levels ) , each covering previously described enhancer elements that act in distinct regions of the developing brain ( Figure 3 ) . In overlap with residues 35–38 , a highly conserved HOX-PBX responsive element was reported to drive expression in rhombomere 4 [42] . More downstream ( in the range of residues 261–313 ) , a series of SOX2 binding sites was shown to drive expression in rhombomere 2 [43] . Both regions are located outside the sole domain of the protein ( the homeobox ) and a pronounced shift towards lower structural constraints was detected in both . The residues overlapping the HOX-PBX responsive element were predicted as having low sequence complexity and partial disorder ( Figure 3A ) , and the corresponding region was devoid of regular secondary structure elements . The two residues predicted to fall in helical and extended conformation in this region cannot form a real secondary structure and also , their corresponding PSIPRED confidence scores were very low , so we considered them erroneously assigned by the prediction method . The other segment of 53 residues , although not displaying reduced levels of sequence complexity , was predicted to be almost completely disordered and contained a single , four-residue predicted α-helix with relatively low confidence values ( Figure 3B ) . Breast cancer type 1 susceptibility protein ( BRCA1 ) presents a good example for SCEs overlapping with validated translation initiation regulatory sites . BRCA1 is an E3 ubiquitin ligase playing a central role in DNA damage response [44] , [45] . The protein contains an N-terminal RING ( really interesting new gene ) domain and two tandem BRCT ( after the C-terminal domain of a breast cancer susceptibility protein ) domains in its C-terminus . These are separated by a more than 1500 residues long , experimentally validated disordered region [46] that mediates a plethora of interactions . Only one synonymously constrained region was detected in BRCA1 , and it overlapped with an alternative translation start site , which was shown to mediate the translation of a shorter BRCA1 isoform that lacks the RING domain . The corresponding segment of the canonical protein is in the long linker region , and is predicted to be mostly disordered with only a few predicted secondary structure elements ( Figure 4 ) . Nuclear magnetic resonance ( NMR ) and circular dichroism ( CD ) spectroscopy experiments performed on larger segments containing this region confirmed that this part of BRCA1 is disordered and forms only very limited amounts of secondary structure , if any [46] . The FAS gene has a relatively long region annotated as dual-coding ( i . e . overlapping exons translated into protein sequence in different reading frames ) that contains two adjacent , experimentally validated splicing factor binding sites . In fact , these two sites represent triple-function regions and serve as examples for sites involved in splicing regulation . To the best of our knowledge , such sites have not been described in eukaryotic genomes before . We examined the corresponding regions of both isoforms from a structural aspect ( Figure 5 ) . In the canonical protein chain , the three residues corresponding to the shorter binding site do not appear to be disordered or of low complexity , and secondary structure elements are also not predicted here . Interestingly , the residues overlapping the longer binding site reside within the only transmembrane helix region of the protein ( assigned by UniProtKB [47] ) . This region is predicted as low complexity by SEG , since five out of six residues are leucines with only a single cysteine breaking the repeat . Obviously , it is not predicted as disordered by IUPred , which assigns very low scores to a stretch of hydrophobic residues ( meaning highly ordered ) . In the other isoform , the residues overlapping with the binding sites are located in the C-terminal tail and they are not assigned as membrane spanning . The residues corresponding to the shorter binding site are at the border of a predicted disordered region , while the longer binding site encodes for residues predicted to be of low sequence complexity when using SEG with window size 10 . It is clear that in both cases the triple functionality is somewhat compensated for by the protein . The shorter site is located in a disordered region in at least one of the two protein chains , while the long binding site encodes for compositionally biased segments in both . Interestingly , Lin et al did not detect SCEs overlapping this region by any of the three applied resolutions . However , considering their rather stringent filtering criteria [18] , this could also have other reasons than the lack of low levels of synonymous rate constraint . At the 15-codon resolution , Lin and co-workers detected SCEs in about 6000 human genes ( ∼35% of the genes ) . This vast set of genes was checked for biases towards certain Gene Ontology ( GO ) annotations , and genes involved in “chromatin modification” turned out to be the most enriched in SCEs ( ∼twofold enrichment ) [18] . For instance , several SCEs were detected in the genes of the modular transcription coactivators CBP ( CREB-binding protein ) and p300 ( E1A binding protein p300 ) , and we therefore investigated the structural properties of the corresponding protein segments ( Figure 6 ) . Interestingly , despite CBP having seven , and p300 having four , SCE-overlapping regions ( in the dataset of 15-codon resolution ) , none of these is located in well-folded domains . In p300 , one of the four SCEs overlaps with the nuclear coactivator binding domain ( NCBD ) , which was previously described as a molten globule [48] and was predicted to be completely disordered ( Figure 6A ) . In CBP , one of the seven SCEs overlaps with the nuclear receptor interacting domain ( NRID ) , which actually is a short binding motif that lies in a segment predicted to be completely disordered in both proteins ( Figure 6B ) . In fact , all 11 regions are predicted to be completely disordered by IUPred and 7 overlap with regions of predicted low sequence complexity . At the same time , none of them show more than 50% secondary structure content , and six of them have no secondary structure elements ( or contained only a single residue assigned as such ) . Interestingly , despite the high sequence similarity of the two proteins , the SCE-overlapping regions are differently distributed along their chains . This could have two reasons: 1 ) the differences between the structure of the two genes demand different splicing regulation ( for instance , CBP has much longer introns resulting in a large difference in overall gene sizes ) or 2 ) the overlapping functionalities evolved after the divergence of CBP and p300 from the ancestral gene .
It has been previously demonstrated that evolutionary rates of proteins are constrained by additional functions encoded by their genes , for instance , when functional RNAs are encoded on the same or opposite strand as protein chains [49] . Apart from a specific study on human dual-coding regions [31] , however , such multi-functional coding regions have never been comprehensively studied from the protein structural aspect . We performed a thorough computational analysis on such regions using several carefully chosen structure prediction methods . First , we investigated this phenomenon on a large scale , by mapping a recently published , high-resolution dataset of human SCEs onto the human proteome and predicting the structural features of the resulting protein segments . We observed a significant enrichment of structural disorder and low sequence complexity , and depletion in regular secondary structure elements and domain annotations . These results imply that the increased functional demands on coding regions of the DNA coincide with structurally biased segments on the protein level . In general , structurally disordered and/or compositionally biased protein segments have lower structural constraints than regions of regular secondary structure elements or globular domains , which confers them enhanced mutation tolerance [27] . Due to this reason , such structurally less constrained protein regions can obviously better accommodate restraints affecting their coding regions . Here , we provide evidence that the encoded polypeptide is compositionally and/or structurally biased in diverse cases of multiple coding , including a variety of short regulatory elements ( either on DNA- or on RNA-level ) . The observed structural effects were more pronounced when the actual regions of multi-functionality were identified with higher precision . We observed a decrease in relative structural disorder and low sequence complexity content of SCE-encoded segments with increasing SCE detection window size , while their secondary structure content was positively correlated . Also , the datasets of different resolutions were found to be significantly different from each other for most of the structural properties investigated . Larger windows also span protein segments devoid of overlapping functionalities . Hence , the gradual decrease of structural deviations with increasing window size can be considered as further evidence for counterbalancing forces that maintain weak structural constraints in the affected protein regions selectively . As another proof of the structurally biased nature of protein segments encoded by multi-functional gene regions , we found that the validated disordered regions of the DisProt database are highly enriched in SCEs compared to equivalent reference segments . To provide further evidence for our hypothesis , we also analysed an independent set of human exonic splicing factor binding sites that have been experimentally validated and identified at single nucleotide resolution . Despite the paucity of data and the observed bias towards domain regions , we found a significant enrichment in structural disorder , depletion in secondary structure elements , and , on a residue-level , enrichment in low sequence complexity in these segments . These results obtained at single nucleotide resolution further strengthen our initial hypothesis about a compensatory mechanism playing a role in multi-functional coding regions . It seems that multiple demands on DNA level coincide with a local decrease of protein structural constraints even within the boundaries of domains . Additionally , the surprisingly small overlap between the computationally detected SCEs and the experimentally verified SFBSs implies that Lin et al . [18] applied very stringent filtering criteria in SCE detection , and thus there are certainly many multi-functional coding regions in the human genome that were not identified by them as SCEs . Besides general statistical analyses , we have also examined a few important human proteins with different types of well-described overlapping functionalities . The correlation between overlapping DNA- and RNA-level regulatory sites and lack of local protein structure is clear in these cases , as well as the tendency of such multi-functional regions to reside outside well-folded domains . We further investigated a special case of triple functionality ( Figure 5 ) , in which splicing regulatory sites overlap with a longer region of dual protein coding and encode for structural/compositional biases in both protein isoforms . It is important to emphasize that the coincidence between protein disorder and nucleotide-level functionality does not reveal the causative relationship between the two . There are two possible scenarios: ( 1 ) either the protein with an IDR existed first and the corresponding gene region could adopt an additional functionality due to the less stringent structural constraints of the encoded IDR , or ( 2 ) the other functionality existed first , which demanded reduced structural constraints in the overlapping protein . Obviously , none of these two scenarios might apply exclusively , since the ∼10000 examined multi-functional regions certainly provide examples for both . Human CBP and p300 , for instance , seem to follow the first scenario . They are paralogues , showing a very high level of sequence conservation , but their detected SCEs are not similarly distributed along their chains ( Figure 6 ) . This implies that the overlapping regulatory functionalities represented by the detected SCEs appeared after the duplication of their ancestral gene i . e . the starting point of their evolutionary divergence . We have shown that these additional functionalities preferentially evolved at exon regions that could more easily accommodate them due to the lack of counteracting constraints in their encoded polypeptide chains . In all , our results demonstrate that the level of complexity encoded by a genomic region of a given length is limited , and in case of multiple competing functions this limitation results in compromises . Since regulatory functions at DNA or RNA level are primarily fulfilled by short stretches of nucleotides , their information content cannot be reduced , which makes their sequences strictly conserved . Proteins , however , can be considered as longer functional elements , many of their residues are not crucial for their function and structural integrity , and are thus rather free to change . This is particularly true for regions of structural disorder and low sequence complexity , while globular domains are less flexible in this regard . In accord , we report here that genomic regions with multiple functionalities are more likely to overlap with protein regions of lower structural constraints , which suggests a trend towards the rational distribution of functional elements within the coding regions of genomes . | Certain genomic regions code for multiple , overlapping functionalities that can be detected by analyzing the levels and patterns of their evolutionary conservation . The redundant nature of the genetic code facilitates the appearance of such multi-functional gene regions through evolution . At many of these sites the DNA sequence encodes a protein segment and in parallel to that another function , e . g . regulatory sites involved in translation initiation and transcript splicing . However , it has never been studied how the corresponding protein segments can tolerate that their primary sequences , and consequently their structures , are restricted by the sequences of the overlapping functionalities . To answer this question , we analyzed a recently published , large set of human , potentially multi-functional coding regions for the structural properties of encoded proteins with a variety of computational structure prediction tools . We examined the level of disorder , secondary structure , and sequence complexity of the corresponding protein regions , and found that multi-functional gene regions translate into protein segments that are significantly enriched in structurally disordered and compositionally biased regions , while they are depleted in secondary structure and domain annotations compared to reference segments of similar lengths . This tendency suggests that protein structural disorder provides evolutionary advantage when accommodating multiple overlapping functions in coding regions . | [
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] | 2014 | Synonymous Constraint Elements Show a Tendency to Encode Intrinsically Disordered Protein Segments |
Mycobacteria of the Mycobacterium tuberculosis complex ( MTBC ) greatly impact human and animal health worldwide . The mycobacterial life cycle is complex , and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood . Eurasian wild boar ( Sus scrofa ) are natural reservoir hosts for MTBC and a model for mycobacterial infection and tuberculosis ( TB ) . In the wild boar TB model , mycobacterial infection affects the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils , and biomarkers have been proposed as correlates with resistance to natural infection . However , the mechanisms used by mycobacteria to manipulate host immune response are not fully characterized . Our hypothesis is that the immune system proteins under-represented in infected animals , when compared to uninfected controls , are used by mycobacteria to guarantee pathogen infection and transmission . To address this hypothesis , a comparative proteomics approach was used to compare host response between uninfected ( TB- ) and M . bovis-infected young ( TB+ ) and adult animals with different infection status [TB lesions localized in the head ( TB+ ) or affecting multiple organs ( TB++ ) ] . The results identified host immune system proteins that play an important role in host response to mycobacteria . Calcium binding protein A9 , Heme peroxidase , Lactotransferrin , Cathelicidin and Peptidoglycan-recognition protein were under-represented in TB+ animals when compared to uninfected TB- controls , but protein levels were higher as infection progressed in TB++ animals when compared to TB- and/or TB+ adult wild boar . MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls . The results reported here suggest that M . bovis manipulates host immune response by reducing the production of immune system proteins . However , as infection progresses , wild boar immune response recovers to limit pathogen multiplication and promote survival , facilitating pathogen transmission .
Tuberculosis ( TB ) caused by mycobacteria of the Mycobacterium tuberculosis complex ( MTBC ) is one of the world's most common causes of death from infectious diseases [1] . Animal TB is caused by infection with Mycobacterium bovis and closely related members of the MTBC . Cattle are the main health concern regarding animal TB in industrialized countries , but other mammalian species are also infected with mycobacteria of the MTBC [2 , 3] . Additionally , human TB cases due to M . bovis infection are reported every year [4 , 5] . Eurasian wild boar ( Sus scrofa ) are natural reservoir hosts for MTBC in some regions and therefore vaccination strategies are being developed for TB control in this species [6–9] . Additionally , wild boar are a model for mycobacterial infection and TB reproducing some of the clinical characteristics observed in human cases such as lung pathology and latent infection [9 , 10] . The life cycle of mycobacteria is complex and not fully characterized [11] . It is generally accepted that after inhalation into the lung or entry to the oropharyngeal cavity , the principal entry routes , mycobacteria of the MTBC are phagocytized by macrophages . As with other intracellular bacteria , mycobacteria survive inside macrophages by escaping host immune response , which results in the formation of a granuloma that effectively contains infected cells . A change in the host-bacterial equilibrium of granulomas is thought to result in the release of infected cells outside containment and onward transmission of mycobacteria to susceptible hosts [11] . In wild boar , mycobacterial infection occurs mostly through oral-nasal routes and mandibular lymph nodes are the most frequently affected tissue by the formation of granulomatous lesions , and the main organ responsible for infection dissemination within the organism [12] . However , generalized infection affects lungs , therefore increasing the risk for pathogen transmission through the oral-nasal route [13] . In the wild boar TB model , mycobacterial infections affect the expression of innate and adaptive immune response genes in mandibular lymph nodes and oropharyngeal tonsils , and Complement component 3 ( C3 ) and Methylmalonyl-CoA mutase ( MUT ) have been proposed as correlates with resistance to natural mycobacterial infection [10 , 14–16] . However , the mechanisms used by mycobacteria to manipulate host immune response are still not fully understood . Our hypothesis is that the immune system proteins under-represented in infected animals when compared to uninfected controls are used by mycobacteria to guarantee pathogen infection and transmission . To address this hypothesis , in this research a comparative proteomics approach was used to characterize host response to natural M . bovis infection using the wild boar TB model . The results identified host immune system proteins that are manipulated by mycobacteria for pathogen infection and transmission .
All animal sampling was post-mortem . Wildlife samples were obtained from hunter-harvested individuals that were shot during the legal hunting season independently and prior to our research . According to EU and National legislation ( 2010/63/UE Directive and Spanish Royal Decree 53/2013 ) and to the University of Castilla–La Mancha guidelines no permission or consent is required for conducting the research reported here . Based on tooth eruption patterns [17] , young ( Age 6–24 months; N = 14 ) and adult ( Age >24 months; N = 15 ) Eurasian wild boar were selected and included in the study . The animals were collected between hunting seasons 2009–2012 from Montes de Toledo , Spain in a region with 66±5% TB prevalence in wild boar [18] . The hunters provided the whole carcass less than 20 min after the animal died and the necropsy were performed on site [18] . Animals were subjected to detailed necropsy as described previously [14] . Samples of dissected mandibular lymph nodes were obtained by sagittal cross-section at half the length , and tissue fragments of approximately 2 cm3 were rapidly prepared and stored in liquid nitrogen for DNA , RNA and protein extraction . The remaining portion of the sample was used for culture and spoligotyping of mycobacteria ( see below ) . After necropsy , young animals were classified as TB- ( N = 5 ) or TB+ ( N = 9 ) based on the absence/presence of TB-compatible lesions and negative/positive for mycobacterial culture . Adult animals were classified as TB- ( N = 4 ) , TB+ ( N = 5 ) or TB++ ( N = 6 ) . The TB- animals were negative for mycobacteria culture and did not have TB-compatible lesions . The TB+ and TB++ animals were positive for mycobacteria culture and showed TB-compatible lesions localized in head organs ( mandibular lymph nodes and/or oropharyngeal tonsils ) referring to localized ( potentially early ) or controlled M . bovis infection or affecting multiple organs in the head and thorax that reflect disseminated TB , respectively ( Table 1 ) . Adult TB++ wild boar with disseminated disease showed extensive macroscopic lesions with poor fibrotic containment of the granulomas and ulceration into the lumina of airways . All animals positive for mycobacteria culture had infection with M . bovis . Mandibular lymph nodes were used in the study because these organs are involved in mycobacterial infection and TB [10 , 14–16] . Proteins from mandibular lymph nodes were extracted using the AllPrep DNA/RNA/Protein Mini Kit ( Qiagen , Inc . Valencia , CA , USA ) according to manufacturer instructions . Precipitated proteins from individual samples of each group ( TB- and TB+ young animals and TB- , TB+ and TB++ adult animals ) were resuspended in 20mM Tris-HCl pH 7 . 5 with 4% SDS and protein concentration was determined using the BCA Protein Assay ( Thermo Scientific , San Jose , CA , USA ) using bovine serum albumin ( BSA ) as standard . Protein extracts ( 150 μg per sample ) were on-gel concentrated by SDS-PAGE as previously described [20] . The unseparated protein bands were visualized by staining with GelCode Blue Stain Reagent ( Thermo Scientific ) , excised , cut into 2 × 2 mm cubes and digested overnight at 37°C with 60 ng/μl sequencing grade trypsin ( Promega , Madison , WI , USA ) at 5:1 protein: trypsin ( w/w ) ratio in 50 mM ammonium bicarbonate , pH 8 . 8 containing 10% ( v/v ) acetonitrile [21] . The resulting tryptic peptides from each band were extracted by 30 min-incubation in 12 mM ammonium bicarbonate , pH 8 . 8 . Trifluoroacetic acid was added to a final concentration of 1% and the peptides were finally desalted onto OMIX Pipette tips C18 ( Agilent Technologies , Santa Clara , CA , USA ) , dried-down and stored at −20°C until mass spectrometry analysis . The desalted protein digests was resuspended in 0 . 1% formic acid and analyzed by RP-LC-MS/MS using an Easy-nLC II system coupled to an ion trap LTQ mass spectrometer ( Thermo Scientific ) . The peptides were concentrated ( on-line ) by reverse phase chromatography using a 0 . 1×20 mm C18 RP precolumn ( Thermo Scientific ) , and then separated using a 0 . 075×100 mm C18 RP column ( Thermo Scientific ) operating at 0 . 3 ml/min . Peptides were eluted using a 180-min gradient from 5 to 40% solvent B ( Solvent A: 0 , 1% formic acid in water , solvent B: 0 , 1% formic acid in acetonitrile ) . ESI ionization was done using a Fused-silica PicoTip Emitter ID 10 mm ( New Objective , Woburn , MA , USA ) interface . Peptides were detected in survey scans from 400 to 1600 amu ( 1 mscan ) , followed by fifteen data dependent MS/MS scans ( Top 15 ) , using an isolation width of 2 mass-to-charge ratio units , normalized collision energy of 35% , and dynamic exclusion applied during 30 sec periods . The MS/MS raw files were searched against the Uniprot-Sus scrofa database ( 34 , 207 entries in November 2015 ) ( http://www . uniprot . org ) using the SEQUEST algorithm ( Proteome Discoverer 1 . 4 , Thermo Scientific ) . The following constraints were used for the searches: tryptic cleavage after Arg and Lys , up to two missed cleavage sites , and tolerances of 1 Da for precursor ions and 0 . 8 Da for MS/MS fragment ions and the searches were performed allowing optional Met oxidation and Cys carbamidomethylation . A false discovery rate ( FDR ) < 0 . 01 was considered as condition for successful peptide assignments and at least two peptide-spectrum matches ( PSMs ) per protein were the necessary condition for protein identification ( S1 Table ) . Gene ontology ( GO ) analysis for biological process ( BP ) was done by Blast2GO software ( version 3 . 0; www . blast2go . com ) . Two biological replicates with 2–5 pooled mandibular lymph node samples each were used for analysis . Identified proteins were grouped according to BP GO . Within each BP , the average number of PSMs for each S . scrofa protein were added and normalized against the total number of PSMs and compared separately in young and adult animals between TB- and TB+ or between TB- , TB+ and TB++ samples , respectively by Chi2-test ( p = 0 . 05 ) . The average number of normalized PSMs for proteins in BPs with statistically significant differences between samples was then used to identify proteins with significant differences in representation within each BP by Chi2-test ( p<0 . 05 ) . The mass spectrometry proteomics data have been deposited at the ProteomeXchange Consortium ( http://proteomecentral . proteomexchange . org ) via the PRIDE partner repository with the dataset identifier PXD003251 and doi: 10 . 6019/PXD003251 . S1 Table contains all S . scrofa proteins identified with FDR<0 . 01 and at least two PSMs per protein in at least one of the analyzed samples , BP annotation and data quantitation . Venn diagrams were constructed using Concept Draw PRO 10 ( CS Odessa LLC , San Jose , CA , USA ) . Recombinant Calcium binding protein A9 ( S100A9; Uniprot accession number C3S7K6 ) , Lactotransferrin ( LTF; Q6YT39 ) and Peptidoglycan-recognition protein ( PGLYRP1; F1RM24 ) were produced in Escherichia coli using pET101/D-TOPO expression system ( Invitrogen-Life Technologies Inc , Grand Island , NY , USA ) . Coding regions were amplified by RT-PCR using total RNA extracted from 3D4/31 cell line ( Pig macrophage ) samples and sequence-specific oligonucleotide primers ( S2 Table ) and cloned into the pET101/D-TOPO expression vector ( Invitrogen-Life Technologies Inc , Grand Island , NY , USA ) . Recombinant proteins were purified by Ni affinity chromatography to >95% purity and used to produce antibodies in rabbits as previously described [22] . The specificity of the antibodies was characterized by Western blot as described below but using 10 μg of recombinant proteins . For Western blot analysis , 15 μg of total proteins from individual wild boar mandibular lymph nodes ( young TB- , N = 5; young TB+ , N = 9; adult TB- , N = 4; adult TB+ , N = 5; adult TB++ , N = 5 ) were loaded onto a 12% SDS-polyacrylamide gel ( Life Science , Hercules , CA , USA ) and transferred to a nitrocellulose membrane during 1 h at 12 V in a Mini-Genie Electroblotter semi-dry transfer unit ( Idea Scientific , Corvallis , OR , USA ) . The membrane was blocked with 5% skim milk for 1 h at room temperature , washed three times in TBS and probed with rabbit antibodies . Serum from rabbits immunized with recombinant proteins was diluted 1:500 in 3% BSA in TBS and the membrane was incubated with the diluted sera for 1 h at room temperature , and washed three times with TBS . Rabbit antibodies against the recombinant 40S ribosomal protein S14 ( RPS14; Q29303 ) ( Sigma-Aldrich Co , St . Louis , MO , USA ) were used as control for normalization in Western blot analysis . The membrane was then incubated with an anti-rabbit horseradish peroxidase ( HRP ) conjugate ( Sigma-Aldrich Co , St . Louis , MO , USA ) diluted 1:1000 in TBS . The membrane was washed three times with TBS and finally developed with TMB stabilized substrate for HRP ( Promega ) for 20 min . The intensity of protein bands corresponding to test and control proteins including those with lower or higher molecular weight than the recombinant protein that likely correspond to degradation and polymerization products , respectively were determined in the Western blot membrane by densitometric analysis using ImageJ 1 . 44p ( National institute of Health , USA ) . The intensity of test protein bands was normalized against the intensity of the control band and analyzed by a multivariate comparison between the groups using the one-way ANOVA test followed by one-tailed Student’s t-test with Bonferroni correction for samples with unequal variance ( p = 0 . 05 ) . Hemoglobin protein levels were determined by ELISA ( Cloud-Clone Corp . , Houston , TX , USA ) in serum from individual wild boar ( young TB- , N = 4; young TB+ , N = 7; adult TB- , N = 4; adult TB+ , N = 5; adult TB++ , N = 6 ) . Optical density values were converted to g/dl Hemoglobin using the ELISA standard curve and compared between groups by one-tailed Student’s t-test for samples with unequal variance ( p = 0 . 05 ) . Pools of mandibular lymph node samples were submitted to culture and spoligotyping of mycobacteria as previously described [23 , 24] . The frequency of different spoligotypes in each group was compared between groups by ANOVA F-test ( p = 0 . 05 ) . Total RNA was isolated from individual wild boar mandibular lymph nodes tissue samples using the AllPrep DNA/RNA/Protein Mini Kit ( Qiagen , Inc . Valencia , CA , USA ) according to manufacturer’s instructions . Individual RNA samples of young TB- , TB+ and adult TB- , TB+ , TB++ wild boar mandibular lymph nodes ( young TB- , N = 5; young TB+ , N = 9; adult TB- , N = 4; adult TB+ , N = 5; adult TB++ , N = 5 ) were used for real-time RT-PCR analysis . Primers were synthesized based on the sequences determined for S . scrofa C3 [12] , MUT [12] , S100A9 , LTF , and PGLYRP1 genes ( S2 Table ) . Real-time RT-PCR was performed using the QuantiTec SYBR Green RT-PCR kit and a Rotor Gene Q thermocycler ( Qiagen , Inc . Valencia , CA , USA ) following manufacturer’s recommendations . Amplification efficiencies were normalized against S . scrofa cyclophilin and expressed as transcript copy numbers in arbitrary units [14–16] . Pair comparisons between mRNA expression levels were done by a multivariate comparison between the groups using the one-way ANOVA test followed by one-tailed Student’s t-test with Bonferroni correction for samples with unequal variance ( p = 0 . 05 ) . For controlled experimental infection with M . bovis , wild boar were selected from the control group in the vaccine trial previously reported [8] . Selected infected wild boar were divided into two groups after necropsy . TB+ animals ( N = 2 ) had a 6–12 lesion score with TB lesions in the mandibular ( N = 2 ) and tracheobronchial ( N = 1 ) lymph nodes [8] . TB++ animals ( N = 3 ) had a 16–38 lesion score with TB lesions in tonsils ( N = 1 ) , mandibular ( N = 3 ) , retropharyngeal ( N = 3 ) , tracheobronchial ( N = 3 ) lymph nodes and lungs ( N = 2 ) [8] . All animals were positive for M . bovis cultures [8] . Proteins from tonsils of TB+ and TB++ wild boar were extracted , on-gel concentrated , trypsin digested and analyzed by RP-LC-MS/MS following the same procedures described above for field-collected samples . The MS/MS raw files were searched against the Uniprot-Sus scrofa database ( 34 , 207 entries in November 2015 ) ( http://www . uniprot . org ) using the SEQUEST algorithm ( Proteome Discoverer 1 . 4 , Thermo Scientific ) with the same constraints described above . A FDR < 0 . 01 was considered as condition for successful peptide assignments and at least two PSMs per protein were the necessary condition for protein identification ( S3 Table ) . For targeted proteomics , the MS/MS raw files were searched against a database composed of the six differentially represented immune system proteins in naturally infected wild boar ( C3S7K6 , F1RRP1 , Q6YT39 , Q8SPA3 , I3LNT1 and F1RM24 ) plus control Actin ( P68137 ) using the SEQUEST algorithm ( Proteome Discoverer 1 . 4 , Thermo Scientific ) with the same constraints described above . A FDR < 0 . 05 was considered as condition for successful peptide assignments and subsequent protein identification ( S3 Table ) . Two ( TB+ animals ) or three ( TB++ animals ) biological replicates were used for analysis . The average number of PSMs for each S . scrofa protein were added and normalized against the total number of PSMs and compared between TB+ and TB++ samples by Chi2-test ( p = 0 . 05 ) . S3 Table contains all S . scrofa proteins identified with FDR<0 . 01 and at least two PSMs per protein in at least one of the samples and the S . scrofa proteins analyzed with FDR<0 . 05 in targeted proteomics .
After proteomics analysis of wild boar mandibular lymph nodes , a total of 428 and 532 proteins were identified in young and adult animals , respectively ( S1 Table ) . The number of identified proteins and PSM with which these proteins were identified was similar between experimental groups ( young TB- , young TB+ , adult TB- , adult TB+ , adult TB++ ) ranging from 358 to 439 proteins and 2165–2497 PSM ( Fig 1A ) . As expected , the same proteins were identified in several experimental groups with 200 proteins found in all groups ( Fig 1B ) . The GO analysis showed that the most represented BPs were cellular , immune system , cell interaction , developmental and response to stimulus processes in young wild boar ( Fig 2A ) , while cellular , immune system , localization , metabolic and growth processes were the BPs with most represented proteins in adult animals ( Fig 2B ) . Significant differences were observed in the most represented BPs between uninfected and M . bovis-infected young and adult wild boar ( Fig 2A and 2B ) or between TB+ and TB++ adult animals ( Fig 2B ) . Two BPs , cellular and immune system were represented in both young and adult animals ( Fig 2A and 2B ) . Protein quantitative analysis within each of the most represented BPs resulted in 40 and 44 differentially represented proteins in young and adults , respectively ( Fig 3A ) . Of them , 19 proteins were differentially represented in both young and adult wild boar ( Fig 3A ) . Differentially represented proteins were over-represented or under-represented in TB+ young animals when compared to TB- uninfected controls ( Fig 3A and 3B ) . In adult animals , differentially represented proteins showed a complex pattern when comparing the different groups ( Fig 3A and 3B ) . Of the BPs represented in young and adult wild boar , only the immune system BP was significantly different between infected and uninfected animals in both age groups ( Fig 2A and 2B ) . Immune system proteins play an important role in host response to mycobacteria and other infectious microorganisms and were therefore selected for further analysis . A total of 27 and 31 proteins were included into the immune system BP in young and adult animals , respectively ( Fig 4A ) . Of them , 5 and 6 proteins were differentially represented in young and adult animals , respectively ( Fig 4A ) . In young animals , all 5 immune system proteins S100A9 ( C3S7K6 ) , uncharacterized Heme peroxidase ( F1RRP1 ) , LTF ( Q6YT39 ) , uncharacterized Cathelicidin ( I3LNT1 ) and PGLYRP1 ( F1RM24 ) were under-represented in TB+ animals when compared to uninfected TB- controls ( Fig 4A and 4B ) . In adults , 3 proteins ( LTF , Cathelicidin , PGLYRP1 ) had the same representation than in young animals while the other 3 proteins were over-represented in infected TB+ ( MHC class I antigen , MHCI; Q8SPA3 ) or TB++ ( Heme peroxidase , LTF ) animals when compared to uninfected TB- controls ( Fig 4A and 4B ) . Additionally , 5 of the differentially represented proteins in adults ( S100A9 , Heme peroxidase , LTF , Cathelicidin , PGLYRP1 ) were over-represented in TB++ when compared to TB+ animals ( Fig 4A and 4B ) . To validate proteomics results , differentially represented immune system proteins S100A9 , LTF and PGLYRP1 were produced in E . coli ( S1A Fig ) and used to generate rabbit antibodies specific for recombinant S . scrofa proteins ( S1B Fig ) . The Western blot analysis of individual wild boar mandibular lymph node protein samples ( S1C–S1E Fig ) showed a good correlation with proteomics results and validated proteomics results for these proteins ( Fig 5A–5D ) . To provide additional support for the results obtained in naturally infected animals , wild boar experimentally infected with M . bovis under controlled conditions [8] were used to characterize the levels of differentially represented immune system proteins C3S7K6 , F1RRP1 , Q6YT39 , Q8SPA3 , I3LNT1 and F1RM24 by targeted proteomics ( S3 Table ) . Mandibular lymph nodes were not available for analysis . Therefore , tonsils that are also involved in mycobacterial infection and TB [14–16 , 19] were used for analysis . The results were similar between TB+ and TB++ experimentally infected and naturally infected animals for most of the differentially represented immune system proteins ( S2 Fig ) . Proteomics results showed that Hemoglobin proteins were under-represented in M . bovis-infected adult wild boar when compared to uninfected animals ( Fig 6A ) . These results were validated by ELISA in individual adult wild boar serum ( Fig 6B ) . In young animals , a tendency was observed towards lower Hemoglobin levels in infected animals , but results were not statistically significant due to high individual variation in protein levels ( Fig 6B ) . To further characterize the response mediated by immune system proteins differentially represented in response to M . bovis infection , a transcriptional profile was obtained in mandibular lymph nodes for genes coding for S100A9 ( Fig 7A ) , LTF ( Fig 7B ) and PGLYRP1 ( Fig 7C ) . The results did not show correlation between protein and mRNA levels in young animals or when comparing adult TB++ and TB+ animals ( Fig 7D ) . However , in adult wild boar a 67% ( 2/3 ) correlation was obtained when comparing mRNA and protein levels between TB- and TB+ or TB++ animals ( Fig 7D ) . The impact of host and pathogen genetic factors on M . bovis infection and disease has been documented in the wild boar TB model [10 , 14–16 , 24] . The expression of MUT and C3 was characterized in young and adult wild boar ( Fig 7E and 7F ) . The results did not support a role for MUT in wild boar infection by M . bovis in this population ( Fig 7E ) . However , C3 mRNA levels were higher in young TB+ animals but lower in infected TB+ and TB++ adult animals when compared to uninfected TB- controls ( Fig 7F ) , suggesting a role for C3 in host response to M . bovis infection . Five different M . bovis spoligotypes ( SB0339 , SB1263 , SB0121 , SB0134 , SB1177 ) were identified in wild boar included in the study ( Fig 7G ) . Although some spoligotypes were not present in all groups , the frequency of different spoligotypes was not statistically different between groups ( p = 0 . 99 ) ( Fig 7G ) . Adult animals had higher spoligotype diversity . The SB0339 spoligotype was isolated with the highest frequency ( 0 . 4–0 . 6 ) from all groups ( Fig 7G ) , while spoligotypes SB0134 and SB01177 were identified with low frequency ( 0 . 1 ) only in adult TB++ animals ( Fig 7G ) .
The protein S100A9 is produced by neutrophils and has been suggested to be involved in the positive regulation of intrinsic apoptotic signaling pathway , innate immune response and autophagy among other processes [25] , all mechanisms involved in host immune response to mycobacterial infection [26] . Therefore , reducing S100A9 protein levels may be a mechanism used by M . bovis to evade host immune response and establish infection in young wild boar . However , S100A9 also mediates neutrophilic inflammation and lung pathology during active TB [27] . The over-representation of S100A9 in TB++ adult wild boar may be a host response to limit pathogen multiplication but it is also associated with active TB resulting in increased transmission of mycobacteria . Heme is an important prosthetic group in hemoglobins , peroxidases , catalases , hydroxylases , and cytochromes required for various processes such as DNA transcription , RNA translation , protein stability , cell differentiation and immunity [28] . Heme peroxidase such as Eosinophil peroxidase also shows inhibitory activity against mycobacteria by inducing bacterial fragmentation and lysis [29] . Furthermore , most bacterial pathogens including mycobacteria require heme and iron for full virulence and have developed systems for heme acquisition [28 , 30] . Therefore , the under representation of Heme peroxidase in infected TB+ wild boar when compared to uninfected TB- animals may be induced by M . bovis to evade host immune response and establish infection in young animals . As infection proceeds in adult wild boar to affect several organs in TB++ animals , Heme peroxidase protein levels are higher than in TB+ animals which may represents a mechanism for the host to inhibit pathogen multiplication . However , mycobacteria may benefit from this response in adult TB++ wild boar by acquiring Heme to increase virulence and favor transmission . Mycobacteria of the MTBC grow within macrophages to establish infection in the host [11] . Iron ( Fe ) acquisition is critical for mycobacterial growth and bacteria acquire Fe bound to citrate , Transferrin and LTF and from macrophage cytoplasm [31] . Furthermore , host immune response to mycobacteria infection partly depends on iron regulation by the host through the tight control of iron-storage proteins [32 , 33] . Consequently , LTF has been proposed as an adjuvant for the BCG vaccine to increase its efficacy [34] . Considering the critical role that LTF plays during mycobacterial infection , protein under-representation in TB+ young and adult animals when compared to uninfected TB- controls could reflect a mechanism of host immune response to infection by reducing Fe source to mycobacteria . However , the LTF protein levels increased in TB++ adult animals suggesting a mechanism by which mycobacteria manipulate host immune response during infection progression to increase Fe availability resulting in higher bacterial growth and transmission . It has long been recognized that many people and animals exposed to MTBC do not subsequently show any evidence of infection probably due to innate , non-specific inflammatory responses that control infection or reduce the infection load , therefore modulating the subsequent host acquired immune response [35] . Cathelicidin is one of the antimycobacterial peptides delivered to phagosomes containing mycobacteria through fusion with lysosomes resulting in macrophage autophagy killing intracellular mycobacteria [35] . Therefore , reduction in the production of antimycobacterial peptides such as Cathelicidin increases susceptibility to TB [35] . As with other immune system proteins identified here as differentially represented in mandibular lymph nodes of naturally infected wild boar when compared to uninfected controls , Cathelicidin was under-represented in infected TB+ young and adult wild boar , probably reflecting a mechanism by which mycobacteria manipulate host innate immune response to facilitate infection and multiplication . However , Cathelicidin protein levels increased in TB++ adult animals suggesting a host mechanism to limit bacterial multiplication as infection progresses to increase host survival . Mycobacteria may benefit from this response in TB++ adult animals by increasing the probability of transmission to susceptible hosts . Peptidoglycan recognition proteins are part of the innate immune system that bind to bacterial cell wall molecules such as lipopolysaccharide , lipoteichoic acid , peptidoglycan and fatty acids such as mycobacterial mycolic acid [36] . The PGLYRP1 protein showed a profile similar to Cathelicidin in response to M . bovis infection in wild boar , again suggesting a mechanism by which mycobacteria manipulate host innate immune response to facilitate infection and multiplication but host response increases protein levels to limit bacterial multiplication as infection progresses to increase host survival . As discussed above , mycobacteria may benefit from this response in TB++ adult animals by increasing the probability of transmission to susceptible hosts . MHCI was the only protein over-represented in TB+ adult wild boar when compared to uninfected TB- controls with no significant differences between other groups . According to the protein annotation , this MHCI antigen probably belongs to the classical MHC class Ia which functions by presenting peptide antigens to pathogen-specific cytotoxic T cells [37] . Therefore , the over-representation of MHCI in TB+ wild boar probably reflects host immune response to M . bovis infection . However , the T cell epitopes of MTBC including M . bovis are hyperconserved in different strains consistent with strong purifying selection acting on these epitopes [24 , 38] . Consequently , MTBC might benefit from recognition by T cells because this essential response for host survival may be necessary for mycobacteria to establish latent infection [38] . Protein levels and the expression of coding genes for differentially represented immune system proteins were characterized by Western blot and real-time RT-PCR in individual wild boar mandibular lymph node protein and RNA samples , respectively . Western blot analysis validated the proteomics results . Additionally , Hemoglobin protein levels that were under-represented in M . bovis-infected adult wild boar when compared to uninfected animals were also validated by ELISA in individual wild boar serum samples . These results suggested the presence of regulatory mechanisms acting at both transcriptional and post-transcriptional levels depending on the age and infection status of the animals . In young infected animals , regulation was probably at the post-transcriptional level while in adult TB+ and TB++ animals the presence of transcriptional mechanisms was more evident . However , the comparison between TB++ and TB+ adult animals also suggested regulation at the post-transcriptional level to explain differences between mRNA and protein levels . Nevertheless , the discrepancy between mRNA and protein levels could also be explained by delay between mRNA and protein accumulation , which requires sampling at different time points . Immune response is regulated at both transcriptional and post-transcriptional levels [39] and the regulatory mechanisms that occur at the level of mRNA splicing , mRNA polyadenylation , mRNA stability and protein translation have instrumental roles in controlling both the magnitude and duration of the immune response [40] . Therefore , it was not surprising to find that both transcriptional and post-transcriptional mechanisms probably operated to regulate the levels of the immune system proteins identified as differentially represented in wild boar mandibular lymph node response to mycobacterial infection . With the approach used in this research we were able to characterize the dynamics of wild boar immune response at the host-mycobacteria interface . However , other factors such as contact probability between hosts and mycobacteria and genetic factors of both hosts and pathogens could also affect infection prevalence and disease progression [9 , 14–16 , 24] . The contact between hosts and mycobacteria was very probable in adult animals due to the high ( 66% ) M . bovis prevalence in wild boar in this region . Consequently , as shown in previous studies [14] , uninfected adult animals were probably resistant to M . bovis . However , uninfected young animals could have been naïve to M . bovis infection . To address the impact of host genetic factors on infection and disease progression , the expression of genes coding for C3 and MUT was characterized as possible correlates with host resistance to natural mycobacterial infection [9 , 14–16] . The results did not support a role for MUT in susceptibility to M . bovis in these animals [16] . However , the results of C3 expression supported a role for this molecule in the outcome of M . bovis infection . As reported in previous studies [8 , 9] , C3 mRNA levels increased with M . bovis infection in young animals as a host response to limit mycobacterial infection . However , in adult wild boar higher C3 levels correlated with protection against M . bovis infection , providing additional support for the central role of this molecule in the protective response against mycobacterial infection [8 , 9 , 14 , 15] . Hemoglobin protein levels that are associated with TB-induced anemia [41] were lower in infected TB+ and TB++ adult animals when compared to uninfected controls , indicating anemia in infected wild boar , but without differences as infection progressed between TB+ and TB++ animals . The tendency in Hemoglobin protein levels in young wild boar also suggested anemia in infected animals . Finally , the prevalence of M . bovis spoligotypes in infected animals was used to characterize pathogen genetic diversity in these animals and their possible impact on infection and disease [24] . Although the frequency of the 5 spoligotypes identified was not different between groups , adult animals had a greater spoligotype diversity probably reflecting a longer exposure to mycobacteria . Two of the spoligotypes , SB0339 and SB0134 has been phenotypically and genetically correlated with high distribution ( isolation frequency ) and low and high TB lesion score in wild boar , respectively [24] . The SB0339 spoligotype was isolated from all groups with high frequency but the SB0134 sopligotype was identified only in adult TB++ animals . These results are in agreement with previous reports [24] and suggest that mycobacteria-derived genetic factors may impact on M . bovis infection and disease in the study site . The results reported here suggested that M . bovis manipulates host immune response to facilitate infection in wild boar ( Fig 8 ) . As other intracellular bacteria , M . bovis manipulate host immune response by reducing the production of immune system proteins [26] . However , as infection progresses , wild boar immune response recover to limit pathogen multiplication and promote survival that also facilitates pathogen transmission ( Fig 8 ) . Adult TB++ wild boar with disseminated disease showed extensive macroscopic lesions with poor fibrotic containment of the granulomas and ulceration into the lumina of airways that facilitate pathogen transmission through aerogenous shedding of mycobacteria [13 , 42] . As previously reported for other obligate intracellular bacteria [43] , host-mycobacteria interactions probably reflect a co-evolutionary process in which pathogens evolved mechanisms to subvert host response to establish infection but hosts also evolved mechanisms to limit pathogen infection and promote survival . Subsequently , mycobacteria benefit from host survival by increasing the probability for transmission to continue the life cycle . The reduction in anemia progression from TB+ to TB++ adult animals is probably associated with the increase in host survival ( Fig 8 ) . These results also provided evidence to support the impact of host and pathogen derived genetic factors affecting pathogen infection and disease ( Fig 8 ) . The upregulation of C3 in uninfected adult wild boar supported the role for this molecule in the protective mechanisms against TB [9 , 44] . Additionally , some of the M . bovis spoligotypes such as SB0134 identified in adult TB++ animals may be associated with the high TB lesion score observed in these animals [24] . These results provide relevant information to develop tools to evaluate risks for TB caused by MTBC and for disease control in humans and animals . | Mycobacteria of the Mycobacterium tuberculosis complex ( MTBC ) are zoonotic pathogens representing a serious health problem for humans and animals worldwide . The life cycle of mycobacteria is complex , and the mechanisms resulting in pathogen infection and survival in host cells are not fully understood . Eurasian wild boar are natural reservoir hosts for MTBC and a model for mycobacterial infections and tuberculosis . The results of this study broaden our understanding of the molecular epidemiology of zoonotic tuberculosis and fill important gaps in knowledge of this topic . The results suggested that mycobacteria manipulate host immune response by reducing the production of immune system proteins . However , as infection progresses , wild boar immune response recovers to limit pathogen multiplication and promote survival , facilitating pathogen transmission . As previously reported in other obligate intracellular bacteria , host-mycobacteria interactions probably reflect a co-evolutionary process in which pathogens evolved mechanisms to subvert host response to establish infection , but hosts also evolved mechanisms to limit pathogen infection and promote survival . Subsequently , mycobacteria benefit from host survival by increasing the probability for transmission to continue their life cycle . These results provide relevant information to develop tools to evaluate risks for tuberculosis caused by MTBC and for disease control in humans and animals . | [
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] | 2016 | Comparative Proteomics Identifies Host Immune System Proteins Affected by Infection with Mycobacterium bovis |
All gammaherpesviruses express homologues of antiapoptotic B-cell lymphoma-2 ( BCL-2 ) to counter the clearance of infected cells by host antiviral defense machineries . To gain insights into the action mechanisms of these viral BCL-2 proteins , we carried out structural and biochemical analyses on the interactions of M11 , a viral BCL-2 of murine γ-herpesvirus 68 , with a fragment of proautophagic Beclin1 and BCL-2 homology 3 ( BH3 ) domain-containing peptides derived from an array of proapoptotic BCL-2 family proteins . Mainly through hydrophobic interactions , M11 bound the BH3-like domain of Beclin1 with a dissociation constant of 40 nanomole , a markedly tighter affinity compared to the 1 . 7 micromolar binding affinity between cellular BCL-2 and Beclin1 . Consistently , M11 inhibited autophagy more efficiently than BCL-2 in NIH3T3 cells . M11 also interacted tightly with a BH3 domain peptide of BAK and those of the upstream BH3-only proteins BIM , BID , BMF , PUMA , and Noxa , but weakly with that of BAX . These results collectively suggest that M11 potently inhibits Beclin1 in addition to broadly neutralizing the proapoptotic BCL-2 family in a similar but distinctive way from cellular BCL-2 , and that the Beclin1-mediated autophagy may be a main target of the virus .
Gammaherpesviruses are DNA viruses comprising a subfamily of the Herpesviridae . These viruses , including Epstein-Barr virus , Kaposi's sarcoma-associated herpesvirus ( KSHV ) and murine γ-herpesvirus 68 ( γHV68 ) , are etiological agents of lymphoid and epithelial tumors in human or animals [1 , 2] . All γ-herpesviruses encode at least one homologue of the cellular apoptosis inhibitor BCL-2 , and expression of these viral BCL-2 genes prevents cell death under various apoptosis-inducing conditions [3–6] . In particular , critical roles of the BCL-2 homologue of γHV68 have been determined by in vitro and in vivo studies in the pathogenesis of the γHV68 virus . The protein , known as and referred to as M11 here , protected cells from undergoing apoptosis induced by a variety of factors , such as dexamethasone treatment , γ-ray irradiation , CD3ɛ ligation [7] , tumor necrosis factor treatment [8 , 9] , Fas ligation [9] , and Sindbis virus infection [10] . Furthermore , the protein contributed to latency establishment [11] and was required for efficient reemergence from latency as well as persistent replication during chronic infection of the virus in immunocompromised mice lacking interferon-γ [12] . These data indicate that removal of virus-infected cells by cell death is a central host defense mechanism against viral infection , and viral BCL-2 proteins play a crucial role in the course of viral replication by inhibiting the death of host cells [1 , 13 , 14] . The BCL-2 family proteins , which are commonly known as positive or negative regulators of apoptosis , are characterized as containing up to four conserved stretches of amino acids , known as BCL-2 homology ( BH ) domains [15 , 16] . BH3-only proteins , a group of proapoptotic BCL-2 family including BIM , BAD , PUMA and Noxa , sense prodeath signals and ultimately activate the downstream proapoptotic members BAX and BAK [17 , 18] . Activated BAX and BAK cause mitochondrial dysfunction and lead to the release of proapoptogenic molecules , such as cytochrome c [19 , 20] . The interactions between such proapoptotic BCL-2 family members and the antiapoptotic members , such as BCL-2 and BCL-XL , are the crucial events in controlling or promoting apoptosis [15 , 16] . These interactions are mediated by the BH3 domain of the proapoptotic members that binds to a site known as the BH3-binding groove in the antiapoptotic members [21 , 22] . In addition to their critical roles in the regulation of apoptosis , the BCL-2 family proteins have emerged as regulators of autophagy , a catabolic process that plays crucial roles in cell survival , tumor suppression , and innate immune defense against intracellular pathogens by degrading cytoplasmic components through lysosomal pathway [23–25] . The leading work was the identification of Beclin1 as a BCL-2-interacting protein [26] . A series of subsequent studies showed that Beclin1 promotes autophagy as a component of a multiprotein complex containing class III phosphatidylinositol 3-kinase ( PI ( 3 ) KCIII ) and UV irradiation resistance-associated gene ( UVRAG ) [27–29] , and that BCL-2 negatively regulates the autophagy-promoting activity of Beclin1 [30] , while the BH3-only protein BAD plays an autophagy-stimulatory function by disrupting the interaction of BCL-2 or BCL-XL with Beclin1 [31] . While Beclin1 exhibits no overall sequence homology with the BCL-2 family proteins , the recently reported structure of BCL-XL in complex with a Beclin1 peptide revealed the presence of a novel BH3 domain in Beclin1 that binds to the BH3-binding groove of BCL-XL [32] . As observed with the cellular kin , expression of the viral BCL-2 protein of KSHV or γHV68 significantly inhibits autophagy in a Beclin1 binding-dependent manner [28 , 30] , suggesting that these two viral BCL-2 proteins may function as autophagy inhibitors as well as apoptosis inhibitors . In this study , we determined the structure of M11 in complex with a 50-residue Beclin1 fragment containing its BH3-like domain . Ensuing analyses revealed that M11 binds Beclin1 significantly more tightly than cellular BCL-2 through tighter hydrophobic interactions . Consistently , transiently expressed M11 inhibited autophagosome formation more efficiently than cellular BCL-2 . We also quantified the interactions of M11 with the BH3 peptides derived from the apoptosis mediators BAX and BAK and the eight upstream BH3-only proapoptotic molecules BAD , BIK , BIM , BID , BMF , PUMA , Noxa and Hrk . The binding affinity of M11 was highest for Beclin1 and fairly high for BAK , BIM , Noxa , BID , BMF and PUMA , but comparatively low for BAX and Hrk . In the observed affinity profile , M11 is distinctively different from cellular BCL-2 and also from M11L , a virulence factor of Myxoma virus and a structural mimic of BCL-2 that acts primarily by sequestering BAX and BAK [33] . These data suggest that M11 robustly inhibits the Beclin1-dependent autophagy and broadly neutralizes the proapoptotic BCL-2 family to subvert the host antiviral responses .
Mouse Beclin1 is composed of 448 amino acids . By coexpression test , we found that mouse Beclin1 fragment consisting of residues 101–150 , which spans the structurally defined BCL-2-binding region consisting of residues 105–125 ( corresponding to residues 107–127 of human Beclin1 [32] ) , formed a tight complex with M11 lacking the C-terminal hydrophobic tail . The protein in complex with Beclin1 ( 101–150 ) was crystallized and its structure was determined to 2 . 3 Å resolution ( Table 1 ) . Residues 106–124 of Beclin1 form an α-helix and bind M11 at an extended hydrophobic surface cleft corresponding to the BH3-binding groove of BCL-XL [7] ( Figure 1A ) . In the crystal , the N-terminal five and the C-terminal 26 residues of the Beclin1 ( 101–150 ) peptide were disordered . The binding of Beclin1 ( 101–150 ) induces a conformational change of M11 to reshape the BH3-binding groove ( Figure 1B ) . Residues 53–55 , a loop segment tailing from α2 in free M11 , form an additional helical turn of α2 in Beclin1 ( 101–150 ) -bound M11 ( Figure 1B ) . In addition , α3 and the following segment undergo a significant conformational transition that involves the translocation of several residues by a distance of 4–10 Å ( Figure 1B ) . In order to test whether the crystal structure reflects the interaction of Beclin1 with M11 in solution and to determine the strength of their interaction , we performed a quantitative binding analysis using isothermal titration calorimetry ( ITC ) ( Figure 1C and Table S2 ) . We employed a Beclin1 fragment containing residues 101–267 ( referred to as Beclin1 ( 101–267 ) ) , since this fragment was expressed as a soluble form in E . coli while Beclin1 ( 101–150 ) was not . This large Beclin1 fragment bound to M11 very tightly with an apparent dissociation constant ( KD ) of 40 nM ( Figure 1C ) . Similar binding affinity ( KD of 99 nM ) was observed with a synthetic Beclin1 ( 101–125 ) peptide ( Figure 1C ) . In contrast , a shorter Beclin1 fragment composed of residues 101–116 exhibited no sign of interaction with the protein ( not shown ) . Unexpectedly , a synthetic Beclin1 ( 106–125 ) peptide showed quite low binding affinity ( KD of 1 . 6 μM ) for M11 ( Figure 1C ) , suggesting that residues 101–105 of Beclin1 constitute an important piece in the interaction of Beclin1 peptide with M11 , although these five residues were disordered in the crystal and thus are not likely to interact with M11 . It was previously shown that residues 140–144 and 161–164 of a BAD peptide contribute to the binding affinity by increasing the helical propensity of the peptide rather than by interacting with BCL-XL [34] . Similarly , a circular dichroism ( CD ) spectroscopic analysis showed that the Beclin1 ( 101–125 ) peptide has considerably higher helical contents ( 29 . 6% ) compared with the Beclin1 ( 106–125 ) peptide ( 17 . 0% ) in 30% trifluoroethanol ( TFE ) solution ( Figure S1 ) . The data supports the idea that residues 101–105 of Beclin1 promote the binding of the Beclin1 ( 101–125 ) peptide to M11 by increasing the helical propensity of the following segment . Conclusively , M11 binds Beclin1 with potently high affinity , and residues 101–125 of Beclin1 compose the minimal region sufficient for binding to M11 . In a reflection of the observed potent interaction , we could easily detect the interaction between transiently expressed full-length M11 and endogenous Beclin1 in NIH3T3 cells ( Figure 1D ) . Cellular antiapoptotic BCL-2 family members share high sequence homology in the BH1 , BH2 and BH3 domains , which compose the common and characteristic BH3-binding groove [35] . At a glance , the intermolecular interaction between M11 and Beclin1 ( 101–150 ) resembled the interactions between the BH3-binding groove of cellular antiapoptotic BCL-2 relatives and a BH3-domain containing peptide or fragment [21 , 22 , 36] . For a detailed structural comparison , we used the crystal structure of BCL-XL in complex with BAD that we have determined to 2 . 3 Å resolution ( Table 1 ) , in which 27 residues of BAD bound to BCL-XL as an extended α-helix and all the rest of the residues were totally disordered . A sequence alignment based on the structural comparison showed that four out of five residues within proapoptotic BH3 domains that are critical for their interactions with the BH3-binding groove [21] are conserved as Leu110 , Leu114 , Asp119 and Phe121 in Beclin1 ( Figure 2A and 2B ) . The remaining residue , which is isoleucine or methionine in the BH3 domains , is substituted as Thr117 in Beclin1 . These five residues occupy spatially and chemically equivalent positions at the BH3-binding groove of M11 as the corresponding residues of BAD bound to BCL-XL ( Figure 2A ) . Additional structural comparison involving the BCL-XL–BAK , BCL-XL–BIM and MCL-1–BIM complexes led to the same conclusion , as the five residues are conserved in the BH3 domains of BAD , BAK and BIM ( Figure 2B ) and they occupy the equivalent positions at the BH3-binding groove of BCL-XL or MCL-1 ( Figure S2 ) . The side chain hydroxyl group of Thr117 of Beclin1 is situated in a hydrophobic milieu , and therefore this residue appeared to make an insignificant or adverse contribution to the helix-groove interaction , in contrast with isoleucine or methionine in the canonical BH3 domains . Thr117 is conserved in the Beclin1 orthologues of vertebrates , but not in those of lower organisms ( Figure 2C ) . Threonine for this position might have been chosen to tune the affinity of Beclin1 for cellular BCL-2 or BCL-XL at a physiologically optimum level . Another noticeable difference from the canonical BH3 domains is that the Beclin1 α-helix has a hydrophobic patch composed of Val116 , Leu120 and Ile123 that are not shielded by the BH3-binding groove ( Figures 2D and S3 ) , while those of other BH3 domains , including that of BAD ( Figures 2D and S3 ) , are distinctively amphipathic . The exposed hydrophobic residues of Beclin1 are identically or similarly conserved throughout species ( Figure 2C ) , suggesting that they may play an as yet unknown important role . These structural and sequence comparisons indicate that Beclin1 has an atypical BH3 domain characterized by the threonine substitution and the exposed hydrophobic patch . In contrast to the robust interaction between M11 and Beclin1 ( 101–267 ) , we found that BCL-2 interacts with Beclin1 ( 101–267 ) weakly with a KD of 1 . 7 μM ( Figure 3A ) , which is similar to the KD value ( 1 . 1 μM ) for the interaction between BCL-XL and a Beclin1 peptide [32] . In order to account for the huge difference in the binding affinity , we compared our structure with the BCL-XL–Beclin1 peptide structure [32] . Compared with 950 Å2 interface of BCL-XL buried by 22 residues of Beclin1 , the binding interface of M11 is smaller ( 860 Å2 ) and involves fewer Beclin1 residues ( a total of 16 residues ) . However , the binding surface of M11 renders tighter hydrophobic interactions with Beclin1 compared with that of BCL-XL ( Figure 3B ) . For example , while Phe121 of Beclin1 interacts with Ala93 of BCL-XL , it interacts with the corresponding but bulkier residue Leu44 of M11 ( Figure 3B ) . Another notable difference is that the bound Beclin1 helix interacts tightly with the α3 helix of M11 , while it interacts poorly with the corresponding region in BCL-XL ( Figure 3B ) , which consistently exhibits poor electron density ( Figure S4 ) and high temperature factors [32] . As a result of these and other differences in the binding interactions , the M11–Beclin1 helix makes 88 intermolecular carbon-carbon contacts ( distance < 4 . 2 Å ) , while the BCL-XL–Beclin1 helix makes 76 such contacts , indicating that the marked difference in the binding affinity arises from the difference in the shape complementarity , and thus the quality , of the hydrophobic interactions . To explore whether the marked difference in the binding affinity of M11 and BCL-2/ BCL-XL for Beclin1 ( 101–267 ) indeed correlates with their activity , we measured the autophagy-inhibiting capacity of M11 and cellular BCL-2 . To quantify the level of autophagy , green fluorescent protein-tagged light chain 3 of microtubule-associated protein 1 ( GFP–LC3 ) was used to indicate the formation of autophagosomes , which deliver cellular components to lysosomes for degradation and recycling during autophagy . GFP–LC3 , a specific marker for autophagosome , moves from the perinuclear region into autophagosomal membranes under autophagy-promoting conditions such as starvation and rapamycin treatment [37 , 38] . In NIH3T3 mouse fibroblast cells , transiently expressed M11 inhibited autophagosome formation more efficiently than transiently expressed BCL-2 , as evident from the rate of GFP–LC3 positive cells carrying autophagic vacuoles and the number of autophagosomes per cell , while the expression level of M11 was much less than that of BCL-2 ( Figure 4A and 4B ) . The efficacy of M11 and BCL-2 was dose-dependent , as the ratio of autophagosome-carrying cells decreased with the increase of the amount of vectors used for transfection ( Figure 4C ) . In these analyses , M11 ( AAA ) , the M11 mutant containing alanine substitutions of three conserved residues ( S85A , G86A and R87A ) within the BH3-binding groove [7] and barely able to bind Beclin1 [28] , exhibited significantly reduced antiautophagic activity compared with the wild-type protein ( Figure 4A , 4B , and 4C ) , suggesting that the Beclin1-binding capacity is essential for the antiautophagic activity of M11 . To further compare their antiautophagic capacity , immunoblotting was also performed with an antibody against LC3 . LC3-II , a cleavage product generated from the LC3 precursor ( LC3-I ) , accumulates in the autophagosomal membrane during autophagy and therefore is widely used as a specific marker for autophagy processing [38 , 39] . In autophagy-inducing rapamycin-treated NIH3T3 cells , the overexpression of M11 suppressed the formation of LC3-II more efficiently than the overexpression of BCL-2 ( Figure 4D ) . These data collectively demonstrate that M11 is a more potent autophagy inhibitor compared with cellular BCL-2 , and that the potency directly correlates with their binding affinity for Beclin1 . To gain insights into the antiapoptotic activity of M11 , we analyzed the interaction between the apoptosis mediators BAX and BAK with M11 . First , 293T cells were transfected with HA-tagged BAK or Flag-tagged BAX , together with each of four different GST-tagged prosurvival BCL-2 proteins including M11 . These proteins , all in the full-length form , were transiently expressed . A following immunoprecipitation assay revealed that M11 exhibited a tight interaction with BAK ( Figure 5A , left panel , lane 3 ) and a comparatively weak interaction with BAX ( Figure 5A , right panel , lane 2 ) . The M11 binding to BAX and BAK , as expected , depended on its intact BH3-binding groove , as triple mutations on the groove abrogated the binding interactions ( Figure 5A ) . Definitely , the M11 binding to BAK was significantly tighter than the BCL-2 binding to BAK ( Figure 5A , left panel , lane 6 ) . However , the M11 binding to BAX appeared to be comparable at most or weaker compared with the BCL-2 binding to BAX ( Figure 5A , right panel , lane 5 ) . In this cell-based assay , KSHV BCL-2 also interacted strongly with BAK ( Figure 5A , left panel , lane 5 ) . However , its interaction with BAX was barely detected ( Figure 5A , right panel , lane 4 , and Figure S5 ) , indicating that KSHV BCL-2 has much poorer affinity for BAX than M11 . These results suggested that M11 could inhibit BAK strongly but BAX weakly and that the apoptosis inhibition by KSHV BCL-2 may not be through neutralizing BAX . Next , we quantified the interactions of M11 with 26-mer peptides containing the BH3 domain of BAX or BAK . In the analysis using ITC , M11 interacted with the BAX peptide weakly , exhibiting a KD of 690 nM ( Figure 5B ) . In contrast , M11 interacted much more tightly with the BAK peptide with a KD of 76 nM ( Figure 5B ) . These measured binding affinities explain and correlate with the cell-based binding assay using the full-length proteins of M11 , BAX and BAK . We noted that 16-mer peptide ( residues 69–84 ) , shorter but spanning the BH3 domain of BAK , produced a flat titration curve and its binding affinity for M11 could not be deduced , and thus a longer BH3-containing sequence of BAK is required for tight binding to M11 . In reflection of the binding assay , the interaction between M11 and endogenous BAK could be easily detected in NIH3T3 cells ( Figure 5C ) . Also using ITC , we next analyzed the interactions between M11 and the BH3 domain-containing peptides of the eight well-studied BH3-only proteins BAD , BIK , BIM , BID , BMF , PUMA , Noxa and Hrk that act upstream of BAX/BAK . These BH3 peptides , containing 24 to 27 amino acids , are the same as or 1 to 2 residues longer than those used by Chen et al . for studying the interactions between the BH3-only proteins and a cohort of prosurvival BCL-2 proteins [40] . In their study , the long BH3 peptides did not appear to pose a problem of reduced helical propensities , because they bound to at least one of the BCL-2 proteins potently . Given this observation and the short BH3-binding groove of M11 , which can be fully spanned by 19 residues of Beclin1 ( Figure 2A ) , we conclude that the length of the BH3 peptides is likely to be optimal . As shown in Figure 6 and Table S2 , M11 interacted with the BIM , Noxa , BID , BMF and PUMA peptides fairly tightly with the KD values ranging from 131–370 nM , while it interacted with the Hrk peptide rather weakly ( KD of 719 nM ) . However , M11 did not interact or poorly interacted with the BAD and BIK peptides such that KD values could not be deduced . Using an optical biosensor , Chen et al . previously quantified the interactions between the entire cohorts of the cellular antiapoptotic BCL-2 relatives with the BH3 domain peptides of the BH3-only proteins [40] . A comparison of these data with our results shows that M11 is dissimilar from any of the five cellular BCL-2 homologues in the selectivity and affinity for the BH3 domain peptides ( Table S1 ) . For example , while M11 has high affinity for the Noxa peptide but negligible affinity for the BAD peptide , BCL-2 exhibits the opposite binding affinity for the two peptides ( Table S1 ) . Importantly , M11 binds tightly the BH3 domain peptides of BIM and PUMA , which have potent cell-killing activity probably owing to their selectivity for all the five anti-death BCL-2 relatives [40] . Moreover , M11 exhibited extremely poor binding affinity for the BH3 domain peptides of BAD and BIK , which have limited selectivity for BCL-2/BCL-XL and relatively poor apoptotic activity [40] .
A newly identified function of BCL-2 is the down regulation of autophagy through their inhibitory binding to Beclin1 , which appears critical for cellular homeostasis [30] . As shown by others [32] and in this study , the BCL-2/BCL-XL interaction with Beclin1 is quite weak compared with their interactions with the BH3-only proteins such as BAD and BIM [40] . The weak interaction explains the recent observation that endogenous BH3-only proteins induce autophagy by displacing Beclin1 from BCL-2/BCL-XL [31] . Like the cellular kin , two viral BCL-2 proteins from γHV68 and KSHV are known to inhibit autophagy in addition to suppressing apoptotic death of cells [28 , 30] . In this study , we provided the structural basis for the inhibitory interaction of M11 with Beclin1 , which is reminiscent of the canonical interaction between a BH3 peptide and a BH3-binding groove . Significantly , M11 bound to Beclin1 ( 101–267 ) more tightly than BCL-2 did . Furthermore , the affinity of binding ( KD of 40 nM ) between M11 and Beclin1 ( 101–267 ) was higher than that between M11 and any of the ten different BH3 peptides used in this study . As a confirmatory experiment , we carried out a displacement test , where a complex between two proteins was challenged by another protein . Consistent with our affinity measurement , the M11–Beclin1 ( 101–267 ) complex remained intact when it was incubated with the BIM , BID or Noxa peptide ( Figure S6A ) . In contrast , the BCL-2–Beclin1 ( 101–267 ) or BCL-XL–Beclin1 ( 101–267 ) complex was easily disrupted by BAD or BIM peptide ( Figure S6B ) . Conceivably , M11 could negate the proautophagic role of the BH3-only proteins under apoptosis-inducing conditions in contrast with BCL-2/BCL-XL . The observed robust interaction of M11 with the Beclin1 fragment , which correlates with its strong antiautophagic effect in NIH3T3 cells ( Figure 4 ) , suggests that Beclin1 may be a main target of M11 and that the inhibition of autophagy may contribute to the viral infection of cells . Viral BCL-2 homologues , including M11 , share limited sequence homology with the cellular kin [2] . Nonetheless , two available structures of KSHV BCL-2 and M11 have demonstrated that they are structurally homologous to the cellular kin and possess a prominent surface groove which binds the BH3 domain peptides from proapoptotic BCL-2 family members [7 , 41] . While the known BCL-2 homologues encoded by alpha and gamma herpesviruses exhibit only 20–30% overall sequence homology with each other [2] , we noted that the residues of M11 significantly involved in the interactions with the Beclin1 fragment share 60–90% sequence similarity with the corresponding residues of the other herpesviral BCL-2 proteins ( Figure S7 ) . This observation raises a possibility that at least some alpha and gamma herpesviral BCL-2 homologues could interact with the BH3-like domain of Beclin1 . In addition , some structural viral mimics of BCL-2 , such as M11L of Myxoma virus [33] and N1 of Vaccinia virus [42] , might also interact with Beclin1 through their BH3-binding groove . The underlying mechanism of how viral BCL-2 homologues or mimics suppress apoptosis is not well understood . Perhaps M11L of Myxoma virus is best characterized in this regard . Through structural and biochemical analyses , M11L was shown to bind BAX , BAK and BIM proteins or peptides tightly but not the other proapoptotic BH3-only proteins [33] . Using a panel of M11L mutants containing an amino acid substitution at the BH3-binding groove , it was demonstrated that the prosurvival action of M11L largely depended on binding BAX and BAK [33] . The observation is consistent with a general expectation that viral BCL-2 would prefer to target BAX/BAK rather than the upstream BH3-only proteins [1] . In contrast with the binding selectivity of M11L , our quantitative binding analysis indicated that M11 primarily targets BAK , but not BAX , and broadly engages the BH3-only proteins except for BAD and BIK ( Figure 7 ) . How could M11 , having the weak binding affinity for BAX , antagonize apoptosis of cells following the rise of the concentration of the activated BH3-only proteins under apoptosis-inducing conditions ? We speculate that the neutralization of a subset of the BH3-only proteins ( including BIM , BID , BMF , PUMA and Noxa ) by M11 should prevent them from engaging their cellular prosurvival BCL-2 targets , and this protection would allow some fractions of the prosurvival proteins to keep suppressing the activation of BAX . This possibility is relevant to the suggestion that all the BCL-2 relatives keep BAX in check , whereas only BCL-XL and MCL-1 inhibit BAK according to the so-called indirect activation model [18] . In this scenario , although M11 cannot neutralize BAD and BIK , MCL-1 , having very low affinity for BAD and BIK [40] , and other prosurvival protein molecules saved by M11 can inhibit BAX when M11 is expressed in the infected cell . An alternative possibility is that M11 inhibits the BAX activation by neutralizing BIM , BID , and PUMA , which are believed to directly activate BAX/BAK according to the hierarchical regulatory scheme [17] . Although further investigations may shed light on this important issue , the data presented here , including the weak interaction of KSHV BCL-2 with BAX ( Figures 5A and S5 ) , suggest that viral BCL-2 homologues may not necessarily target both BAX and BAK to suppress apoptosis . We provided structural and biochemical bases for how M11 may subvert the antiviral host defense mechanisms , which is likely to involve both apoptosis and the Beclin1-dependent autophagy . Further studies are necessary to assess the importance of the Beclin1-dependent autophagy as an antiviral measure and to understand the consequences of the robust interaction of M11 with Beclin1 in the establishment and/or maintenance of the viral chronic life cycle . Our work provides a rational ground for future investigation to learn whether the inhibition of the Beclin1-dependent autophagy is the unique property of M11 and KSHV BCL-2 or is a general feature of other viral BCL-2 homologues or mimics .
The DNA fragments coding for M11 ( residues 1–137 ) and mouse Beclin1 ( residues 101–150 ) were cloned into pET30a ( Novagen ) and pPROEX HTa ( Invitrogen ) , respectively . From these vectors , a two-promoter vector was constructed for coexpression of the two proteins . The protein complex was produced in E . coli BL21 ( DE3 ) strain ( Novagen ) at 21 °C overnight and purified using a Ni-NTA column ( QIAGEN ) , a Hitrap Q anion exchange column ( Amersham Pharmacia ) and a Mono Q anion exchange column ( Amersham Pharmacia ) , equilibrated with 20mM Tris-HCl ( pH 8 . 0 ) , 220mM NaCl and 1mM dithiothreitol . Crystals of the complex were obtained by the hanging-drop vapor diffusion method at 24 °C by mixing and equilibrating 1 μl of each of the protein solution ( 10 mg/ml ) and a precipitant solution containing 25% ( w/v ) polyethylene glycol 3350 , 0 . 2 M magnesium chloride , and 0 . 1 M imidazole ( pH 7 . 0 ) . Before data collection , the crystals were immersed briefly in a cryoprotectant solution , which was the reservoir solution plus 10% glycerol . A diffraction data set at 2 . 3 Å resolution was collected on the beamline 4A at the Pohang Accelerator Laboratory , Korea , and processed using the programs DENZO and SCALEPACK [43] . The structure was determined by the molecular replacement method with the CCP4 version of MolRep [44] using the structure of M11 [7] as a search model . Subsequently , model building and refinement were carried out using the programs O [45] and CNS [46] . The final model does not include residues 1–4 and 136–137 of M11 , and residues 101–105 and 125–150 of Beclin1 , whose electron densities were not observed or were very weak . The DNA fragment coding for mouse BCL-XL ( residues 1–196 ) was cloned into pPROEX HTa . This construct was used as a template for deletion mutagenesis to produce BCL-XL lacking the internal long loop ( residues 45–84 ) and the C-terminal tail region ( residues 197–235 ) . DNA fragment coding for mouse BAD ( residues 43–204; corresponding to residues 1–168 of human BAD ) was cloned into pET30a . A two-promoter vector was constructed from these two vectors . The protein complex was expressed in the E . coli BL21 ( DE3 ) RIG strain ( Novagen ) at 21 °C overnight and purified using a Ni-NTA column , a Hitrap Q anion exchange column and a HiLoad 26/60 Superdex 75 gel filtration column ( Amersham Pharmacia ) , equilibrated with 20mM Tris-HCl ( pH 8 . 0 ) , 100mM NaCl , and 1mM dithiothreitol . Crystals of the complex were obtained by the hanging-drop vapor diffusion method at 4 °C by mixing and equilibrating 1 μl of each of the protein solution ( 5 mg/ml ) and a precipitant solution containing 10% ( w/v ) polyethylene glycol 1000 and 10% ( w/v ) polyethylene glycol 8000 . Before data collection , the crystals were immersed briefly in a cryoprotectant solution , which was the reservoir solution plus 16% glycerol . A diffraction data set at 2 . 3 Å was collected on the beamline 41XU at the Spring-8 , Japan . The structure was determined by the molecular replacement using the structure of BCL-XL [47] as a search model . The final model does not include residues 31–44 of BCL-XL , and residues 43–136 and 164–204 of BAD . Crystallographic data statistics are summarized in Table 1 . Each of the DNA fragments coding for M11 ( residues 1–137 ) , mouse BCL-XL ( residues 1–44 and 85–196 ) or mouse Beclin1 ( residues 101–267 ) was cloned into pPROEX HTa . A plasmid containing the DNA segment coding for human BCL-2 ( residues 1–50 and 92–207 ) was also constructed . The resulting protein lacks the internal long loop ( residues 51–91 ) and contains a replacement of residues 35–50 with residues 33–48 of BCL-XL , which was necessary for the solubility of the protein as reported earlier [48] . Each construct was introduced into the E . coli BL21 ( DE3 ) strain . The proteins were expressed at 21 °C overnight and purified using a Ni-NTA column and a Hitrap Q anion exchange column . Synthetic peptides of 25-mer ( residues 101–125 of Beclin1 ) , 20-mer ( residues 106–125 of Beclin1 ) , 16-mer ( residues 69–84 of BAK ) , 26-mer ( residues 65–90 of BAK ) , 26-mer ( residues 52–77 of BAX ) , 27-mer ( residues 137–163 of BAD ) , 25-mer ( residues 45–69 of BIK ) , 26-mer ( residues 139–164 of BIM ) , 25-mer ( residues 80–104 of BID ) , 24-mer ( residues 214–237 of BMF ) , 26-mer ( residues 130–155 of PUMA ) , 26-mer ( residues 16–41 of Noxa ) , and 26-mer ( residues 26–51 of Hrk ) were purchased from Peptron ( Korea ) . All measurements were carried out at 25 °C on a MicroCalorimetry System ( MicroCal ) . Protein samples were dialyzed against the solution containing 20 mM Tris-HCl ( pH 7 . 4 ) and 100 mM NaCl . The samples were degassed for 20 min and centrifuged to remove any residuals prior to the measurements . Dilution enthalpies were measured in separate experiments ( titrant into buffer ) and subtracted from the enthalpies of the binding between the protein and the titrant . Data were analyzed using the Origin software ( OriginLab Corp . ) . Autophagy was assessed by GFP–LC3 redistribution and LC3 mobility shift . For GFP–LC3 redistribution assay , NIH3T3 cells were transfected with a GFP–LC3 expression plasmid together with the vector encoding BCL-2 , M11 , or M11 ( AAA ) . At 16–18 h posttransfection , GFP–LC3 in the cells grown under normal and 2 μM rapamycin-treated medium containing 1% FBS for 4 h was detected using an inverted fluorescence microscope . The percentage of GFP–LC3-positive cells with punctuate staining was determined in three independent experiments . To quantify GFP–LC3-positive autophagosomes per transfected cell , six random fields representing 200 cells were counted . For the LC3 mobility shift assay , NIH3T3 cells transfected with the vector encoding BCL-2 , M11 or M11 ( AAA ) were treated for 30 min on ice , lysed with 1% Triton X-100 and then subjected to immunoblot analysis with an antibody against LC3 ( Santa Cruz Biotech ) . Each of fusion protein GST–BCL-2 , GST–KSHV BCL-2 , GST–M11 and GST–M11 ( AAA ) was cloned into pcDNA5/FRT/TO ( Invitrogen ) and overexpressed in 293T cells together with HA-tagged BAK or Flag-tagged BAX . HA–M11 , HA–M11 ( AAA ) and HA–BCL-2 proteins were also cloned into pcDNA5/FRT/TO and overexpressed in NIH3T3 cells , respectively . Cells were harvested and lysed in NP40 buffer supplemented with a complete protease inhibitor cocktail ( Roche ) . Immunodetection was achieved with anti-Flag ( 1:5000 ) ( Sigma ) , anti-HA ( 1:5000 ) , anti-GST ( 1:2000 ) , anti-tubulin ( 1:1000 ) , anti-BAK ( 1:100 ) , or anti-Beclin1 ( 1:500 ) ( Santa Cruz Biotech ) , which was incubated at 40 °C for 8–12 h . The proteins were visualized by a chemiluminescence reagent ( Pierce ) and detected by LAS 3000 ( Fujifilm ) . Data were collected on a JASCO model J-810 spectropolarimeter with a 0 . 2 cm cuvette . CD spectrum was recorded over the range of 200–250 nm in a nitrogen atmosphere with peptides dissolved in 40 mM sodium phosphate buffer ( pH 7 . 0 ) containing 30% TFE at the concentration of 0 . 1 mg/mL . The spectrum was the accumulation of three scans corrected by subtracting signals from the buffer control . The law CD signal at 222 nm ( in millidegrees ) was converted to mean residue ellipticity ( [θ]obs , in deg . cm2 . dmol−1 ) using the equation where C is the peptide concentration ( in millimolarity ) , n is the number of residues in the peptide , and l is the pathlength ( in cm ) . The contents of helix ( Fhelix ) was calculated using the equation where [θ]helix represents the mean residue ellipticity for a complete helix of infinite length at 0 °C ( −42 , 500 ( 1−3/n ) deg . cm2 . dmol−1 ) and [θ]coil is the ellipticity of a complete random coil at 0 °C ( 640 deg . cm2 . dmol−1 ) [49 , 50] .
The coordinates of the M11–Beclin1 fragment structure and the BCL-XL–BAD structure have been deposited in the Protein Data Bank ( http://www . rcsb . org/pdb/ ) with the accession codes 3BL2 and 2BZW , respectively . The accession numbers for the coordinates for the structures mentioned in this article are M11 ( 2ABO ) , BCL-XL ( 1AF3 ) , BCL-XL–Beclin1 ( 2P1L ) , BCL-XL–BAK ( 1BXL ) , BCL-XL–BIM ( 1PQ1 ) , MCL-1–BIM ( 2NL9 ) , and KSHV BCL-2 ( 1K3K ) . The National Center for Biotechnology Information ( http://www . ncbi . nlm . nih . gov/ ) accession numbers for the protein sequences in the sequence databases are mouse Beclin1 ( NP_062530 ) , BCL-XL ( NP_033873 ) , BAX ( NP_031553 ) , BAK ( NP_031549 ) , BAD ( NP_031548 ) , BIK ( NP_031572 ) , BIM ( NP_997563 ) , BID ( NP_031570 ) , BMF ( NP_612186 ) , PUMA ( NP_573497 ) , Noxa ( NP_067426 ) , Hrk ( NP_031571 ) , human Beclin1 ( NP_003757 ) , BCL-XL ( NP_612815 ) , BCL-2 ( NP_000624 ) , MCL-1 ( NP_068779 ) , BAK ( NP_001179 ) , BIM ( NP_619527 ) , xlBeclin1 ( AAH73292 ) , trBeclin1 ( NP_001032963 ) , dmBeclin1 ( NP_651209 ) , scBeclin1 ( BAA32104 ) , M11 ( AAF19336 ) , KSHV BCL-2 ( NP_572068 ) , RRV ORF16 ( AAF59994 ) , BHV4 BORFB2 ( NP_076508 ) , HVS ORF16 ( CAA73630 ) , MeHV BCL-2 ( NP_073365 ) , EBV BHRF1 ( CAD53396 ) , and EHV2 ORFE4 ( NP_042601 ) . | In higher animals , defective or surplus cells are removed by a process known as apoptosis . On the other hand , defective or damaged cellular components are removed by a process known as autophagy . These two destructive processes are indispensable for the survival and development of an organism . While apoptosis is known as a central host defense mechanism that removes virus-infected cells , the role of autophagy against viral infection has recently emerged . Many viruses express an armory of viral proteins that counteract cell death–mediated innate immune control . One such protein is a homologue of the cellular BCL-2 protein that suppresses apoptosis through inhibitory binding to apoptosis-promoting proteins . Murine γ-herpesvirus 68 also encodes a viral BCL-2 , known as M11 . In this study , we quantitatively measured the binding affinity of M11 for its potential cellular targets , including ten different proapoptotic proteins and the proautophagic protein Beclin1 . We found that M11 neutralizes the proapoptotic proteins broadly rather than selectively to suppress apoptosis . Surprisingly , M11 bound to Beclin1 with the highest affinity , which correlated with its strong antiautophagic activity in cells . These data suggest that M11 suppresses not only apoptosis but also autophagy potently , which ultimately contributes to the viral chronic infection . | [
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] | 2008 | Structural and Biochemical Bases for the Inhibition of Autophagy and Apoptosis by Viral BCL-2 of Murine γ-Herpesvirus 68 |
Precise temporal coordination of gene expression is crucial for many developmental processes . One central question in developmental biology is how such coordinated expression patterns are robustly controlled . During embryonic development of the Drosophila central nervous system , neural stem cells called neuroblasts express a group of genes in a definite order , which leads to the diversity of cell types . We produced all possible regulatory networks of these genes and examined their expression dynamics numerically . From the analysis , we identified requisite regulations and predicted an unknown factor to reproduce known expression profiles caused by loss-of-function or overexpression of the genes in vivo , as well as in the wild type . Following this , we evaluated the stability of the actual Drosophila network for sequential expression . This network shows the highest robustness against parameter variations and gene expression fluctuations among the possible networks that reproduce the expression profiles . We propose a regulatory module composed of three types of regulations that is responsible for precise sequential expression . This study suggests that the Drosophila network for sequential expression has evolved to generate the robust temporal expression for neuronal specification .
Precise coordination of cell fate decisions is crucial in the development of multicellular organisms . In the developmental processes , where a series of events occurs at a specific place and time , gene regulatory networks are responsible for implementing reliable biological functions [1] , [2] . To obtain system-level understanding of such processes , it is necessary to integrate the molecular machinery of each regulation with architecture and dynamics at the regulatory network level . Biological functions achieved by gene networks are generally expected to possess robustness , i . e . , insensitivity of system properties against a variety of perturbations that might originate from fluctuations during development and mutations through evolution . Recent investigations have addressed the questions of how robust biological functions are achieved through underlying molecular network architecture and its dynamic properties [3] , [4] , [5] , [6] , [7] . An illustrative example in developmental systems on this subject is segmentation of Drosophila melanogaster , which has been studied both experimentally and theoretically [8] , [9] , [10] . The requisite regulations or architecture of this system have been discussed at the network description level [10] , [11] , [12] , [13] , , and it is suggested that the underlying gene network has evolved to perform its processes in a robust manner [15] , [16] , [17] . Besides spatial patterning , temporal profiles of gene expression also play important roles in development [18] , [19] , [20] . Several computational studies have analyzed temporal expression profiles in biological processes such as the midgut development of sea urchin [21] , [22] and vulval development of C . elegans [23] . These studies have shown relevant regulatory interactions and predicted unknown regulations for cell-fate specification . The development of the Drosophila central nervous system ( CNS ) also manifests the importance of temporal patterning mechanism in development . Drosophila neural stem cell-like progenitors , called neuroblasts ( NBs ) , generate a variety of neural cell types . During the embryonic development of the Drosophila CNS , NBs in the ventral nerve cord express certain transcription factors , i . e . , Hunchback ( Hb ) , Krüppel ( Kr ) , Pdm1/Pdm2 ( Pdm ) , and Castor ( Cas ) , in a definite order ( Fig . 1A–C ) [24] , [25] , [26] , [27] . In addition , the fifth factor , Seven-up ( Svp ) , is expressed in the time window between Hb and Kr expression [28] . In association with this sequential expression , NBs divide asymmetrically to bud off a series of ganglion mother cells ( GMCs ) . Each GMC undergoes an additional division to typically generate two postmitotic neurons . Depending on the transcription factors expressed in NBs at each division , postmitotic neurons acquire different cell fates . Thus , the sequentially expressed transcription factors control the cell-fate specification , thereby establishing the diversity of neurons in the Drosophila CNS . While neuronal specification process and generated cell types also depend on the spatial position [29] , [30] , [31] and lineage [32] , [33] of NBs , the sequential expression is observed in a majority of ventral nerve cord NBs [34] . Isolated NBs exhibit sequential expression in vitro and differentiate into various neurons in a manner similar to that observed in vivo [35] , [36] . Hb expression is switched off by Svp in a mitosis-dependent manner , while the subsequent expression of Kr , Pdm , and Cas proceeds in a mitosis-independent manner [28] , [37] . These observations suggest that sequential expression of the genes is regulated cell-autonomously and occurs through mutual interactions among the factors . In this study , we address the robustness of the gene network for sequential expression in the Drosophila CNS . One of the promising approaches to obtain insights into the system-level properties of biological systems is to compare the robustness of the actual network with that of other possible network architectures . Wagner considered how network architecture and robustness are related by studying circadian oscillation networks [38] , although these networks lack a direct biological counterpart . Ma et al . studied the robustness of the Drosophila segmentation network [39] , in which they had to arbitrarily eliminate components to reduce the size of the entire network . From theoretical and computational points of view , one advantage of studying temporal patterning in the Drosophila CNS is that the number of system components is so small that we can perform a comprehensive analysis of network architecture without any loss of biological relevance . First , we explored the regulatory networks to reproduce the observed expression patterns in both wild-type ( WT ) and mutant embryos . We did not confine ourselves to only known regulations for sequential expression , but rather searched all possible networks that could reproduce the observed expression patterns . Studying the common structure of the specified genetic networks , we detected requisite regulations and predicted an unknown factor to reproduce known expression profiles . Second , we compared the robustness of the actual Drosophila network with that of the other networks reproducing the expression profiles . As a measure of robustness , we analyzed the stability of sequential expression against parameter variations and gene expression fluctuations . We found that the Drosophila network is highly robust and stable among possible functional networks . By further investigating the regulations necessary for the Drosophila network to be robust , we detected the responsible regulations . We propose a regulatory module composed of three kinds of regulations that is responsible for precise sequential expression of the Drosophila network .
Expression profiles of temporal transcription factors ( hb , Kr , pdm , cas , and svp ) in Drosophila NBs are summarized in Figure 1D for WT , loss-of-function , and overexpression embryos [25] , [26] , [28] , [36] , [40] , [41] . It has been considered that these sequential expressions are produced ( or at least modulated ) by mutual regulations among the temporal transcription factors [24] , [25] . We reconstructed the gene network for sequential expression in Drosophila NBs from the literature as shown in Figure 1E and F ( for references , see Table 1 ) . First , we searched for regulatory networks that reproduce the sequential expression patterns of both WT and mutants . To investigate gene expression dynamics , we adopted a Boolean-type model [6] ( see Materials and Methods for details of the model and the following analysis ) : ( 1 ) where represents the expression state of gene i ( ) at the t-th time step and takes either 1 ( ON ) or 0 ( OFF ) . Regulation from gene j to gene i is either positive ( Jij >0 ) , negative ( Jij <0 ) , or zero ( Jij = 0 ) , which corresponds to activation , repression , or absence of regulation , respectively . The state of gene i at the next step ( ) is 1 when the sum of regulatory inputs is positive ( ) or 0 when the sum is negative ( ) . When the sum equals zero ( ) , takes the default expression state : . In this study , the value of Jij is supposed to take one of the discrete values . The large negative value ( −5 ) of Jij signifies that the expression of a gene is completely shut off in the presence of a repressor . This choice of large negative value comes from experimental observations of mutants . In experimentally observed expression patterns ( Fig . 1D ) , genes are not activated when both repressors and activators are expressed . For example , in Kr++ and pdm++ embryo ( here “++” means overexpression of the gene ) , pdm and cas expression is not observed in hb-expressing time window , although their activators are overexpressed . This indicates that the repressive effect from hb is dominant over pdm activation by Kr and cas activation by pdm . Initial expression state of genes is set to 0 , except for Hb , which emulates the NB gene expression in the first stage of sequential expression [24] , [25] . Thus far , the only known function of Svp during the early stage is downregulation of Hb . There is no evidence that Svp regulates or is regulated by other temporal transcription factors during the expression series: Kr Pdm Cas [28] . In addition , Hb is only regulated by Svp and not by the other three factors ( Kr , Pdm , and Cas ) . Thus , in the model , we assumed a pulsed expression of Svp as an input to the system , resulting in downregulation of Hb at the next time step . The temporal expression dynamics of Kr , Pdm , and Cas follow Eq . ( 1 ) with assigned values of Jij ( Fig . 1F ) . Based on the above formulation , we investigated whether the reconstructed Drosophila gene network ( Fig . 1E and F ) is sufficient to reproduce the sequential expression observed in WT , as well as all the known single loss-of-function and overexpression mutants , i . e . , hb− , Kr− , pdm− , cas− , hb++ , Kr++ , pdm++ , and cas++ ( Fig . 1D , Table 2 ) . Presently , we cannot specify the value of the parameters , and from empirical data; thus , each value could be arbitrarily chosen from ( ) . We studied all 23 combinations of and found that the dynamics coincide with the expression profile in WT but not in some mutants for each choice of parameters ( examples shown in Fig . 2 ) . Depending on the parameter values , the expression dynamics changed to some extent , but none of the possible combinations reproduced the expression profiles of all of the mutants . For example , in case of , , and , the dynamics of the network for hb− and Kr− did not agree with the experiments ( Fig . 2A ) , and in case of , , and , the dynamics of hb− and pdm− did not ( Fig . 2C ) . We then investigated whether networks other than the Drosophila network can reproduce the observed expression profiles by checking all the 312 ( = 531 , 441 ) combinations of Jij values . The dynamics agreed with the expression profile in WT for a large number of networks ( 39 , 391 out of 531 , 441 ) , but any networks composed of hb , Kr , pdm , cas , and svp did not reproduce the profiles in both WT and mutants . Preceding results indicate the difficulty of reproducing the observed expression patterns only with known constituents . We therefore introduced an additional presumptive regulator ( x ) . The expression state of x was assumed to start in the ON state and change into OFF , or vice versa at ( ) ( see Materials and Methods ) . Including this assumption , we reinvestigated the dynamics of all 315 ( = 14 , 348 , 907 ) possible regulatory networks with all the possible switching timings of x . In the case that the expression of x switches OFF to ON , none of the networks conformed to the expected expression profiles . On the other hand , in the case that the expression of x switches ON to OFF , we found that 384 networks ( <0 . 003% ) reproduced the expression profiles of both WT and mutants . We refer to the detected networks as “the functional networks” hereafter in the study . Comparing the regulatory interactions of the functional networks , we found that the regulations shared among all the functional networks are coincident with experimentally verified regulations ( colored as black in Fig . 3A ) . In addition , activation of Kr and repression of cas by a presumptive factor x appear in all of the functional networks ( colored as brown in Fig . 3A ) . The genetic network composed of these common regulations is a minimum network to reproduce the expression profiles of WT and mutants . To quantify the similarity among the functional networks , we measured the distances of the 384 functional networks from the actual Drosophila network ( Fig . 3C ) ; the distances are defined by the number of different regulations ( see Materials and Methods ) . As a reference , we also performed the same analyses of distance measurement for all possible networks and the networks that are randomly reconnected from functional networks ( see Materials and Methods ) . For all possible networks , the frequency distribution of the distances shows that the network architectures are different from the actual Drosophila network by 7 . 81 . 5 regulations . The reconnected networks yield similar results , albeit with slightly decreased distances ( 7 . 01 . 7 regulations ) . In contrast , the architectures of the functional networks differ by only 2 . 41 . 1 regulations . The architectures of the functional networks resemble that of the actual Drosophila network . These indicate that the gene networks that reproduce the known sequential expression patterns are highly constrained in their topologies . Because there are multiple network architectures that explain the observed expression profiles as shown above , we then investigated the characteristics of the actual Drosophila network among the functional networks . From the biological point of view , the sequential expression in NBs should proceed reliably despite developmental disturbances such as cell-to-cell variation and intracellular fluctuations . We thus evaluated the stability of sequential expression for each of the detected functional networks and compared the properties of the actual Drosophila network to those of the other networks . To address the problem quantitatively , we extended the previous Boolean model into a model of ordinary differential equations with fluctuations in gene expression , where the concentrations of mRNAs {Mi ( t ) } and proteins {Pi ( t ) } obey the following equations [42] , [43] ( see Materials and Methods for the details of the model and the following analysis ) : ( 2 ) Here i refers to one of each gene: . The variables {Mi ( t ) } and {Pi ( t ) } take continuous values , unlike the previous Boolean description . The precise function form of promoter activities {Fi ( {Pj ( t ) } ) } is dependent on the regulatory interactions of the genetic networks and the default promoter activities {Si} , corresponding to the Boolean model . The time-dependent variables represent the noise in promoter activities . Here we have assumed that the expression noise comes from the transcription process ( noise is incorporated only in the dynamics of {Mi ( t ) } ) . One reason is the practical convenience in the numerical calculations . In addition , recent quantitative analyses of gene expression have indicated that the gene expression noise mainly arises from transcription [44] , [45] , [46] . However , we should note that the result and conclusion obtained from the following analysis does not change even if we incorporate noise in the dynamics of {Pi ( t ) } as well ( data is not shown ) . Typical dynamics of the Drosophila network are shown in Figure 4 , where sequential expression of WT is reproduced . The dynamics of the model are largely dependent on the parameter values and the noise intensities , and coincide with the experimental observations only under appropriate conditions . Therefore , such sensitivity to parameter variation is important for the development to proceed under environmental and individual fluctuations . To characterize sensitivity , we measured the fraction of successes; that is , the fraction of the parameter sets that can reproduce the expression profile of WT among all the trials of random parameter assignments [15] , [39] . To judge whether the dynamics coincide with the expression profile in Drosophila NBs , the dynamics of the protein concentrations {Pi} were discretized to 1 ( 0 ) for Pi > Pth ( Pi < Pth ) . The threshold Pth was set as Pth = 0 . 2 . The temporal dynamics of a network were accepted when the discretized dynamics satisfied the condition for WT in Table 3 . To obtain the effect of parameter variation , we carried out the simulation without stochastic terms in Eq . ( 2 ) . In each network , we repeated the simulations with random assignment of parameter values and calculated the fraction of successes ( Fig . 5A ) . The Drosophila network scored the highest fraction of successes among the functional networks , and the networks closer to the Drosophila network tended to have higher scores . We also investigated the dynamical stability of the gene networks against fluctuations . In this case , we performed the stochastic simulations in Eq . ( 2 ) with expression noise . To evaluate stability against noise , we chose the parameter values with which the expression profile is reproduced in the absence of noise . We then measured the relative fraction of successes under fluctuation . As is shown in Figure 5B , the fraction of successes under expression noise increased with the similarity to the actual Drosophila network as the fraction of successes under parameter variations . Thus , the Drosophila network lies at the top level of the functional networks in terms of robustness against these perturbations . Because the Drosophila network has several other regulations in addition to the minimum functional network ( gray arrows in Fig . 3A ) , these regulations might be responsible for the robustness shown above . We compared the robustness among the networks with or without the additional regulations . The fraction of successes against parameter variations for these networks is plotted in Figure 6A . The minimum network reproduces the sequential expression under the appropriate parameters , but the robustness is much lower than that of the Drosophila network . The scores of networks that lack one of the regulations fall between the minimum and the Drosophila network . Stability to expression noise was also evaluated by changing noise intensity , and similar results were obtained ( Fig . 6B ) . The fraction of successes decreased as the noise intensity became larger , but the effect of noise on the Drosophila network was less severe than that on the minimum network . Thus , each of these regulations contributes to the robustness of the system . To elucidate the roles of these regulations , we tried random parameter assignments for each of these networks and sampled successful parameter sets that reproduce WT sequential expression profile ( Fig . 7 ) . In the Drosophila network ( Fig . 7A ) , wide ranges of parameter values are allowed , indicating that this network reproduces the required profile without quantitative tuning of parameters , and thus , shows high robustness . For other networks ( Fig . 7B–E ) , the ranges are narrower for some parameters ( as clearly seen in Spdm and Scas ) , and the numbers of successful parameter sets are less than those obtained for the Drosophila network . How is the robust nature of the Drosophila network implemented by these regulations ? As seen above , the parameter values of Spdm and Scas ( default promoter activities of pdm and cas ) are most influenced by the loss of these regulations . Because expression of a gene is induced by either the activity of the default promoter or the activators ( see Materials and Methods ) , additional regulations in the Drosophila network ( gray arrows in Fig . 3A ) might compensate for the loss of default activities . To verify this possibility , we measured the dependence of the fraction of successes on the strength of regulations ( , , and ) and default promoter activities ( Spdm and Scas ) ( Fig . 8A–C ) . Figure 8A shows the fraction of successes for random assignments of parameter values under given strengths of and Spdm . To score high reproducibility , Spdm must be large for small , but need not to be large for sufficiently large . This indicates that activation of pdm expression by Kr indeed compensates for the loss of default promoter activity of pdm . Thus , for the network lacking this regulation , the default promoter activity is necessary because inductions from other factors are absent . A similar relationship is found between and Scas ( Fig . 8B ) . As for repression of cas by hb , the role for robustness seems to be different from the above two . When the absolute value of is small , Scas must be small to achieve a high fraction of successes ( Fig . 8C ) . As becomes larger , a higher value of Scas is allowed . This is because the repression from hb to cas reduces the mis-expression of cas in the early stage of sequential expression . Grosskortenhaus et al . suggested the direct repression from hb to cas [26] , although there is no confirmative evidence to our knowledge . This regulation possibly contributes to the robustness of the actual system .
In this study , we introduced an additional presumptive factor x to obtain networks that reproduce the sequential expression of both WT and mutants . Because x is hypothetical , we discuss its validity here . Because the loss-of-function mutant of any one gene has only minor effects on the expression sequence ( Fig . 1D ) , several previous reports suggested the existence of either unknown regulators or an additional clock mechanism that regulates the sequential expression [25] , [26] . Our assumption is feasible for explaining experimental results because it does not need any other clock mechanism or superfluous multiple regulators . It is notable that our analysis indicates that the possible regulations of the presumptive factor are highly restricted; the expression of x switches ON state to OFF state ( Fig . 4 ) , and all the functional networks have activation of Kr and repression of cas by x ( Fig . 3A ) . Thus , our assumption can be tested in future experiments in vivo . We should note that while the regulator x is needed to explain the mutant profiles under our modeling assumptions , the mutual regulations of only known factors also reproduce the WT sequential expression ( Fig . 1D ) . Therefore , the regulations among hb , Kr , pdm , and cas would play a primary role as discussed below . An effective way to capture network function is to focus on the specific substructures ( network motifs or modules ) [1] , [13] , [14] , [16] , [39] , [47] . Comparing all the functional networks , we detected the minimum structure for the sequential expression , which contains two successive regulatory loops ( Fig . 3A and 9A ) ; one is composed of hb , Kr , and pdm , and the other of Kr , pdm , and cas . In each loop , one gene represses the previous and the second next factor . The repressions of the second next factors ( hb to pdm and Kr to cas ) define the induction timing of the regulated factors , since they are kept repressed until the regulators are switched off . The feedback repression of the previous factors ( pdm to Kr and cas to pdm ) ensures their downregulation , which promotes the progress of the sequential expression . These coincide with the observations by Kambadur et al . , who experimentally showed that the repressions from hb and cas define the temporal window of Pdm [24] . These repressive regulations and the activation from hb to Kr compose the minimum network for sequential expression ( Fig . 9A ) . Although they are enough to reproduce the sequential expression under appropriate conditions , the expression profiles could be easily perturbed by parameter variations or increase of noise ( Fig . 5 and 9A ) . In the two loops of the Drosophila network , activations from one gene to the next ( Kr to pdm and pdm to cas ) exist in addition to the repressive regulations . Other functional networks do not necessarily have these activations , but the activations can compensate for the loss of default promoter activities ( Fig . 8A and B ) . These regulations achieve precise expression by enhancing the correlations among the factors and heightening the stability against fluctuations ( Figs . 5B and 6B ) . From these results , we conclude that three types of regulations ( activation of the next factor , feedback repression , and repression of the second next factor ) compose a regulatory module for precise temporal expression , as summarized in Figure 9B . The feature of this network module embodies the robustness of the Drosophila network . Do the previous discussions have any implications on other developmental processes ? In the studies of spatial patterning in Drosophila segmentation , it was claimed that the frequent substructure feed forward loop ( FFL ) can set the positions of expression domains [13] , and mutual feedback repressions between the gap genes also have a pivotal role in the formation of expression domains with steep boundaries [12] , [47] . In case of the Drosophila network for sequential expression , preceding genes activate the next ones , while these genes repress the preceding ones . Similar regulatory interactions are reported in the yeast cell cycle by Lau et al . [48] . Thus , such asymmetric mutual regulations would be a general mechanism that serves as precise switches in the process of temporal patterning . We showed that the temporal specification network of Drosophila NBs contains not only the regulations necessary for generating sequential expression , but also additional regulations to achieve higher precision in the expression . In each hemisegment of Drosophila embryo , 30 different NBs are generated through spatial heterogeneity [29] . To guarantee sequential expression of common temporal transcription factors despite their differences in Drosophila NBs , the robustness of the system might be important . The robust nature of the Drosophila temporal network could be the consequence of evolutionary optimization in the reproducibility of the sequential expression under functional constraint . In future , we expect that experimental manipulation of corresponding enhancers will be able to clarify the relevance of each regulation to temporal patterning and stability .
Here we describe the details of the Boolean model ( Eq . ( 1 ) ) . The expressions of svp and x occur as inputs to the system . A pulse of svp expression always occurs at t = 1 . Expression of x switches either from ON to OFF state , or from OFF to ON state at ( ) . Once we assign the switching time of x expression ( ) , its value becomes fixed through the analysis of expression patterns for all the genotypes . Because the autonomous pulsed expression of svp results in hb downregulation , we set Jhb , svp = −5 , Jhb , j = 0 ( j = hb , Kr , pdm , cas , or x ) , and Jk , svp = 0 ( k = Kr , pdm , or cas ) throughout this study . The time step at which we finish the simulation ( ) was set as . We thus investigated the behaviors of the remaining three factors ( Kr , pdm , and cas ) under the given regulatory interactions {Jij} . The total number of combinations of the parameters is 3M23 ( the number of possible network architecture {Jij} multiplied by the number of default expression states ) , where M is the number of regulations . To simulate the dynamics for mutants , we always set the expression state of the corresponding gene to 0 ( OFF ) for loss-of-function or to 1 ( ON ) for overexpression . We then examined whether the temporal dynamics of the genetic networks are coincident with the expression profiles of each mutant ( Fig . 1D and Table 3 ) . In order to measure the similarity between the functional networks and the actual Drosophila network , we used two types of network ensembles as references . One is the ensemble of the possible network architectures . The other is a set of reconnected networks generated from the functional networks by iterative random reconnections of the matrix elements ( 1 , 000 iterations ) . The numbers of positive and negative regulations are preserved in the iterations . To count the number of different regulations between functional networks and the actual Drosophila network , we neglected the regulations from x and positive self-feedbacks because the existence of those is uncertain from the experimental data . We introduced the continuous model with stochasticity as shown in Equation ( 2 ) . The promoter activity of gene i ( i = hb , Kr , pdm , cas , or x ) is described as follows , Regulatory interactions are continuous equivalents of {Jij} in the Boolean model , and g ( x ) is a piece-wise linear function such that g ( x ) = x for x>0 and g ( x ) = 0 for x<0 . The parameters {Si} are the default activities of the promoters . Transcription of a gene is induced when the total regulatory inputs become positive ( ) , and is suppressed when they become negative ( ) . In order to consider the effect of fluctuations on the expression dynamics , we introduced additive white Gaussian noise : ( Eq ( 2 ) ) , where is the noise intensity of gene i . The expression of hb and x is induced only by the default promoter activities because all the regulations are absent for these two ( ) . To describe the expression change of hb and x , the promoter activities of these two are set as Shb >0 for ( Sx >0 for ) and Shb = 0 for ( Sx = 0 for ) , respectively . The promoter activities of the others are always assumed to exist ( SKr , Spdm , and Scas >0 ) . The noise intensities are also set as ( >0 ) for and for ( i = hb , x ) . Those of the other genes are ( >0 ) ( j = Kr , pdm , cas ) , Here we simply assume that the noise intensities of the genes take the same value . The noise intensity is set as in Figure 4 , and in Figure 5 . Noise intensity ( horizontal axis ) in Figure 6B means the value of . For the continuous model , we considered two different types of robustness: ( 1 ) the reproducibility of the sequential expression against parameter variations and ( 2 ) dynamical stability against temporal fluctuations . To analyze the former , the default promoter activities {Si} were assigned randomly within the defined ranges . The values of the matrix were set to 0 when the corresponding regulations were absent ( the corresponding element of the Boolean model takes Jij = 0 ) or assigned randomly when they are present ( Jij0 ) . In order to confine our attention to the properties of network architectures , the other parameters ( , , , and ) were fixed throughout the analysis . The ranges and the fixed values of the parameters are listed in Table 4 . Robustness against temporal fluctuations is measured as explained in the main text . In the simulations , we found that the existence of positive self-regulation enhanced the fraction of successes in many cases , but hardly affected the sequential expression . To focus on the contributions of mutual regulations of genes to robustness , we neglected the positive self-feedback regulations and confined the analysis to 120 out of 384 functional networks . | Cell fate specification is of key importance in the development of multicellular organisms . To specify various cell fates correctly , genetic networks precisely coordinate spatial and temporal gene expression patterns during various developmental stages . One central question in developmental biology is to elucidate the relationship between the pattern formation and the network architecture . During embryonic development of the Drosophila central nervous system , the neural stem cells express a group of genes in a definite order , which is responsible for the diversity of neural cells . To elucidate the underlying mechanism of the process , we analyzed the structure and dynamics of the genetic network for the temporal changes occurring in the Drosophila neural stem cells . Searching all the possible regulatory networks of these genes using a computer program , we detected the requisite regulations that reproduce observed gene expression profiles . By comparing the stability of the dynamics among the functional networks , we uncovered the robust nature of the actual Drosophila network against environmental and intrinsic fluctuations . These results indicate that the genetic network for sequential expression has evolved to be robust under functional constraints . Our study proposes regulatory modules that are responsible for the precise sequential expressions , which might exist in genetic networks for other temporal patterning processes . | [
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] | 2010 | Robustness under Functional Constraint: The Genetic Network for Temporal Expression in Drosophila Neurogenesis |
Human genetic diversity in the Pacific has not been adequately sampled , particularly in Melanesia . As a result , population relationships there have been open to debate . A genome scan of autosomal markers ( 687 microsatellites and 203 insertions/deletions ) on 952 individuals from 41 Pacific populations now provides the basis for understanding the remarkable nature of Melanesian variation , and for a more accurate comparison of these Pacific populations with previously studied groups from other regions . It also shows how textured human population variation can be in particular circumstances . Genetic diversity within individual Pacific populations is shown to be very low , while differentiation among Melanesian groups is high . Melanesian differentiation varies not only between islands , but also by island size and topographical complexity . The greatest distinctions are among the isolated groups in large island interiors , which are also the most internally homogeneous . The pattern loosely tracks language distinctions . Papuan-speaking groups are the most differentiated , and Austronesian or Oceanic-speaking groups , which tend to live along the coastlines , are more intermixed . A small “Austronesian” genetic signature ( always <20% ) was detected in less than half the Melanesian groups that speak Austronesian languages , and is entirely lacking in Papuan-speaking groups . Although the Polynesians are also distinctive , they tend to cluster with Micronesians , Taiwan Aborigines , and East Asians , and not Melanesians . These findings contribute to a resolution to the debates over Polynesian origins and their past interactions with Melanesians . With regard to genetics , the earlier studies had heavily relied on the evidence from single locus mitochondrial DNA or Y chromosome variation . Neither of these provided an unequivocal signal of phylogenetic relations or population intermixture proportions in the Pacific . Our analysis indicates the ancestors of Polynesians moved through Melanesia relatively rapidly and only intermixed to a very modest degree with the indigenous populations there .
The populations in New Guinea and the islands immediately to the east ( the Bismarck and Solomons archipelagos ) are well-known for their great diversity in cultures , languages , and genetics , which by a number of measures is unsurpassed for a region of this size [1] . This area is referred to as Near Oceania , as opposed to the islands farther out in the Pacific , known as Remote Oceania [2] ( see Figure 1 ) . For simplicity , we refer only to the peoples of Near Oceania as “Melanesians , ” although this term ordinarily encompasses additional groups to the east as far as Fiji , who are not covered in this study . Major parts of Near Oceania were settled from Southeast Asia early in modern human prehistory , between ∼50 , 000 and ∼30 , 000 years before present ( YBP ) [3–5] . Populations were relatively isolated at this edge of the human species range for the following 25 , 000 years . The early settlers in Near Oceania were very small groups of hunter-gatherers . For example , New Ireland , which is more than 300 km long , is estimated to have had a pre-Neolithic carrying capacity of ∼1 , 200 people or fewer [6] . There is evidence of sporadic , modest contact between New Guinea and the Bismarcks from 22 , 000 YBP , and with Bougainville/Buka in the Solomons only from ∼3 , 300 years ago [3 , 7] . By ∼3 , 300 YBP [3] , at least one powerful new impulse of influence had come from Austronesian speaking migrants from Island Southeast Asia , likely associated with the development of effective sailing [8] , that led to the appearance of the Lapita Cultural Complex in the Bismarck Archipelago . After only a few hundred years , “Lapita People” from this area had colonized the islands in Remote Oceania as far east as Tonga and Samoa , where Polynesian culture then developed [9] . The distribution and relations of Pacific language families reflect ancient settlement . Austronesian is a widespread and clearly defined linguistic family with more than 1 , 000 member languages , which has its greatest diversity , and likely origin , in Taiwan ∼4 , 000–5 , 000 years ago [10] . Some basic phylogenetic relations within Austronesian are sketched in Figure S1 . All Austronesian languages spoken outside Taiwan belong to the Malayo-Polynesian branch , and almost all the Malayo-Polynesian languages of Oceania belong to the Oceanic branch . It is Proto Oceanic , the immediate ancestor of the Oceanic languages , that is associated with an early phase of the Lapita Cultural Complex . Proto Oceanic split into a number of branches as its descendants spread across Remote Oceania , including Proto Nuclear Micronesian and Proto Polynesian ( a branch of Central Oceanic ) . Almost all the other indigenous languages of Oceania are referred to as non-Austronesian , or Papuan . Most Papuan languages are found in New Guinea , with the remainder in nearby islands . This is a residual category of ∼800 languages . Most of these can be assigned to more than 20 different language families , but these families cannot be shown to be related on present evidence . There remain a number of “Papuan” isolates that cannot be grouped at all [11] . Trans New Guinea is the largest Papuan language family . It consists of ∼400 languages and dates to 6 , 000 to 10 , 000 YBP [12] . Other Papuan families including the ones in the Bismarck and Solomon archipelagos probably also go back at least to this period [13–15] . While it is reasonable to assume these different Papuan families had common origins further back in time , any evidence of such ties that is recoverable with standard methods of historical linguistics has been erased over the millennia . The concentration and number of these apparently unrelated language families and isolates is unsurpassed in any other region of the world [15] . Analyses of genetic variation at some informative loci , particularly the mitochondrial DNA ( mtDNA ) ( reviewed in [16 , 17–19] ) , non-recombining Y-chromosome markers ( NRY ) ( reviewed in [19 , 20] ) , and a small set of autosomal microsatellites [21] have provided divergent impressions of the population genetic structure of both Near and Remote Oceania . Because they have ¼ the effective sample size of autosomal markers , the mtDNA and NRY haplotypes have been particularly subject to the effects of random genetic drift , and each autosomal marker , no matter how informative , still represents a minute fraction of the total genetic variation among populations . Even so , these data have shown that the genetic variation in Near Oceanic populations is considerably greater than in Remote Oceanic ones , and that there are a cluster of haplogroups that developed in particular islands of Near Oceania between approximately 50 , 000 and 30 , 000 years ago . However , a number of unresolved issues remain concerning the proper interpretation of these and other data that a comprehensive genomic sampling of neutral biparental markers across Pacific populations should clarify . A list of these includes: 1 ) to whom are these diverse Melanesian populations most closely related outside this region ( East or South Asians , or perhaps even Africans , whom they physically resemble ) ? 2 ) how does the genetic diversity and differentiation of Near Oceanic populations compare with those in other regions ? 3 ) is there a clear organization of the variation among groups in Near Oceania ( i . e . , either by language , by island , or distance from major dispersal centers ) ? 4 ) is there a genetic signature of Aboriginal Taiwanese/Southeast Asian or Polynesian influence in Melanesian populations , especially in the Bismarcks , where the Lapita Cultural Complex developed ? and 5 ) are Polynesians more closely related to Asian/Aboriginal Taiwanese populations or to Melanesians ? Here we report the analysis of 687 microsatellite and 203 insertion/deletion ( indel ) polymorphisms in 952 individuals from 41 Pacific populations , primarily in the Bismarck Archipelago and Bougainville Island , and also including select sample sets from New Guinea , Aboriginal Taiwan , Micronesia , and Polynesia . The results show the reduced internal variation of Near Oceanic Melanesian populations and the remarkable divergence among them , and how this divergence is influenced by island size and topography , and is also correlated with language affiliation . We also detected a very small but clear genetic signature of “Asian/Polynesian” intermixture in certain Austronesian ( Oceanic ) -speaking populations in the region ( by “genetic signature , ” we mean an ancestral proportion in some groups inferred by the STRUCTURE analysis that predominates in another ancestral grouping ) . For global context , these data were compared with data from the Centre d'Etude du Polymorphisme Humain human genome diversity panel ( HGDP-CEPH ) , composed of cell lines [22–24] , especially its subset from East Asia . Figure 1A shows how undersampled the Pacific populations had been in the HGDP-CEPH dataset ( as well as its emphasis on particular regions of Asia ) , and Figure 1B shows the distribution of our Pacific population samples , with its intensive coverage in Near Oceania .
Figure 2 shows the estimated values of θ ( θ̂ ) calculated from expected heterozygosity ( He ) arranged from highest to lowest values , combining our Pacific populations and the HGDP-CEPH global set ( the values of θ̂ , He , and the average number of alleles per locus are given in Table S1 ) . From Ohta and Kimura [25] , under a stepwise model , the expected relationship between θ and heterozygosity ( H ) is which rearranges to For autosomal loci , θ is defined as θ = 4Neμ , where Ne is defined as the effective population size and μ is the per generation mutation rate . Assuming the mutation rate is constant across populations and that the stepwise mutation model is appropriate , θ̂ provides an estimate that is linearly correlated with effective population size . In contrast , H asymptotically approaches a value of 1 as the effective population size increases . Therefore , the use of θ̂ is more appropriate to represent differences in effective population sizes among populations ( e . g . , a θ ratio of 2 between two populations indicates twice the effective population size between the populations , while an H ratio of 2 does not ) . The pattern of variation in Figure 2 is consistent with a series of successive founder effects that modern humans underwent in their expansions out of Africa ( also shown by [26] ) . African populations have the highest values , followed in order by Europe/Central Asians , East Asians , Melanesians , and Native Americans . All the Pacific populations ranked together in a narrow band towards the low end of θ̂ values ( between 4 . 8 and 2 . 9 ) . Within the Melanesian set , inland populations generally had lower values of θ̂ than shore-dwelling groups , as shown . The three non-Pacific groups in the range between 4 . 8 and 2 . 9 were the Maya , Columbia , and Lahu . The Maya are known to have some European ancestry , which would explain their relatively high θ̂ for a Native American group; and the Lahu are an Asian population that was subject to particularly strong random genetic drift [24] . Columbia and other conglomerate groups made up of individuals from different populations ( e . g . , Bantu South , Sepik , Highlands , Micronesia , and Samoa ) consistently had higher values of θ̂ than related groups . This combining of groups has caused inflated levels of diversity and effective population size estimates ( i . e . , there is more variation in a combined sample set than is typically contained in one from a clearly defined population ) . Ramachandran et al . [26] investigated the correlation between geographic distance and genetic differentiation as measured by pairwise FST in the global HGDP-CEPH dataset , and found a linear relationship existed , with major deviations from the fitted line they believed consistent with admixture or extreme isolation . We analyzed this correlation by major region , adding our expanded Pacific dataset . The results , shown in Figure 3 , show the extremely heterogeneous nature of the linear correlations and distributions from region to region . The sampled Melanesian populations were distributed across a comparatively small geographic area , but their range of pairwise FST values was extremely large . Only the Native American groups had an equivalent range of FST values , but these were unreliable since there were only five American populations distributed across very large distances . To quantify the degree of variation within and among populations , an analysis of molecular variance ( AMOVA ) for the Pacific materials plus the HGDP-CEPH dataset was performed , with the results shown in Table 1 . The global AMOVA results first presented in [24] for the HGDP-CEPH dataset were based on 377 microsatellites , included some first degree relatives , and included only two “Oceanic” populations ( from the Nasioi of Bougainville and highland New Guinea ) . In the current analysis based on 687 microsatellites , the Americas had the highest among-population variation component , followed in order by Melanesia , Africa , Asia , and Europe . This pattern follows directly from their ranking in population heterozygosities or θ̂ [27] . As shown in Table 2 , the microsatellite variation in Melanesia ( New Guinea , New Britain , New Ireland , and Bougainville ) was apportioned first by language group and then by island . While population variation among the different islands was considerable ( refer to the 95% confidence interval ) , within-island variation among populations was more than three times greater . This was primarily due to the extensive variation within New Britain ( with a 5% internal variance component ) , followed by Bougainville ( 3 . 7% ) , and New Ireland ( 2% , see Table S2 ) . The variation among the three New Guinea samples in our series was lower , most likely because of their less rigorous population definitions ( see the Methods section for sampling details ) . Apportioning the molecular variance by language group ( between Oceanic speaking and Papuan speaking populations ) only accounted for 0 . 2 % of the total , which , as indicated by the very small 95% confidence interval , was still significant . Since the two language categories are scattered across the islands , geography and intermixture will confound possible language effects . While the microsatellite variation among the Oceanic-speaking populations was significant , it was much greater among the Papuan-speaking populations ( many of which are located in the mountainous interiors of the larger islands ) . To investigate individual and population similarities , we applied a Bayesian model-based clustering algorithm implemented in the STRUCTURE program [28] to our Pacific dataset combined with the HGDP-CEPH panel ( also genotyped by the Marshfield Clinic ) . This program identifies groups of individuals who have similar allele frequency profiles . The great advantage of this clustering approach is that it avoids a priori population classifications , and instead estimates the shared population ancestry of individuals based solely on their genotypes under an assumption of Hardy-Weinberg equilibrium and linkage equilibrium in ancestral populations . It infers individual proportions of ancestry from K clusters , where K is specified in advance and corresponds to the number of posited ancestral populations; K can be varied across independent runs . Individuals can be assigned admixture estimates from multiple ancestral populations , with the admixture estimates summing to 1 across these population clusters . Figure 4 presents the STRUCTURE analysis of our Pacific dataset plus the HGDP-CEPH Panel for 687 microsatellites and 203 indels on the 22 autosomes , on a total of 1 , 893 individuals from 91 populations . Each increase in K split a cluster that had been defined in an earlier run , and individuals from the same populations had very similar membership coefficients in the inferred clusters . Details of the STRUCTURE results are provided in the Table S3 . Inclusion of our large Pacific dataset altered the sequence of splitting , but did not change , the five major global clusters that had previously identified with a smaller set of microsatellites: Sub-Saharan Africa , Western Eurasia , East Asia , “Oceania , ” and the Americas [24] . The Taiwan Aborigines clustered with East Asia , while Polynesians and Micronesians had a mixed position between East Asians and Melanesians ( “Oceania” ) . The Mãori had the suggestion of a minor proportion of European admixture , which had been indicated by the donors themselves . There was a small but consistent “Asian/Polynesian” admixture estimate in specific Melanesian groups . Because clustering after K = 6 mostly involved Near Oceanic populations , we stopped the combined global analysis there , and analyzed the Pacific subset separately thereafter . An unrooted neighbor-joining tree for the same HGDP-CEPH and Pacific samples , excluding the indels , was calculated from a matrix of pairwise FST “coancestry” distances ( similar to Reynolds' D [29] , see Table S4 ) , and is shown in Figure 5 . For comparison , the cluster colors for the K = 6 STRUCTURE run were superimposed on the tree . The results were compatible with the clusters identified with STRUCTURE . Branch lengths varied inversely with values of θ̂ or expected heterozygosity , so that populations with the longest branch lengths had the lowest values of θ̂ . The longest branches belonged to the Native American and separate Melanesian groups . As with the STRUCTURE results , this unrooted FST based tree had Melanesians , East Asians , and Native Americans at the opposite end of the human tree from Africans and Europeans . Trees based on other population pairwise genetic distance matrices ( Nei's chord distance [30] , ( δμ ) 2 [31] , the proportion of shared alleles [32] , and Cavalli-Sforza and Edwards' chord distance [33] ) also indicated relatively large distances between Africans and Melanesians , and also consistently placed the Taiwan Aborigines between the East Asians and Polynesians/Micronesians ( Figure S2 ) . We performed STRUCTURE analyses on a combined East Asia–Pacific dataset to explore in detail the relationships among Melanesians , Polynesians , Taiwan Aborigines , and East Asians , and to clarify the role of intermixture there . The samples included in this analysis were our Pacific set of 40 groups , and from the HGDP-CEPH panel , the “Papuans , ” ( identified here as “Highlands” ) , the East Asians , and French ( the French were included to identify European admixture ) . The STRUCTURE results are shown in Figure 6 , and the details on their reproducibility in Table S5 . At K = 2 and K = 3 , the Asia-Pacific clusterings mirrored the first five runs of the global comparison . Bougainville formed a cluster contrasting with central New Britain at K = 3; the New Guinea groups separate at K = 4; and a central New Britain cluster splits at K = 5 . Then , at K = 6 , a Polynesian cluster appeared , centered on the Mãori , with high ancestral proportions for the Samoan and Micronesian samples as well as the Taiwanese Aborigines . The former “East Asian” ancestral proportion in Melanesian populations converted almost entirely to “Polynesian” in this run . At K = 7 , 8 , and 9 , more Melanesian clusters formed in New Britain and New Ireland . All but one of the Melanesian cluster foci are Papuan-speaking groups , primarily located in the interiors of the large islands ( see Figures 7 and 8 ) . The Mamusi , who are Oceanic-speaking neighbors of the Ata , are the exception . There is reason to suspect the Mamusi were originally a Papuan-speaking group ( perhaps Ata speakers ) who adopted an Oceanic language [34] . At K = 10 , the “Europeans” were finally identified as a separate cluster . As shown in Table S5 , runs at K = 11 and above became unstable and not reproducible . The approximate percentage of “European” admixture is best seen in Figure 7 , which gives average ancestral proportions by population . In the Mãori , the “European” ancestry was ∼12% , and for Samoans it was ∼5% . The Samoan and Micronesian results also suggested minor ties with East Asians and also Melanesians , specifically the “New Ireland” cluster ( a number of Lapita sites have been found in the vicinity of New Ireland [3] ) . The Micronesians had low levels of inferred ancestry shared with populations in New Guinea , which is not far from Belau , where most of the Micronesian samples are from . This relationship is echoed in mtDNA results as well [35] . The typical ancestral proportions by population for a majority rule run are given in Table S6 . As seen in Table S5 , 15 out of 20 STRUCTURE runs on our Pacific dataset at K = 10 produced essentially the same group ancestry proportions as shown in Figures 6 and 7 , with individual similarity coefficients ranging from 0 . 90 to 0 . 96 , so these results are quite reproducible . As in the global comparison , an “East Asian/Polynesian” estimated ancestry proportion for a number of Melanesian populations only occurred at frequencies of >5% in certain Oceanic-speaking ( Austronesian ) groups , and it is hereafter referred to as the “Austronesian” genetic signature . In Figure 7 , the purple arrows point to those Oceanic-speaking groups in our Melanesian sample set that have this clear “Austronesian” signature . The probabilities were highest in the Kove and Saposa ( just below 20% ) , followed by the Mussau at 15% , with the Teop , Mangseng , Nakanai ( Bileki ) , Melamela , and Tigak having lower “Austronesian” signatures . In these Oceanic-speaking populations , the “Austronesian” ancestral assignment proportions never ranked higher than third , indicating their comparatively intermixed , and predominantly Papuan , genetic nature . As a check on these results , particularly to verify the relationships of the Polynesians and Micronesians within our dataset , we performed a separate “supervised” STRUCTURE analysis [28 , 36] , where the individual Mãori , Samoan , and Micronesian genotypes were distributed across eight representative populations ( Taiwan Aborigines , East Asians , Europeans , and the Near Oceanic New Guinea , Ata , Baining , Kuot , and Aita ) . The results , shown in Figure S3A , underline the primary affinity of the Mãori , Samoans , and Micronesians to Taiwan Aborigines and secondarily to East Asians , with lesser suggestions of links to Europeans and New Ireland/New Britain ( there is no suggestion of any Bougainville or Baining tie ) . In a second “supervised” STRUCTURE analysis where a ninth population was specified but not associated with a particular group a priori , the Polynesians/Micronesians constituted the largest proportion of this cluster ( Figure S3B ) . Of the three populations in question , the Mãori had the smallest signal of external relationship , consistent with their extensive genetic drift , and the Micronesian group has the largest signal ( to Taiwan , East Asia , New Guinea , and New Ireland/New Britain ) . Figure 8 shows the distribution within Northern Island Melanesian populations of the STRUCTURE clustering probabilities for K = 10 in pie-chart form ( some populations from the same language groups with very similar probability profiles were merged ) . Neighboring groups tended to share similar profiles . New Britain , the largest and most rugged island , had the greatest internal differentiation , with five different assigned clusters at >50% probabilities in different populations . Bougainville groups had two common cluster assignments , while there was only one common cluster in New Ireland . Figure 9 shows the unrooted neighbor-joining tree for the East Asia–Pacific populations from a pairwise FST coancestry distance matrix for 687 microsatellites ( the pairwise FST values are in Table S7 ) . Bootstrap values for the branches , generated with the PHYLIP program from population allele frequencies for 100 different trees , are indicated by branch thicknesses . As shown , most of the trunk elements had high bootstrap values , as did a number of branches within Northern Island Melanesian groups . By contrast , the mainland East Asian group relationships were considerably more ambiguous , their branches were shorter , and only the Taiwan Aborigines had a strong internal branch . The tree branching again closely reflected the clustering in STRUCTURE , indicated by the corresponding colors from K = 10 . The populations with the longest branches were those with the largest ancestral proportions assigned to single STRUCTURE clusters , and had the lowest heterozygosities . These populations tend to be Papuan-speaking groups in island interiors . The STRUCTURE analysis specifies the role and nature of admixture in a way that a population-based tree cannot . The AMOVA , STRUCTURE , and population tree analyses were all driven by large distinctions in allele frequencies , rather than by the presence of private alleles in one population or another , since these generally occur in very low frequencies . In the first publication on the global HGDP-CEPH set of 377 microsatellites , Rosenberg et al . quantified continental relationships independent of the STRUCTURE analysis by showing the number of alleles that were only present in one continent , shared by two , by three , etc . [24] . The pattern of specific allele sharing was taken to indicate greater African heterogeneity , and that allele sharing was least for the Americas and for the two “Oceanic” groups . With our enlarged dataset and microsatellite coverage , we also compared patterns of private alleles and allele sharing between regions ( Table 3 ) . We recovered 271 Melanesian-specific alleles , which in raw numbers actually exceeded those for Africa . Correcting for sample sizes , the rate of Melanesian-specific alleles was at the high end of the range for the major regions except for Africa . The number of alleles missing from only one continent , also given in Table 3 , shows the dramatic effect of genetic drift on the American populations . The number of shared alleles between pairs of regions is shown in Table 4 , with the correction for sample sizes in Table 5 . All non-African regions including Melanesia shared the most alleles with Africa , indicating they were primarily subsets of African diversity . Melanesia shared more alleles with East Asia than with any other non-African region , but they cannot simply be viewed as an extension or subset of East Asian diversity . When Papuan and Oceanic speaking groups in Melanesia were analyzed separately , the Papuan-speaking groups showed greater isolation , as they shared fewer alleles with all other regions than did Oceanic speaking groups ( unpublished data ) .
Our study suggests that in the Pacific , and specifically in Near Oceania , there is only a modest association between language and genetic affiliation . Oceanic languages were introduced and dispersed around the islands within the last 3 , 300 years , but there was apparently only a small infusion of accompanying “Austronesian” ancestry that has survived . Approximately one-half of the Oceanic-speaking groups in Melanesia had an identifiable “Austronesian” genetic signature ( see Figure 7 and Table S8 ) . In each case where there was such an “Austronesian” signature , at least two other cluster assignments had probabilities higher than the “Austronesian” one ( see , in Figure 6 , the Saposa and Teop of Bougainville; the Mussau and Tigak in New Ireland Province; and the Kove , Mangseng , Melamela , and Nakanai Bileki of New Britain ) . On the other hand , the Oceanic-speaking groups without the “Austronesian” signature were often genetically indistinguishable from their immediate Papuan-speaking neighbors ( in New Britain , the Mamusi have no Austronesian signature , but they and the Nakanai Loso cluster closely with their Papuan-speaking Ata neighbors; the Nalik , Notsi , and Madak of New Ireland are genetically indistinguishable from their Papuan-speaking Kuot neighbors; the Tolai and Lavongai profiles suggest significant intermixture , but only between different Papuan-speaking groups ) . The result suggests that Oceanic languages were adopted by many formerly Papuan-speaking groups , while at the same time there was little genetic influence or marital exchange . At least in Near Oceania , rates of language borrowing and language adoption have been faster and more pervasive than rates of genetic admixture . However it is measured , genetic variation is reduced within Melanesian populations ( Figure 2 ) , while the genetic divergences among them are very large ( refer to Figures 6 , 8 , and 9 and to Tables 1–5 ) . The size of the differences among the populations would appear to equal or surpass those among populations across East Asia , Europe , or even Africa . However , the large Melanesian population distinctions are a direct consequence of their very low levels of internal variation or heterozygosity . These low levels will directly inflate both the proportion of among group variation in AMOVA and also pairwise FST genetic distances ( for a full discussion of this point , see especially [27] and also [ 26 , 37] ) . As population heterozygosities decrease , pairwise FSTs should increase because of this intrinsic mathematical relationship . This is illustrated by our global and Near Oceania datasets ( Figure 10A and 10B ) . Those pairwise FSTs involving the Bantu South population ( which has a heterozygosity approaching 1 . 0 ) are plotted against the heterozygosities of each population , and the resulting correlations approach 1 . 0 . Our Structure and tree analyses of the combined microsatellite datasets indicate that Melanesians are quite far removed from Africans , in spite of their superficial similarities in hair form and skin pigmentation [38] . In the initial analysis of the HGDP-CEPH dataset , the placement of the two Melanesian ( “Oceanic” ) groups was different . There , they split from Eurasia before Asians and Native Americans [39] . This also differed from the result of a genome-wide SNP study [40] on a very small world-wide dataset . The extreme positioning of Melanesians in our tree was not due to our over sampling . Rather , our extensive coverage of Melanesian variation has enabled a clearer resolution of their relationships with populations outside the region . The pattern of Near Oceanic diversity has been made clear . The AMOVA analysis of the microsatellites showed that the larger and more rugged the island , the greater the differentiation among populations . The most divergent populations were in large island interiors while these same populations were internally the most homogeneous ( as measured by reduced values of θ̂ and expected heterozygosity—Table S1 ) . Genetic variation from one large Near Oceanic island to the next was also significant . While our coverage of microsatellite variation elsewhere in the Pacific was admittedly spotty , our data as well as other smaller scale microsatellite analyses [21 , 41] suggest that , excluding the large islands of Near Oceania , there is a gradual decline in variation as one moves from Asia eastward , and variation among populations in the Pacific otherwise is not nearly as great as that in the large islands of Near Oceania . As noted , New Guinea does not appear to have as much microsatellite/indel diversity among groups as New Britain . Our sample coverage and definition was less rigorous there , and we expect equivalent coverage in New Guinea would equal or surpass the divergence of our New Britain series . The biogeographic pattern of population divergences in Near Oceania is most likely attributable to the restricted marital migration distances that have been documented most clearly for inland Bougainville groups [42] , as well as for some New Guinea highlands populations [43] . Few people in small inland communities traditionally married and established households more than 1–2 kilometers from their birthplaces , while marital migration distances tended to be longer among shoreline communities . Nettle has argued that in ecologically rich tropical regions such as Near Oceania , small populations easily became self-sufficient , which in turn encouraged isolation and discouraged exchange [44 , 45] , causing the development of extreme diversity among populations in both language and genetics . We suggest this was the underlying cause of the short marital migration distances among inland groups in Near Oceania , which in turn was responsible for the low population heterozygosities and resulting large genetic distinctions among groups [42] . Because they arrived first and came to occupy large island interiors , the Papuan-speaking groups are considerably more diverse than Oceanic-speaking groups , which tend , in large islands , to be arranged along the shorelines . The prehistoric record suggests there was a gradual reduction after initial settlement in the size of foraging zones of formerly mobile groups , associated with the filling up of the landscape [3 , p . 16] . In many ways , these patterns and dynamics parallel the biogeography of birds and ants in the same region , where dispersal abilities of different species have dictated their patterns of diversity , and dispersal tendencies have , in many cases , contracted in island interiors over time [46 , 47] . Some known population relationships suggested the considerable age of the clusters identified by our STRUCTURE analysis . The Tolai of East New Britain , with an assignment profile similar to New Ireland groups , are known to have migrated from southern New Ireland over 1 , 200 years ago [42] . A major volcanic eruption in western New Britain 3 , 000 years ago isolated that section of the island , and the Anêm , along with the recently arrived and intermixed Kove , form a separate cluster . Although the two Baining groups of east New Britain formed a cluster of their own , it has been suggested from the mtDNA , Y , and X chromosome analyses that they have been separated by thousands of years [48] ( see their long branch lengths in Figure 9 ) . Also , the clustering of the Polynesians , Taiwan Aboriginals , and East Asians reflects ties older than 3 , 300 years . In the Pacific , the change in genetic clustering apparently has evolved over thousands of years , and in many cases tens of thousands . This is likely a function of small effective population sizes and the high degree of isolation/drift over these immense time periods . There were indications from the mtDNA , NRY , and certain autosomal microsatellites that in Remote Oceania , where islands are generally smaller in size , genetic variation among human groups is comparatively reduced , which is a contrast to Near Oceania [17 , 19–21 , 49] . At some point , prehistoric Oceanic mariners apparently became so accomplished that the inter-island water crossings in the central Pacific were often no more of an impediment to travel than the ( already occupied ) rugged terrain of the larger island interiors in the western Pacific . In many areas , the ocean was transformed from a formidable barrier into a highway [50 , 51] . However , exactly where the ( relatively homogeneous ) Polynesians came from has remained controversial , and the number of proposed explanatory models for their origin form a continuum [49 , 52] . At one extreme is the “Entangled Bank” [53] , which is essentially a null hypothesis for detecting clear signals of specific Polynesian ancestry anywhere to the west . It suggests that , although there certainly must have been a series of introductions and influences from Asia into the Pacific over the millennia , no decipherable signal has survived that can be identified as specifically ancestral to Polynesians , because of the complexities of human interactions from the outset [54] . Proponents argue that tree-like representations of population ( or linguistic ) relationships cannot be expected to develop regularly and are likely to be entirely inappropriate representations of population relationships in many , if not all , instances , since they so often ignore interactions between neighboring groups . Models at the other end of the continuum assume contemporary genetic ( as well as cultural ) similarities can carry a clear signal of past population relationships . Primary among these is “The Express Train to Polynesia” model [55] . It proposes a rapid movement of the ancestors of the Polynesians from the vicinity of Taiwan to the Central Pacific , without extensive contact with indigenous Near Oceanic populations along the way . With regard to human genetics , the published mtDNA evidence has generally been interpreted as supporting the “Express Train . ” This is because a younger mtDNA haplotype ( B4a1a1 ) is assumed to have been closely linked to the development and expansion of Polynesian populations . At present , the state of the evidence for this association is as follows: a ) the precursor haplotype to B4a1a1 has been identified in Taiwan aboriginal populations [56]; b ) the final development of B4a1a1 with the key mutation at nucleotide site 14022 seems to have occurred in eastern Indonesia or Near Oceania [17]; c ) its frequency varies widely over Near and Remote Oceania before becoming ubiquitous in Central and Eastern Polynesian populations; d ) in Near Oceania , it is common along many Oceanic-speaking coastal groups , as well as a number of Papuan-speaking groups , especially in New Ireland and Bougainville [17]; and e ) its expansion dates are relatively recent , although old enough to suggest to some observers that it cannot be easily tied to the Polynesian expansion [17 , 56] . The “Slow Boat to Polynesia” model which is supported by NRY variant distributions , also assumes current genetic patterns in Oceania directly reflect prehistoric migrations and interactions . These NRY haplogroup distributions have been taken to suggest a very minor “Asian” contribution to current Polynesian populations , suggesting instead that Polynesians derived primarily from Melanesian ( Near Oceanic ) populations [19 , 57 , 58] . “Melanesian” NRY haplogroups were found to be very common in some Polynesian populations , while “Asian” NRY haplogroups were scarce in Melanesian populations [20 , 58] , and low in their frequencies in the Central Pacific . However , recent studies have shown that the “Asian” NRY haplogroups are not as rare in Polynesia as initially thought , and are quite variable in frequency ( [19] , Table S2 ) . Because of their comprehensive nature , we believe the results of our autosomal microsatellite survey present a resolution to this issue with regard to human genetic relationships . The fact that the STRUCTURE cluster containing Micronesians , Samoans , and Maoris has a detectable signature only in Oceanic-speaking Melanesians and Taiwan Aborigines supports the position that an expansion of peoples from the general vicinity of Taiwan is primarily responsible for the ancestry of Remote Oceania , and that these people left a small but still identifiable signature in ( some Oceanic-speaking ) populations of Near Oceania . Scenarios for different male and female dispersals have been proposed to reconcile the divergent mtDNA and NRY patterns in Oceania [35 , 59] , but the autosomal microsatellite results should now serve as the primary reference . Although the Polynesians in our analysis were similar to Taiwan Aborigines and East Asians , they might be even closer to other populations not covered in our study , from Indonesia , the Philippines , or Southeast Asia . While there is a substantial body of evidence that indicates Taiwan is the primary point of Austronesian dispersal [60 , 61] , there are now also suggestions of the importance of ( Island ) Southeast Asia as well [62 , 63] . The ties of particular Near Oceanic populations to those regions also remain poorly understood , but should be resolved with additional sampling from these regions and similar analyses . To revisit the questions posed at the beginning , we can provide answers as follows . 1 ) To whom are these Melanesian populations most closely related outside the Pacific ? Outside the Pacific , East Asian populations are apparently the closest ( but still very distant ) relatives of Melanesians . Africans and Europeans are the most distant . 2 ) How does the genetic diversity of Near Oceanic populations compare with groups in other regions ? The within-group diversity in Melanesian populations is consistently very low , which acts to exaggerate the considerable among-group distinctions there . This great diversity in such a small region makes comparisons of human population structure from continent to continent problematic . 3 ) Is there a clear organization of the variation among Melanesian groups ? The diversity among groups is primarily organized by island size and topographic complexity , with the inland Papuan-speaking groups the most isolated and differentiated . Shore-dwelling Oceanic-speaking groups are more intermixed ( dispersal along the shorelines was easier ) . 4 ) Is there an identifiable genetic signature of Taiwanese/Southeast Asian or Polynesian influence in Near Oceanic populations , especially in the Bismarcks , where the Lapita Cultural Complex developed ? There is a weak “Austronesian” genetic signature in only a portion of Oceanic-speaking populations in Melanesia , and none at all in Papuan-speaking groups ( contradicting the results of mtDNA , but in accord with the NRY results ) . 5 ) Are Polynesians more closely related to Asian/Taiwanese populations or to Melanesians ? Polynesians are closely related to Asian/Taiwanese Aboriginal populations , while they are very weakly associated with any Melanesian groups ( the closest association there appears to be with New Ireland populations ) . This is in accord with mtDNA interpretations , but differs from the usual interpretation of the NRY results . The sailing capabilities of the ancestors of the Polynesians transformed the nature of their Diaspora and kept them relatively homogeneous .
Our Asia–Pacific sample set came from a variety of sources . The objective was to include between 15 and 25 unrelated individuals ( minimally excluding reported first-degree relatives ) from locales where individuals and their parents had all lived . These criteria were achieved in most instances . All of the samples except the cell lines were Whole Genome Amplified ( Qiagen RepliG ) . Details are given below . 1 . Samples from Northern Island Melanesia were collected in three field seasons ( 1998 , 2000 , and 2003 ) in collaboration with the Institute for Medical Research of Papua New Guinea . Besides a 10 ml blood sample , a simple genealogy and residency questionnaire was taken , including in most instances parent and grandparent names , residences , and native languages . All individuals gave their informed consent for participation , and the study was approved by the Institutional Review Boards of Papua New Guinea , Temple , Michigan , Yale , and Binghamton Universities . Among over 1 , 500 samples collected , 995 were chosen for submission to the Marshfield Clinic for microsatellite and indel analysis . As many Papuan-speaking groups as possible were included , along with neighboring Oceanic-speaking groups , focusing on New Britain , New Ireland , New Hanover , Mussau , and Bougainville . We included multiple locales in larger language groups where feasible; and picked samples from individuals whose family's residence histories suggested close identification with the sampling locale . People of mixed parentage ( especially with one grandparent from a different language group or island ) could not always be excluded if the minimum required sample size was to be achieved . A number of individuals who were born on the New Guinea mainland but had settled in Northern Island Melanesia were taken to constitute one additional sample—the “Sepik” —so that this sample is a conglomerate . DNA was extracted as previously described [17] . 2 . DNA was obtained from the Kidd lab collection of cell lines for: a ) the Eastern Highlands of Papua New Guinea , primarily from the Gimi , which were collected in collaboration with the Papua New Guinea Institute of Medical Research , and also from Goroka Town; b ) Micronesians , primarily from Belau , who drew each other's blood samples during their training in the Pacific Basin Medical Officer Training Program; and c ) Samoans , who were in a combined collection from the Pacific Basin Medical Officer Training Program and from American Samoa . All individuals gave their informed consent for participation . 3 . New Zealand DNA samples were collected from indigenous Mãori individuals residing in the North Island . Individuals were unrelated by first degree , had two Mãori parents by self-report , and belonged to one segment of the wider Mãori population . Ethical clearance was granted by the NZ National Ethics Committee . DNA was extracted from blood using Qiagen kits . 4 . Taiwan Aboriginal samples comprise the Northeastern Taroko tribe from Hsiulin , part of the Atayal language group , and the Amis tribe living on the east coast of Taiwan and speaking Amis . All individuals were unrelated and had both parents belonging to the same tribe . Each individual gave informed consent to participation in population genetics studies and the project was approved by the Ethics Committee of the Hospital and the Department of Health of Taiwan . Blood samples were collected in acid citrate dextrose tubes . Genomic DNA was extracted from 500 μl of buffy coat using the QIAmp DNA kit ( QIAml blood kit , Qiagen ) by Loo Jun-Hun at the Transfusion Medicine and Molecular Anthropology Laboratory , Mackay Memorial Hospital , Taipei . Each individual was originally genotyped for 751 microsatellite and 481 insertion/deletion autosomal polymorphisms . The microsatellites were drawn from Marshfield Screening Sets #16 and #54 , and the indel markers were drawn from Marshfield Screening Set #101 . 890 markers typed in our Pacific series ( 203 indels and 687 microsatellites ) had been typed in the HGDP-CEPH Human Genome Diversity Cell Line as described in [23] , although for some microsatellites , a change in primer length or position occurred between the HGDP-CEPH genotyping ( 2004 ) and our own ( 2006 ) , or a change in allele calling occurred . Where the primer changed , allele sizes from one of the two data sets were adjusted ( Table S9 ) . The changes were done by comparing the same set of individuals ( called “Nasioi” in our dataset , and “Melanesians from Bougainville” in the HGDP-CEPH dataset ) duplicated in both studies . Two loci for which the allele size shift was ambiguous—GATA11C08 and GGAA10C09—were excluded . Of the 687 microsatellites remaining for the combined analysis with the HGDP-CEPH panel , 166 had primer changes between the datasets . All analyses utilized the 687 microsatellites , and in addition the 203 indels were used in the STRUCTURE analyses . The set of 957 individuals used here from the HGDP-CEPH panel is the “H971” subset of the original panel [64] , without first-degree relatives , and with the Melanesian ( Nasioi ) removed , since these individuals were also present in our samples ( one individual , number 857 , was inadvertently deleted early in this analysis ) . Small African populations with single or two individuals were grouped into Bantu South ( Herero , Ovambo , Pedi , Sotho , Tswana , and Zulu ) The expected heterozygosity and average number of alleles per locus were computed on the microsatellites with the GDA software [65] , using the sample-size corrected estimator , as in [66] . FST was estimated on the microsatellites as in Equation 5 . 3 from [67] , using GDA , with 95% confidence intervals based on 1 , 000 bootstraps across loci . Indels were excluded from all analyses except STRUCTURE . Cluster analysis of genotypes utilized the Structure versions 2 . 1 and 2 . 2 software package [28 , 36] . Results using Structure 2 . 1 and 2 . 2 were essentially identical . STRUCTURE was run with a Markov Chain Monte Carlo ( MCMC ) burnin of 20 , 000 steps , followed by an MCMC chain of 10 , 000 steps for clustering inference . Ten runs were performed at each K in most cases , except as noted in Table S3 ( for K = 7 ) and Table S5 ( for K = 10 ) . When multiple runs at the same values of K produced discrepant results , we relied on majority rule ( i . e . , modal topography in cluster assignment ) to pick the optimal result . For the combined global analysis , we terminated the STRUCTURE runs at K = 6 , as explained in the Results , and for the Pacific set we terminated the analysis when it became unstable at higher values of K ( i . e . , when multiple solutions appeared ) . Details are provided in the Tables S3 and S5 . Individual similarity coefficients for pairs of runs were calculated as in [24] and Methods . The neighbor-joining trees for Figures 5 and 9 were based on the FST distance matrices obtained with GDA . The bootstrap values for the Asia–Pacific dataset ( Figure 9 ) were obtained based on allele frequencies using PHYLIP [68] . The neighbor-joining trees in Figure S3 were calculated using MSA [69] and drawn with Phylip . Great circle geographic distances were calculated with the Haversine method as described in [26] . The results of the STRUCTURE runs were graphed with the software DISTRUCT [70] . | The origins and current genetic relationships of Pacific Islanders have been the subjects of interest and controversy for many decades . By analyzing the variation of a large number ( 687 ) of genetic markers in almost 1 , 000 individuals from 41 Pacific populations , and comparing these with East Asians and others , we contribute to the clarification and resolution of many of these issues . To judge by the populations in our survey , we find that Polynesians and Micronesians have almost no genetic relation to Melanesians , but instead are strongly related to East Asians , and particularly Taiwan Aborigines . A minority of Island Melanesian populations have indications of a small shared genetic ancestry with Polynesians and Micronesians ( the ones that have this tie all speak related Austronesian languages ) . Inland groups who speak Papuan languages are particularly divergent and internally homogeneous . The genetic divergence among Island Melanesian populations , which is neatly organized by island , island size/topography , as well as their coastal or inland locations , is remarkable for such a small region , and enlarges our understanding of the texture of contemporary human variation . | [
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] | 2008 | The Genetic Structure of Pacific Islanders |
The hTREX complex mediates cellular bulk mRNA nuclear export by recruiting the nuclear export factor , TAP , via a direct interaction with the export adaptor , Aly . Intriguingly however , depletion of Aly only leads to a modest reduction in cellular mRNA nuclear export , suggesting the existence of additional mRNA nuclear export adaptor proteins . In order to efficiently export Kaposi's sarcoma-associated herpesvirus ( KSHV ) intronless mRNAs from the nucleus , the KSHV ORF57 protein recruits hTREX onto viral intronless mRNAs allowing access to the TAP-mediated export pathway . Similarly however , depletion of Aly only leads to a modest reduction in the nuclear export of KSHV intronless mRNAs . Herein , we identify a novel interaction between ORF57 and the cellular protein , UIF . We provide the first evidence that the ORF57-UIF interaction enables the recruitment of hTREX and TAP to KSHV intronless mRNAs in Aly-depleted cells . Strikingly , depletion of both Aly and UIF inhibits the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle and consequently prevents ORF57-mediated mRNA nuclear export and KSHV protein production . Importantly , these findings highlight that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs .
Post-transcriptional events which regulate mRNA biogenesis are fundamental to the control of gene expression [1] . A nascent mRNA is therefore steered through multimeric RNA-protein complexes that mediate its capping , splicing , polyadenylation , nuclear export and ultimately its translation [2] , [3] . A key aspect of these post-transcriptional events is that they are intrinsically linked [4] . For example , the act of splicing is coupled to the deposition of two distinct multiple protein complexes onto the mRNA which are involved in further processing events , namely the human transcription and export complex ( hTREX ) [5]–[7] and the exon-exon junction complex ( EJC ) [8] . The hTREX complex associates with the 5′end of the first exon by virtue of interactions with the cap-binding complex , and facilitates the nuclear export of the bulk mRNA through the TAP-mediated pathway [6] . In contrast , the EJC is deposited 20–24 nucleotides upstream of each exon-exon boundary and plays a role in mRNA surveillance [9] and translation enhancement [10]– . The TREX complex is conserved from yeast to metazoans [3] , [13] , [14] . The human TREX complex comprises several core components: Aly ( a NXF/TAP adaptor protein ) ; UAP56 ( a DEAD-box helicase ) ; Tex1 ( a protein of unknown function ) and the stable multi-protein hTHO complex ( hHpr1 , hTho2 , fSAP79 , fSAP35 and fSAP24 ) [3] . Moreover , recent proteomic analysis has identified CIP29/Tho1 as a hTREX component that is conserved in both yeast and metazoans [15] . The precise mechanism of how hTREX is assembled onto the mRNA is not fully understood or characterised . UAP56 is thought to associate with mRNA at an early stage during the assembly of the spliceosome and functions to mediate the recruitment of Aly , CIP and the THO complex in an ATP-dependent manner to form hTREX [15] , [16] . This involvement of the spliceosome in hTREX assembly reflects the splicing-dependent nature of mRNA nuclear export [16]–[18] . In addition to splicing , a functional 7-methylguanosine 5′ cap is also essential for hTREX recruitment , due to an interaction between Aly and the cap-binding complex protein , CBP80 [6] . Such cap-dependent recruitment of the export complex affords the mRNA polarity upon exiting the nuclear pore . Once assembled onto the mRNA , hTREX then instigates the recruitment of the nuclear export factor TAP , and its heterodimeric partner , p15 , at the nuclear periphery , via a direct interaction with Aly [18]–[20] . TAP binding then elicits a RNA handover mechanism which results in the remodelling of the protein-mRNA interactions within the ribonucleoprotein complex [21] . Subsequently , TAP associates with the nucleoporins through central and carboxy-terminal domains , directing the ribonucleoprotein though the nuclear pore complex into the cytoplasm [22] . Surprisingly , considering the central role played by Aly in TAP recruitment , gene knockdown experiments performed in Drosophila melanogaster and Caenorhabditis elegans have shown that only UAP56 , in contrast to Aly and THO-complex proteins , is required for bulk mRNA nuclear export [23]–[25] . Moreover , a genome-wide RNAi study in D . melanogaster reported that the conserved THO-complex was only required by a subset of transcripts for nuclear export [26] , [27] . This data indicates a degree of redundancy is present in these pathways and suggests the existence of additional export adaptor proteins which are involved in bulk mRNA nuclear export . In support of this idea , a novel mRNA export adaptor protein has recently been identified that utilises the UAP56/TAP-mediated pathway . UAP56-interacting factor ( UIF ) was initially identified in silica , by virtue of sequence similarity to the characterised UAP56-binding domain found in Aly [28] . Notably , cellular expression levels of UIF appear to be linked in vivo to the relative expression of Aly , as miRNA-mediated depletion of Aly led to a dramatic increase in UIF expression . Importantly , simultaneous depletion of both Aly and UIF leads to a dramatic nuclear accumulation of bulk mRNA [28] . Therefore , it is believed that Aly and UIF bind independently to the same mRNA providing multiple export adaptor proteins to recruit multiple TAP molecules to ensure efficient mRNA nuclear export . Moreover , the observation that UIF expression increases in Aly-depleted cells is believed to be a redundancy mechanism that ensures cellular survival should Aly expression be compromised . Given the importance of the formation of multimeric mRNA-protein complexes in mRNA biogenesis , it is not surprising that viruses manipulate and exploit these pathways . This is particularly important for herpesviruses which replicate in the host-cell nucleus and express numerous lytic intronless mRNAs . Due to the reliance of herpesviruses on the host cell machinery for efficient processing of their mRNAs , an immediate issue arises concerning the mechanism by which the viral intronless mRNAs are efficiently exported from the nucleus , given that the majority of cellular bulk mRNA nuclear export is intimately linked , and dependent upon , splicing [29] . We have investigated this potential roadblock to herpesvirus gene expression and replication in the gamma-2 herpesvirus , Kaposi's sarcoma-associated herpesvirus ( KSHV ) [30] , which is associated with the AIDS-related malignancies Kaposi's sarcoma ( KS ) , primary effusion lymphoma ( PEL ) and multicentric Castleman's disease [31]–[33] . To circumvent the roadblock of efficient intronless viral mRNA nuclear export , KSHV encodes a multi-functional protein termed ORF57/Mta . KSHV ORF57 is a functionally conserved protein found in all herpesviruses that plays a pivotal role in enhancing viral gene expression at a post-transcriptional level [34] , [35] . ORF57 has been implicated in multiple steps of RNA biogenesis , including enhancing viral splicing , protecting viral RNAs from degradation to enhancing viral mRNA nuclear export and translation [36]–[39] . We have demonstrated that KSHV ORF57 promotes the nuclear export of intronless viral mRNAs via the TAP-mediated pathway , by directly interacting with the hTREX export adaptor , Aly [37] . Moreover , we investigated the composition and assembly of these export-competent intronless KSHV ribonucleoprotein particles ( vRNP ) and showed that ORF57 functions to recruit the complete hTREX complex to intronless viral mRNA , an event that is essential for viral intronless mRNA export and KSHV replication [37] . Furthermore , these properties are also conserved in other gamma-2 herpesvirus ORF57 homologues , such as the Herpesvirus saimiri ( HVS ) ORF57 protein [40] , [41] . These data suggest that Aly is essential for ORF57-mediated KSHV intronless mRNA export , as well as playing an important role in mRNA nuclear export in other herpesviruses . However , experiments involving siRNA-mediated depletion of Aly report only a modest effect on ORF57-mediated KSHV intronless mRNA export , although only partial depletion of Aly was achieved [42] . This data correlates with depletion-related studies on the role of Aly in mRNA export in higher eukaryotes where , surprisingly , Aly has been shown to be dispensable in mRNA export [23] , [24] . Similar stories are also evident for other herpesviruses mRNA export proteins . For example , an observed interaction between ICP27 ( the HSV-1 ORF57 homologue ) and Aly was initially reported as important for HSV-1 mRNA export [43] . However , subsequent functional studies using siRNA-mediated depletion of Aly led to the authors suggesting that Aly is not essential for ICP27-mediated HSV-1 mRNA export [44] . This suggests that additional cellular mRNA export proteins play important roles in herpesvirus intronless mRNA export . Indeed , recently it has been demonstrated that the SR proteins , SRp20 and 9G8 , can contribute to efficient export of herpes simplex virus 1 mRNAs [45] . Herein we report a novel interaction between the KSHV ORF57 protein and the recently identified mRNA export adaptor protein , UIF . Moreover , we provide data to suggest that ORF57 may preferentially bind Aly compared to UIF . Furthermore , we investigate whether the linked expression of UIF and Aly plays a role in the apparent redundancy of Aly in herpesvirus intronless mRNA nuclear export . We provide the first evidence that the ORF57-UIF interaction enables the recruitment of the complete hTREX and the nuclear export factor , TAP , to KSHV intronless mRNA in Aly-depleted cells . Strikingly , we demonstrate that depletion of both Aly and UIF inhibit the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle and consequently prevent ORF57-mediated nuclear export of intronless viral mRNAs and KSHV protein production . Importantly , these findings highlight that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs .
KSHV ORF57 interacts directly with the cellular export adaptor protein Aly to recruit cellular hTREX , comprising UAP56 and the hTHO complex , onto a viral intronless mRNA to form an export competent ribonucleoprotein particle [37] . However , ORF57 and homologues can mediate nuclear export of an intronless viral mRNA in Aly-depleted cells [42] , suggesting that alternative export pathways may be targeted by the ORF57 protein . Therefore , to determine whether ORF57 interacts with alternative export adaptor proteins , GST-pulldown and co-immunoprecipitations assays were performed to assess if ORF57 interacted with the recently identified UAP56 interacting protein , UIF . Initially , recombinant GST- , GST-UAP56 or GST-ORF57 fusion proteins were produced and used in GST-pulldown assays . It must be noted however , that although full length GST-ORF57 is produced , a large proportion of the product is degraded as previously observed [37] . GST-pulldown experiments were therefore performed using equal amounts of total protein from each GST construct immobilised to beads followed by incubation with 293T cell lysates transfected with pUIF-Flag . Analysis showed that UIF interacted with both UAP56 and KSHV ORF57 ( Figure 1A ) . To confirm these results co-immunoprecipitation experiments were also performed . 293T cells were transfected with either pEGFP , pUAP56-myc or pORF57GFP in the presence of pUIF-Flag and used in co-immunoprecipitation experiments with GFP or UAP56-specific antibodies . Results confirmed the interaction between UIF and KSHV ORF57 ( Figure 1B ) . We have previously identified an ORF57 mutant protein , ORF57PmutGFP , which is unable to interact with Aly and therefore recruit the remainder of the hTREX complex onto viral intronless mRNAs [37] . Moreover , we demonstrated that this mutant is unable to efficiently export viral intronless mRNA from the nucleus suggesting that the recruitment of a complete hTREX complex is required for ORF57-mediated nuclear export . ORF57PmutGFP contains site-directed alterations of two proline residues within a PxxP poly-proline motif , situated in the previously identified minimal Aly-binding domain encompassing residues 181–215 . We have previously demonstrated that although ORF57PmutGFP is unable to bind Aly , it still retains features of the wild type ORF57 protein , namely localising to nuclear speckles , the ability to homodimerise , bind KSHV RTA and bind intronless viral mRNA [37] . To assess whether this mutant could interact with UIF , GST-pulldown experiments and co-immunoprecipitation experiments were performed as described above using GST-ORF57Pmut and pORF57PmutGFP , respectively . In both cases the mutant ORF57 protein , which fails to bind Aly , also lacks the ability to interact with UIF ( Figure 1A and 1B ) . Importantly , this suggests that the failure of ORF57PmutGFP to recruit hTREX and efficiently export intronless viral mRNAs from the nucleus may be due to the inability to bind either Aly or UIF . To determine if the interaction between ORF57 and UIF depended on RNA bridging , co-immunoprecipitation experiments were repeated in the absence and presence of RNase . 293T cells were transfected with either pEGFP or pORF57GFP in the presence of pUIF-Flag and co-immunoprecipitation assays were performed using a polyclonal Flag-specific antibody . In addition , no antibody and a negative control antibody ( α-SC-35 ) were also used in the analysis . ORF57 was readily precipitated using the Flag-specific antibody in contrast to negative controls . Moreover , the observed interaction was still detected in the presence of RNase suggesting the interactions are not due to RNA bridging ( Figure 1C ) . To ensure the RNase treatment was effective the immunoprecipitations were also blotted with an Aly-specific antibody . Results show that the UIF-Aly interaction is RNA dependent as previously described [28] , [36] . In order to address potential overexpression artefacts of the above co-immunoprecipitation experiments and also determine whether ORF57 interacts with UIF during KSHV lytic replication , latently-infected BCBL-1 cells remained uninduced or reactivated using the phorbol ester , TPA . Lytic expression was confirmed by the detection of ORF57 using Western blot analysis in the reactivated samples ( Figure 2 ) . Uninduced and reactivated cell lysates were then incubated with no antibody control , ORF57- or UIF-specific antibodies . Reciprocal western blot analysis using the antibodies in reverse demonstrated that ORF57 interacts with UIF during KSHV lytic replication ( Figure 2 ) . Therefore , these data provide the first evidence of a viral protein associating with UIF . ORF57 is a nucleocytoplasmic protein that is predominately observed in the nucleus , specifically colocalising with nuclear speckle and nucleoli-associated proteins [42] , [46] . Therefore , we were interested to determine whether ORF57 colocalises with UIF in either of these subnuclear domains . To this end , 293T cells were cultured on poly-L lysine coated coverslips and transfected with either pORF57-mCherry or pUIF-GFP alone or in combination . The subcellular localisation of ORF57 and UIF were observed via direct fluorescence , in addition indirect-immunofluorescence was performed to identify nuclear speckles and the nucleolus using SC35- ( Figure 3Bii ) and B23- ( Figure 3Dii ) specific antibodies , respectively . As previously observed ORF57 colocalises with both subnuclear domain markers ( Figure 3Bii and 3Dii ) . Moreover , UIF was also found to localise with these subnuclear structures and also colocalises with the ORF57 protein ( Figure 3B and 3D ) . However , results demonstrate that the majority of ORF57 and UIF colocalise in the nucleolus whereas only a proportion of ORF57 and UIF colocalise with the nuclear speckle marker , SC35 . One major difference between the mRNA export adaptor proteins Aly and UIF is the mechanism they utilise to be loaded onto mRNA . Aly has been shown to associate with mRNA in a UAP56 and splicing-dependent manner [47] , in contrast UIF is loaded onto mRNA via the histone chaperone FACT [28] . We have previously demonstrated that ORF57 is required for the recruitment of Aly and the remainder of the hTREX complex onto viral intronless mRNAs , therefore we were intrigued to determine if UIF could associate with intronless viral mRNAs in an ORF57-independent manner using RNA-immunoprecipitation ( RNA-IP ) assays . A vector expressing KSHV ORF47 ( a late structural intronless gene ) was transfected into 293T cells with either pEGFP or pORF57GFP . Total cell lysates were then used in immunoprecipitations performed with either No , Y14- ( negative control ) , UIF- or GFP-specific antibodies and the amount of ORF47 precipitated was measured by qRT-PCR . RNA-IPs performed on cell extracts transfected with pORF47 and pEGFP failed to show an interaction between UIF and the viral intronless ORF47 mRNA ( Figure 4 ) . In contrast , extracts from cells transfected with both pORF47 and pORF57GFP displayed a clear interaction between UIF , ORF57GFP and the intronless viral ORF47 mRNA ( Figure 4 ) . These data show that although UIF can associate with cellular spliced and unspliced single exon cellular mRNAs , ORF57 is required for the recruitment of UIF onto intronless viral mRNA . We have previously demonstrated that the nuclear export adaptor protein , Aly , is recruited to viral intronless mRNAs in a splicing-independent manner by directly interacting with ORF57 . Once bound it then leads to the recruitment of the remaining components of hTREX , in turn leading to efficient nuclear export of these viral intronless mRNAs via a TAP-mediated pathway [37] . We therefore next sought to determine if UIF can perform a similar function by linking ORF57 to hTREX components such as UAP56 . Initially , we determined whether ORF57 interacted with UIF directly using GST-pulldown assays . Recombinant GST- and GST-ORF57 proteins were immobilised to beads and incubated with purified recombinant UIF-6xHis or a negative control purified recombinant HVS ORF73-6xHis protein [48] . UIF-6xHis was precipitated by GST-ORF57 but not the negative GST control , moreover ORF73-6xHis failed to interact with either GST or GST-ORF57 ( Figure 5A ) . These data provide further support for the direct interaction between ORF57 and UIF . Given the fact that ORF57 and UIF interact directly , we next determined whether UIF can bridge the interaction between ORF57 and hTREX components , such as UAP56 , which we have previously shown fails to interact with ORF57 directly [37] . Reconstitutive GST-pulldowns were therefore performed using recombinant GST- and GST-UAP56 proteins immobilised to beads and incubating with either purified recombinant ORF57-6xHis or purified recombinant UIF-6xHis alone or in combination . No interaction with GST or GST-UAP56 was observed in the presence of ORF57-6xHis alone . In contrast , an interaction between GST-UAP56 and ORF57 was observed in the presence of purified UIF-6xHis protein ( Figure 5B ) , suggesting that UIF can facilitate the formation of the ORF57-hTREX complex . This provides the first evidence to demonstrate that UIF could function to assemble the hTREX complex on viral intronless mRNAs . The above data demonstrate that UIF interacts directly with ORF57 and suggest that it can function to bridge an interaction between ORF57 and the remaining hTREX components . This mechanism is similar to our previous observations regarding the functional significance of the Aly-ORF57 interaction , and therefore leads to the intriguing question of whether ORF57 has a preference for Aly binding over UIF or vice versa . To address this question we performed competitive GST pulldown assays . Recombinant GST-ORF57 protein was immobilised to beads and incubated with a constant amount ( 1 µg ) of purified recombinant Aly-6xHis protein , in addition the pulldown was spiked with increasing amounts of purified recombinant UIF-6xHis protein ( 0 , 0 . 5 , 1 , 2 , 3 µg ) . Western blot analysis was then performed using an Aly-specific antibody . Results demonstrate that the binding of Aly to GST-ORF57 is only slightly reduced in the presence of increasing amount of UIF ( Figure 6Ai ) , suggesting that UIF cannot out-compete Aly for ORF57 binding . Similar spiked experiments were performed using a constant amount of UIF and increasing amounts of Aly . In contrast , results showed that even low quantities of Aly led to a dramatic loss of UIF binding to the ORF57 protein ( Figure 6Aii ) . These results reveal that Aly can out-compete UIF for ORF57 binding , suggesting that ORF57 may preferentially bind Aly to form an export competent ribonucleoprotein particle . However as shown in Figure 1A , although bacterial expression of full length GST-ORF57 results in a full length ORF57 protein , a large proportion of degraded products are also produced . Therefore , to further assess the possibility that ORF57 may interact with Aly preferentially over UIF , dose-dependent coimmunoprecipitation assays were performed . To this end , 293T cells were cotransfected with 0 . 5 ug of pORF57GFP and 0 . 5 ug of pAly-myc , in addition to increasing amounts of pUIF-Flag ( 0 , 0 . 1 , 0 . 5 , 0 . 8 , 1 . 2 ug ) . After 24 hours , cell lysates were incubated with GFP-TRAP-Affinity agarose beads and the amount of precipitated Aly was identified by immunoblotting with a Myc-specific antibody . Results again show that the binding of Aly is only slightly reduced in the presence of increasing amounts of UIF ( Figure 6Bi ) . Moreover , reciprocal dose-dependent coimmunoprecipitations were performed using 0 . 5 ug of pORF57GFP and 0 . 5 ug of pUIF-Flag , in addition to increasing amounts of pAly-myc ( 0 , 0 . 1 , 0 . 5 , 0 . 8 , 1 . 2 ug ) . In contrast , results suggest that higher concentrations of Aly can significantly reduce the amount of precipitated UIF ( Figure 6Bii ) . These results corroborate the above GST pulldown assays and suggest that ORF57 may preferentially bind Aly over UIF to form an export competent ribonucleoprotein particle . Having established that both Aly and UIF can bridge an interaction between ORF57 and hTREX components , such as UAP56 , we next sought to determine the effect of depleting Aly and UIF either singularly , or in combination , on the ability of ORF57 to form an export competent ribonucleoprotein particle containing the complete hTREX complex and the nuclear export factor TAP . To this end , we have utilised doxycycline inducible 293 cell lines expressing miRNAs targeting Aly , UIF or both Aly and UIF [28] . Effective depletion of Aly , UIF or both proteins can be observed after 72 hours post doxycycline induction ( Figure 7A ) . However , a caveat of this type of experiment is that depletion of multiple mRNA export factors in combination may firstly be toxic to the host cell and second inhibit the expression of ORF57 itself as recently reported [49] . Characterisation of the cell viability and growth of the cells depleted with both Aly and UIF has previously been performed and results show they are viable and grow for 4 days post knockdown prior to cell death at day 6 [28] . Therefore all experiments using these cell lines were performed in this 4 day window . Moreover , to ensure ORF57 protein production , cells were transfected at 48 hours prior to complete Aly or UIF depletion at 72 hours . To assess viral ribonucleoprotein particle formation , wild type 293 cells and each miRNA-targeted cell line were induced with doxycycline to deplete the respective proteins and after 48 hours' induction , each cell line was transfected with pORF57GFP . After a further 24 hours when maximum Aly and UIF depletion has occurred , cell lysates were used in co-immunoprecipitation experiments using GFP-TRAP-Affinity agarose beads . Western blot analysis was then performed using UAP56- , FSAP79- ( a hTHO complex component ) and TAP-specific antibodies . As a negative control , GFP was also transfected into the wild type 293 cell line and co-immunoprecipitations performed using GFP-TRAP-Affinity agarose beads , no interactions were observed with any of the hTREX components or TAP . However , results showed that expression of ORF57 in the wild type 293 cell line led to the precipitation of UAP56 , FSAP79 and TAP suggesting that ORF57 expression leads to the formation of an export competent ribonucleoprotein particle ( Figure 7B ) . Similar complex formation was observed in cell lines depleted singularly for Aly and UIF , where ORF57 can precipitate UAP56 , FSAP79 and TAP ( Figure 7B ) . In contrast , depletion of Aly and UIF in combination significantly reduced the interaction between ORF57 and the hTREX components and the nuclear export factor TAP . Importantly , these data demonstrate that either Aly or UIF are required for the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle . The above data suggest that ORF57 must interact with either export adaptor protein , Aly or UIF , to recruit hTREX and the nuclear export protein TAP , to form an export competent ribonucleoprotein particle . Therefore , we next determined whether both UIF and Aly were required for efficient ORF57-mediated nuclear export of viral intronless mRNAs . To this end , we assessed the ability of ORF57 to enhance the nuclear export of the KSHV intronless ORF47 mRNA , using a previously described assay to compare the accumulation of ORF47 mRNA in the cytoplasm [46] . Essentially , cells are transfected with a plasmid expressing the intronless KSHV ORF47 gene in addition to either GFP or wild type ORF57 constructs . After 24 hours , RNA is extracted from total and cytoplasmic fractions and RNA levels quantified using qRT-PCR . Total RNA levels are assessed to ensure similar expression levels of the ORF47 mRNA in each sample , where an increase in cytoplasmic levels of ORF47 mRNA signifies an increase in ORF57-mediated mRNA export levels . Therefore , to assess the ability of ORF57 to export ORF47 mRNA from the nucleus in the absence of either UIF or Aly or both , wild type 293 cells and each miRNA-targeted cell line were induced with doxycycline to deplete the respective proteins and after 48 hours induction , each cell line was transfected with pORF57GFP and pORF47 . Again , this allowed sufficient time to express ORF57 prior to optimal export adaptor protein depletion . After a further 24 hours , RNA was extracted from total and cytoplasmic fractions and ORF47 levels assessed by qRT-PCR . Results demonstrated that ORF47 mRNA levels from total cell fractions are similar in wild type and the depleted cell lines . Moreover , in the control 293 cell line ORF47 mRNA accumulates in the cytoplasm in the presence of ORF57 as previously described [46] . Similarly , mRNA can accumulate in the cytoplasm of cells depleted singularly for Aly and UIF , however , a reduction in export efficiency was observed of approximately 40% and 23% of wild type levels , respectively ( Figure 8A ) . In contrast , depletion of both Aly and UIF together led to a dramatic reduction of ORF47 mRNA accumulation in the cytoplasm with an 80% decrease compared to wild type levels ( Figure 8A ) . We next tested whether the observed reduction in the ability of ORF57 to export intronless mRNAs from the nucleus in cell lines depleted for Aly and UIF had any effect on KSHV protein production . To this end , the wild type 293 cells and each miRNA-targeted cell line were induced with doxycycline to deplete the respective proteins and after 48 hours induction , each cell line was infected with recombinant KSHV at a MOI = 1 . This time point was used to allow sufficient time to express ORF57 prior to optimal export adaptor protein depletion . After a further 48 hours , the cell lysates were analysed by immunoblotting using KSHV glycoprotein B- and ORF4-specific antibodies . Results showed that gB protein expression in cell lines singularly depleted for either Aly or UIF was reduced by ∼42% and ∼10% , respectively , whereas little or no reduction was observed for ORF4 protein levels in the singularly depleted cells . Strikingly , however depletion of both Aly and UIF led to a dramatic reduction in both gB and ORF4 expression levels of 78% and 79% , respectively ( Figure 8B ) . These results suggest that depletion of UIF has limited if any effect of virus replication , however , depletion of UIF together with Aly had a dramatic negative effect on KSHV protein production . However , it must be noted that this reduction in protein levels may also stem from altered levels of one or more key cellular proteins involved in KSHV lytic protein production . Taken together , our data suggest that either one of the cellular nuclear export adaptor proteins , Aly or UIF , is required for the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle which is essential for KSHV protein production .
The nuclear export of bulk mRNA is mediated by the conserved heterodimeric export receptor , TAP/p15 [3] . Cellular mRNAs gain access to TAP/p15 via interaction with a group of RNA-binding proteins termed export adaptors . The first mRNA export adaptor to be identified in higher systems was Aly/REF , and subsequent work from a number of groups led to the current model where Aly is recruited to the 5′ cap of spliced mRNA along with several other proteins to form a multimeric protein complex termed hTREX [6] . The hTREX complex facilitates the association of bound mRNAs with TAP/p15 thus licensing nuclear export . In addition to Aly , several other hTREX components have been identified including the DEAD-box helicase UAP56 , hTex1 , the multi-protein THO complex and recently , CIP29 [15] . While the underlying mechanism of hTREX-mediated mRNA export is loosely understood , the individual functions of the hTREX components remain elusive . Perhaps the greatest enigma surrounding TAP/p15-mediated mRNA export is the apparent redundancy that exists for certain hTREX proteins . This is particularly true for Aly , where a number of different studies have shown that the metazoan homologue , REF1 , is not required for the bulk export of mRNA [23] , [24] . These studies suggest that additional mRNA export adaptors must exist which can function to link nascent mRNA to the TAP/p15 heterodimer . Moreover , this raises the intriguing possibility that , via the use of numerous different mRNA export adaptor proteins , a further layer of control may exist to regulate gene expression . Indeed , several recent reports have highlighted that differences exist within component members of mRNA export complexes associated with different classes of mRNAs . For example , HSP70 mRNA only requires Aly and the co-adaptor Thoc5 to mediate TAP recruitment [50] . Moreover , an alternative mRNA export ( AREX ) complex , distinct to hTREX has recently been identified which comprises the related RNA helicase URH49 , instead of UAP56 [51] . Interestingly , each helicase regulates a specific set of mRNAs associated with distinct subsets of key mitotic regulators . In addition , members of the SPEN family of proteins , RBM15 and OTT3 are functionally similar , in that they can bind RNA and physically interact with TAP . However , the association of OTT3 with TAP is attenuated compared to RBM15 , leading to speculation that strong and weak variants exist that may function during developmental or tissue specific mRNA processing events [52] . These data galvanise the hypothesis that ultimately it is the recruitment of TAP/p15 that is required for nuclear export , and that one function of the export adaptor proteins is to provide selectivity to this system . Such a hypothesis is consistent with , and offers an explanation to , conflicting data regarding the nuclear export of KSHV intronless mRNAs . Herpesviruses hijack the TAP/p15-mediated mRNA export pathway in order to enhance the nuclear export of viral intronless mRNA . We have previously shown that during KSHV replication the virus-encoded ORF57 protein procures the hTREX complex ( and subsequently TAP/p15 ) via a direct interaction with Aly , facilitating the efficient export of KSHV intronless mRNAs [37] . We proposed therefore , that as the ORF57-Aly interaction provides the link between the virus mRNA and hTREX , it was likely that Aly would be essential for KSHV mRNA export . This hypothesis was supported by data showing that an ORF57 mutant , ORF57PmutGFP , unable to bind Aly was no longer functional in virus mRNA export . However , similarly to previous studies in D . melanogaster and C . elegans , siRNA-mediated depletion of Aly did not translate to a decrease in ORF57-mediated nuclear export of KSHV intronless mRNA , although only partial knockdown of Aly was observed [42] . Correspondingly , the HSV homologue of ORF57 , ICP27 , was shown to directly interact with Aly . Moreover , studies in Xenopus laevis oocytes showed ICP27 dramatically stimulated the export of intronless viral mRNAs , and a mutant ICP27 protein that failed to interact with REF is inactive in viral mRNA export [43] . Again however , siRNA-mediated depletion of Aly has been shown not to affect HSV-1 mRNA export [44] . Herein , we demonstrate that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs . Evidence for such redundancy in export adapter proteins was recently provided by the identification of a second mRNA export adaptor protein , UIF [28] . Importantly , cellular expression levels of UIF appear to be linked in vivo to the relative expression of Aly , as depletion of Aly leads to a dramatic increase in UIF expression . This would therefore account for the modest reduction in mRNA nuclear export in Aly-depleted cells . Indeed , as shown in Figure 1 and 5 , ORF57 interacts directly with UIF and thus is able to recruit hTREX/TAP/p15 allowing efficient intronless virus mRNA nuclear export in Aly-depleted cells ( Figure 8 ) . Recent analysis has also suggested that additional mechanisms exist to ensure the nuclear export of viral transcripts in other herpesviruses . For example , ICP27 can bind directly to TAP , suggesting ICP27 can bypass nuclear export adapter proteins [53] . However , although analysis of ICP27 mutants unable to interact with TAP export showed greatly reduced intronless viral mRNA export , it was not completely abolished suggesting other cellular proteins may have a role . Indeed , recent analysis has shown that nuclear accumulation of HSV-1 mRNA is reduced when cells were treated with siRNAs specific for the SR proteins , SRp20 and 9G8 , confirming that other cellular export proteins , such as SR proteins , can contribute to HSV-1 mRNA nuclear export [45] . Similarly , the EBV ORF57 homologue , SM/EB2 , can interact with SRp20 , although to date , this interaction has been implicated in alternative splicing mechanisms [54] . However , EBV SM/EB2 has been previously shown to interact with alternative cellular export factors , such as CRM-1 [55] . An alternative approach may be employed by the hCMV ORF57 homologue , UL69 , which interacts with other hTREX proteins required for bulk mRNA nuclear export , such as UAP56 [56] . However , current work is ongoing to determine if these homologues interact with UIF . Moreover , the role of UIF may also have wider implications in the field of virology . Influenza A virus produces capped and polyadenylated mRNAs in the nucleus of infected cells that resemble mature cellular mRNAs , which require export by the TAP-mediated pathway [57] . Depletion of Aly had little effect on viral mRNA export , but reduction of UAP56 levels strongly inhibited trafficking and/or translation of influenza mRNAs [58] . It will now be interesting to determine whether UIF also substitutes for Aly function in this viral system . There are however , some important mechanistic differences between Aly and UIF which have implications for KSHV intronless mRNA nuclear export . The hTREX component , CIP29 , bridges the Aly-UAP56 interaction to form a trimeric complex that is assembled in an ATP-dependent manner [15] . Importantly , the recruitment of Aly to the mRNA requires an interaction with the 5′ cap and is dependent on splicing [6] . However , UIF appears to be co-transcriptionally loaded onto burgeoning mRNAs via an interaction with the histone chaperone , FACT [28] . It appears therefore that Aly and UIF are deposited onto the same mRNA separately and independently , a hypothesis supported by ribonuclease-treated co-immunoprecipitation experiments , which show that the interaction between Aly and UIF is facilitated by RNA-bridging [28] , [36] . These data suggest that there are two distinct cellular mechanisms that can each recruit TAP to an mRNA . This raises a number of interesting questions with regards to how ORF57 orchestrates the recruitment of hTREX ( and ultimately TAP/p15 ) via UIF . As seen in Figure 4 , UIF is recruited to KSHV intronless mRNA only in the presence of ORF57 , this is in stark contrast to the mechanism by which UIF is loaded onto cellular mRNA . Why UIF is not loaded onto KSHV intronless transcripts via FACT is unclear . One possible explanation is that FACT does not interact with RNA polymerase II during the transcription of ORF47 mRNA in this assay , possibly due to incomplete chromatinisation of vector DNA . Alternatively , recruitment of UIF to both spliced and unspliced mRNA maybe partially dependent on UAP56 and we have previously shown that UAP56 recruitment to KSHV mRNA is dependent on the ORF57 protein [37] . As mentioned above , Aly and UIF are loaded separately onto the same cellular mRNA via different mechanisms and both function to ultimately recruit TAP/p15 to the mRNA via interactions with hTREX . Intriguingly , we show in Figure 6 , that ORF57 may preferentially bind to Aly over UIF , using both competitive GST-pulldown and dose-dependent coimmunoprecipitation assays . Why KSHV ORF57 would evolve to preferentially bind Aly over UIF is at present uncertain . One possibility is that Aly is the major export adaptor protein and UIF forms a backup or default pathway . This is not without precedent as proteins expression levels suggest that Aly is more abundantly expressed than UIF and UIF protein levels significantly increase in Aly-depleted cells [28] . Alternatively , it is possible that ORF57 may have a higher affinity for Aly due to important functional differences in how the Aly export adaptor recruits the remaining hTREX components to virus mRNA , compared with UIF . Alternatively , Aly and UIF could recruit different components of the hTREX complex to a KSHV mRNA , highlighted by the Aly-specific recruitment of CIP29 , and that the export of KSHV intronless mRNA is more reliant on these Aly-recruited hTREX proteins . As discussed earlier , a number of siRNA-mediated studies have proposed that Aly is not essential for KSHV intronless mRNA export . However , we have previously described an ORF57 mutant protein , ORF57Pmut , which is unable to interact with Aly and failed to export viral intronless mRNAs [37] . The region mutated in ORF57Pmut maps to a PxxP motif in the N-terminal region of the protein . It is not known whether the PxxP motif mutated in ORF57Pmut is a direct interaction site for Aly , or if this mutant confers some structural change of ORF57 in the Aly binding region . Importantly , herein we have shown that this mutant is also unable to interact with UIF , suggesting that ORF57Pmut is ‘dead’ with regards to export adaptor interaction . This explains therefore why this mutant is unable to export viral intronless mRNAs , as it is unable to bind to either Aly or UIF ( Figure 1 ) . This result is also confirmed by depletion of both these export adaptors which lead to a block in KSHV mRNA nuclear export . Importantly , Aly depletion in these and previous studies have shown that UIF expression is increased and therefore UIF probably replaces Aly as the dominant export adaptor protein . It is tempting to speculate that the link between increased UIF expression in Aly-depleted cells is a redundancy mechanism that ensures cellular survival should Aly expression be compromised . The fact that ORF57Pmut is unable to interact with both Aly and UIF would suggest that the PxxP motif is either the complete ORF57 interacting motif , or part of the interacting motif , for Aly and UIF binding , and that the binding sites for the two proteins are either identical or overlap to some degree . Alternatively , the PxxP motif may cause a loss of interaction of both Aly and UIF by altering the structure of each of the binding sites . Importantly , our competition assays demonstrate that ORF57 may preferentially bind to Aly over UIF . These observations suggest that Aly and UIF may compete for a binding site on ORF57 , and further studies are now required to determine if this is the case . Interestingly , we have recently identified the key residues that interact directly with Aly in both HSV-1 ICP27 and herpesvirus saimiri ( HVS ) ORF57 using solution-state NMR and mapped this interaction to a WRV/A motif [59] . Due to the sequence differences between ORF57 homologues this motif does not appear in KSHV ORF57 , although the region of KSHV ORF57 that interacts with Aly has been mapped to the N terminus ( aa 1–215 ) . We are currently investigating the interacting residues for both Aly and UIF within this N-terminal region of KSHV ORF57 using solution-state NMR . In summary , our results demonstrate the first known interaction between a viral protein and the newly described export adaptor protein , UIF . Importantly , the ORF57-UIF interaction is sufficient to recruit the hTREX complex onto viral intronless mRNAs and highlights that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs . It now seems clear that the events which lead up to TAP/p15 recruitment to the mRNA are not linear . Indeed , it appears that multiple pathways exist by which an mRNA can bind TAP/p15 and be licensed for nuclear export . The existence of numerous export adaptor proteins may partly be explained in terms of redundancy but there is strong evidence to suggest that this also generates specificity within the system .
Details of oligonucleotides used for qRT-PCR have been described previously [37] , [46] . KSHV , hTREX and UIF-related plasmid constructs have been described previously [6] , [28] , [37] . KSHV ORF57- and ORF4- specific antibodies were a kind gift from Gary Hayward ( Johns Hopkins , Baltimore ) and Brad Spiller ( Cardiff University ) , respectively . Antibodies against SC-35 , Flag , Myc and Aly ( Sigma ) , GFP and mCherry ( Clontech ) , B23 ( Santa Cruz ) , KSHV gB ( Abcam ) and GAPDH ( Abcam ) were purchased from their respective suppliers . Western blot analysis was carried out using specific antibodies at 1∶1000 dilution , except for UIF-specific antibody ( 1∶250 ) and GFP-specific antibody ( 1∶5000 ) . Antibodies used for immunofluorescence studies were at a dilution of 1∶250 . 293 inducible cells lines which specifically deplete Aly , UIF and both Aly and UIF have been previously reported [28] . They were produced using the FLP-In T-REX 293 cells ( Invitrogen ) system to express miRNAs to each specific export adapter protein , miRNA sequences are detailed in Hautbergue et al . , 2009 . HEK-293T cells , HEK-293T BAC36 cells harbouring a recombinant KSHV BAC36 genome and FLP-In T-REX 293 cells were cultured in Dulbecco's modified Eagle medium ( DMEM , Invitrogen ) supplemented with glutamine , 10% foetal calf serum ( FCS , Invitrogen ) and penicillin-streptomycin . 293T BAC36 cells were reactivated using TPA ( 20 ng/ml ) for the designated time . miRNA expression from FLP-IN T-REX 293 cells was induced with 2 µg/ml doxycyclin ( Sigma ) for the designated time . Plasmid transfections were carried out using Lipofectamine 2000 ( Invitrogen ) or GeneJuice ( Novagen ) and were carried out as per the manufacturer's instructions . rKSHV . 219 ( KSHV ) was produced from the latently infected Vero line [60] . This virus specifies red fluorescent protein ( RFP ) from the KSHV lytic PAN promoter , green fluorescent protein ( GFP ) from the EF-1α promoter , and encodes a puromycin resistance gene . Vero cells stably infected with rKSHV . 219 were maintained in MEM Eagles medium , 2 . 2 g/L NaHCO3 , 10% fetal calf serum , puromycin ( 5 ug/ml ) ( Sigma-Aldrich , Poole , UK ) and penicillin and streptomycin ( Invitrogen ) . To induce KSHV lytic replication in these cells , they were infected with BacK50 , a baculovirus construct encoding the lytic switch RTA protein , and treated with 1 . 25 mM sodium butyrate ( Sigma ) . 48 h after KSHV reactivation , the supernatant was harvested , centrifuged ( 500g , 15 mins ) to remove cell debris , and the virions concentrated by centrifugation ( 65 , 000g , 4 h ) . The virion pellet was resuspended overnight in EBM2 medium ( Lonza , Clonetics ) . The rKSHV . 219 titre was determined on 293 cells , quantifying GFP-positive cells by fluorescence microscopy . 293 and 293 derived cells were infected with KSHV . To this end , cells were plated at 1 . 25×105 cells per well in 24-well plates for infection and cultured overnight . The culture medium was then removed and replaced with virus diluted in EBM2 basal media after 24 hrs . Cells were then centrifuged for 30 min at 420× g at room temperature . Cells were transferred to a 37°C incubator ( 5% CO2 , humidified ) for 90 min . Virus supernatant was removed and cells were washed once in cell culture media and incubated for 48 hrs before being harvested . Recombinant GST , GST-ORF57 , GST-ORF57pmut , GST-UAP56 and UIF-His , Aly-His and ORF73-His were expressed and purified as previously described [36] , [37] , [61] . Purification of Baculovirus recombinant ORF57-6xHis was as per the manufacturer's instructions ( Invitrogen ) using the pFASTBac protocol . GST pull-down experiments and co-immunoprecipitations were performed as described previously [62] , [63] . GFP-TRAP-Affinity ( Chromotek ) experiments were performed as per the manufacturer's instructions . RNA immunoprecipitation experiments were carried out as follows: 1×107 adherent 293T cells were transiently transfected with appropriate GFP-containing plasmid DNA . After the appropriate amount of time cells were washed in ice-cold PBS and UV irradiated ( 900 mJ/cm2 ) using a Stratalinker 2400 ( Stratagene ) to crosslink protein and RNA . Cells were then scraped , transferred to an RNA-free tube and pelleted at 300× g for 3 min . Cell pellets were then resuspended in 2 ml lysis buffer [Dulbecco's PBS , 1% Nonidet P-40 ( v/v ) , 1 µl/ml RNaseOUT ( Invitrogen ) , 1× Complete EDTA-free Protease inhibitor ( Roche ) ] . Cells were left on ice for 30 min before being centrifuged for 10 min at 15 , 000× g . The clear lysate was then transferred to a clean RNA-free tube . 1 ml of the cleared lysate was added to 30 µl pre-washed GFP-TRAP-Affinity agarose beads ( Chromotek ) per IP and immunoprecipitated at 4°C with end-over-end mixing for 4 hrs . Beads were washed 3 times in ice-cold PBS containing 1× Complete EDTA-free protease inhibitor ( Roche ) followed by a further 2 times in PBS . Beads where then incubated in protease buffer ( Dulbecco's PBS , 1% Nonidet P-40 ( v/v ) , 0 . 1% SDS ( w/v ) , 0 . 5 mg/ml Proteinase K ) for 30 min at 50°C . RNA was extracted using TRIzol reagent ( Invitrogen ) as per the manufacturer's directions . cDNA was then produced from 10 µl of RNA using Superscript II RT ( Invitrogen ) and qPCR performed to analyse the relative levels of cDNA . RT-ve samples were used as controls . Bacterially expressed GST-tagged ORF57 was immobilised to GST beads and used for GST pulldown competition assays . Recombinant His-tagged Aly or UIF was expressed and purified as previously described [36] , [37] . Equal amounts of Aly-His ( 1 µg ) were used in the pull-downs with increasing amounts of UIF-His ( 0 , 0 . 5 , 1 , 2 , 3 µg ) . The converse experiments were also performed with equal amounts of UIF-His ( 1 µg ) and increasing amounts of Aly-His ( 0 , 0 . 5 , 1 , 2 , 3 µg ) . To assess ORF57-mediated ORF47 mRNA export efficiency , 293T and inducible cells were cotransfected with ORF47 and ORF57 expression constructs . After 24 hours RNA was extracted from total and cytoplasmic fractions using TRIzol ( Invitrogen ) as described by the manufacturer . Cytoplasmic fractions were produced by lysis of cells in 200 µl of PBS 1% Triton-X 100 ( v/v ) containing 40 U of RNaseOUT ( Invitrogen ) , prior to TRIzol purification . RNA was DNase treated using the Ambion DNase-free kit , as per the manufacturer's instructions , and RNA ( 1 µg ) from each fraction was reverse transcribed with SuperScript II ( Invitrogen ) , as per the manufacturer's instructions , using oligo ( dT ) primers ( Promega ) . 10 ng of cDNA was used as template in SensiMixPlus SYBR qPCR reactions ( Quantace ) , as per manufacturer's instructions , using a Rotor-Gene Q 5plex HRM Platform ( Qiagen ) , with a standard 3-step melt program ( 95°C for 15 seconds , 60°C for 30 seconds , 72°C for 20 seconds ) . With GAPDH as internal control mRNA , quantitative analysis was performed using the comparative CT method as previously described [46] . Immunofluorescence staining and visualisation by microscopy was carried out as previously described [64] . Visualisation was performed on an LSM 510 Meta confocal microscope ( Zeiss ) and images were analysed using the LSM imaging software ( Zeiss ) . | Herpesviruses hijack cellular components to enhance viral gene expression . This is particularly important for the efficient nuclear export of herpesvirus intronless mRNAs to allow the production of viral proteins . We have previously demonstrated that Kaposi's sarcoma-associated herpesvirus encodes a conserved protein , ORF57 , which recruits essential cellular mRNA export proteins onto the viral intronless mRNAs to form an export competent viral ribonucleoprotein particle . Specifically , we have shown that ORF57 interacts directly with the cellular export adaptor protein , Aly , to recruit other cellular mRNA export proteins . Surprisingly however , depletion of Aly has a limited effect on both cellular and viral mRNA nuclear export levels , suggesting a degree of redundancy in the export pathways and the existence of other export adaptor proteins . Here we have identified a novel interaction between ORF57 and a second export adaptor protein , UIF . We show for the first time that the ORF57-UIF interaction allows the recruitment of the essential cellular mRNA export proteins onto viral intronless mRNA , in cells lacking Aly . However , depletion of both Aly and UIF prevents the formation of an export competent viral ribonucleoprotein particle , suggesting that either Aly or UIF must be present for efficient KSHV intronless mRNA nuclear export and protein production . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"biology"
] | 2011 | An Interaction between KSHV ORF57 and UIF Provides mRNA-Adaptor Redundancy in Herpesvirus Intronless mRNA Export |
Dengue virus ( DV ) infection is the most prevalent mosquito-borne viral disease and its manifestation has been shown to be contributed in part by the host immune responses . In this study , pathogen recognition receptors , Toll-like receptor ( TLR ) 2 and TLR6 were found to be up-regulated in DV-infected human PBMC using immunofluorescence staining , flow cytometry and Western blot analyses . Using ELISA , IL-6 and TNF-α , cytokines downstream of TLR2 and TLR6 signaling pathways were also found to be up-regulated in DV-infected PBMC . IL-6 and TNF-α production by PBMC were reduced when TLR2 and TLR6 were blocked using TLR2 and TLR6 neutralizing antibodies during DV infection . These results suggested that signaling pathways of TLR2 and TLR6 were activated during DV infection and its activation contributed to IL-6 and TNF-α production . DV NS1 protein was found to significantly increase the production of IL-6 and TNF-α when added to PBMC . The amount of IL-6 and TNF-α stimulated by DV NS1 protein was reduced when TLR2 and TLR6 were blocked , suggesting that DV NS1 protein is the viral protein responsible for the activation of TLR2 and TLR6 during DV infection . Secreted alkaline phosphatase ( SEAP ) reporter assay was used to further confirm activation of TLR2 and TLR6 by DV NS1 protein . In addition , DV-infected and DV NS1 protein-treated TLR6-/- mice have higher survivability compared to DV-infected and DV NS1 protein-treated wild-type mice . Hence , activation of TLR6 via DV NS1 protein could potentially play an important role in the immunopathogenesis of DV infection .
Dengue virus ( DV ) is a member of the Flavivirus genus of the Flaviviridae family . Dengue virus is a positive-sense , single-stranded RNA virus and it has four distinct serotypes ( DV1 to 4 ) . Infection by one serotype only confer resistance to the other serotypes for a few months and subsequent secondary infection of a different serotype has a higher risk of developing into the more severe forms of dengue infection; the dengue hemorrhagic fever or dengue shock syndrome [1–5] . Dengue virus genome encodes for a single polyprotein that consists of 3 structural proteins ( capsid , premembrane and envelope ) that form the physical structure of the virus particle and 7 non-structural proteins ( NS1 , NS2a , NS2b , NS3 , NS4a , NS4b , NS5 ) which are necessary for the replication of the virus . Dengue is a mosquito-borne viral disease transmitted through a human-to-mosquito-to-human transmission cycle typically by the Aedes mosquitoes: Aedes aegypti and Aedes albopictus . DV infection remains the most prevalent mosquito-borne viral disease and the geographical regions at risk are continually growing due to globalisation and climate change [6] . It is estimated that 100 million cases of dengue infection occur worldwide each year with 2 . 5 billion people at risk [7–9] . Till now , no effective treatment and vaccine are available for DV infection . The pathogenesis of dengue is not well-understood . The mechanism underlying the wide range of dengue manifestations remain largely unknown . However , the observation that plasma leakage in DHF develops not when the viremia is at its peak in infected patients but when viremia has been significantly reduced or cleared , suggesting that host immune response is responsible for the development DHF [10–13] . In addition , studies have demonstrated that the host immunological mechanism could play a key role in the manifestation of dengue infection [3 , 14–16] . Up-regulation of proinflammatory cytokines and immune cells during dengue virus infection could lead to increased vascular permeability and leakage [17–20] . The hypotheses of antibody-dependent enhancement of infection and original antigenic sin have been proposed to explain the underlying mechanism that contributes to the manifestation of the more severe forms of the dengue infection during secondary infections [21–24] . Toll-like receptors ( TLRs ) are pathogen recognition receptors ( PRRs ) . PRRs are a group of receptors that play a key role in immune surveillance . Pathogen recognition receptors are important as they alert the immune system of the presence of foreign microbes by recognizing pathogen-associated molecular patterns ( PAMPs ) and activating the immune system upon binding to PAMPs . In human , 10 functional TLRs are documented and each recognizing a group of PAMPs . When TLR is activated , adapter molecules like myeloid differentiaton primary response gene 88 ( MyD88 ) , toll-interleukin 1 receptor domain containing adaptor protein ( Tirap ) , TIR-domain-containing adaptor-inducing interferon-β ( Trif ) and toll-like receptor 4 adaptor protein ( Tram ) are recruited . These adapter molecules in turn activate other downstream transcriptional gene regulators like activating protein-1 , NFκB and interferon regulatory factors which induce expression of chemokines , proinflammatory cytokines [tumor necrosis factor alpha ( TNF-α ) , IL-6 , IL-1β and IL-12] or costimulatory molecules [25] . The up-regulation of costimulatory molecules is essential for the induction of pathogen-specific adaptive immune responses [26] . Thus , TLRs can activate both the innate and adaptive immune responses . TLR can recognize viral pathogen via a number of different viral ligands . Generally , TLR3 detects double-stranded viral RNA , TLR2 and TLR4 sense the presence of virus via their proteins , TLR7/8 binds single-stranded viral RNA and TLR9 recognizes viral CpG DNA [27] . Among the TLRs , TLR3 and TLR7 have been found to trigger IL-8 production when stimulated by dengue viral RNA [28 , 29] . TLR6 was found to be up-regulated in DV2-infected K562 cells using Human Th1-Th2-Th3 RT2 Profiler PCR arrays in our previous study [30] . Although TLR6 was previously known only to be activated by diacylated lipoprotein of bacteria [31] , recent studies have found that TLR6 can be activated by viruses including hepatitis C virus and respiratory syncytial virus [32 , 33] . Viral infection induces various TLR-mediated innate responses , which subsequently play a pivotal protective or pathogenic role in conjunction with virus-specific adaptive immune responses [34 , 35] . In the current study , dengue virus infection was found to activate and up-regulate TLR2 and TLR6 of human PBMC and DV NS1 protein was shown to be the viral protein responsible . Knockout of TLR6 increased the survivability of mice infected by dengue virus . Prolonged activation of TLR6 by DV NS1 protein during DV infection could be responsible for the lower survivability observed in wild-type mice compared to the TLR6-/- mice . Hence , TLR6 may play an important role in the immunopathogenesis of dengue virus infection .
In our previous study [30] , several genes involved in the TLR6 pathway have been found to be significantly up-regulated during dengue virus infection in K562 cells on day 3 post-infection which include TLR6 , IL-6 , TNF-α and CD80 . TLR6 pathway activation is well-documented to play an important part in activating both the innate and adaptive immunity . Human PBMC were found to express the whole range of human TLRs ( TLR1-10 ) [36] . The expression of TLRs has been found to increase following inflammations and exposure to pathogens or specific ligands [37–40] . The susceptibility of the PBMC to DV2 infection was first determined using plaque assay ( Fig 1A ) . The virus titer peaked on day 2 post-infection ( 3 . 82 Log10PFU/ml ) and decreases from day 3 to day 5 post-infection . The increase in virus titer on day 2 post-infection of PBMC provided evidence of replication of DV2 in PBMC . Next , flow cytometric analyses were performed to determine the expression of TLR6 of mock-infected and DV2-infected PBMC . Gating was used to exclude the cell debris ( Fig 1B ) . PBMC were also stained with anti-CD14 FITC conjugated antibody to serve as a marker for human monocytes [41 , 42] . Monocytes are the main cells in PBMC that express TLR2 and TLR6 [31] . Upon dengue virus infection , higher percentages of TLR6+CD14+ cell population was observed compared to the mock-infected PBMC on day 2 and 3 post-infection ( Figs 1C , 1E , and S1 ) . TLR6 requires heterodimerization with TLR2 to recognize ligand and trigger cytokine production [43–45] . Hence , TLR2 expression was also investigated . TLR2+CD14+ cell population was up-regulated upon DV infection on day 3 post-infection ( Figs 1D , 1F , and S2 ) . CD14+ monocytes expressing TLR2 were reported by Azeredo and colleagues ( 2010 ) to be increased in peripheral blood of dengue patients . In addition , DV2-infected PBMC expressed higher level of TLR6 and TLR2 on day 3 post-infection but not day 1 and day 2 post-infection ( S3 Fig ) . PBMC were also stained for both TLR2 and TLR6 simultaneously for flow cytometric analysis . In addition , the CD3 and CD20 coexpression on PBMC were analyzed as high percentage of CD3+CD20+ cell population could suggest neoplastic transformation . The percentage of PBMC expressing both CD3 and CD20 were 3 . 84% and 3 . 94% which are within the range detected by other research groups using healthy donors [46–48] . The percentages of mock-infected PBMC which were TLR2+ and TLR6+ were lower than the percentages of DV2-infected PBMC which were TLR2+ and TLR6+ ( Fig 1G , 1H and S1 Table ) . The median fluorescence intensity of the TLR2 and TLR6 were also higher for the DV2-infected than the mock-infected ( S1 Table ) . After affirming the up-regulation of TLR2 and TLR6 of PBMC when infected by DV , activation of these receptors during DV infection were investigated by measuring the amount of IL-6 secreted into the extracellular milieu by the DV2-infected PBMC . The amount of IL-6 in the culture media of DV2-infected PBMC increased significantly from day 2 to day 5 post-infection as compared to that of the mock-infected PBMC ( Fig 2A ) . Similarly , the DV2-infected PBMC significantly up-regulated the amount of TNF-α secreted into the extracellular mileu from day 2 to day 4 post-infection , compared to that of the mock-infected PBMC ( Fig 2B ) . UV-inactivated DV did not induce up-regulation of IL-6 ( Fig 2A ) and TNF-α ( Fig 2B ) when added to PBMC culture . This could suggest that viral replication is required for the up-regulation of IL-6 and TNF-α . To determine if the up-regulation of IL-6 and TNF-α detected were contributed by TLR2 and TLR6 activation , TLR2 and TLR6 blocking antibodies were used . Blocking of TLR2 and TLR6 reduced the amount of IL-6 produced by PBMC when stimulated by LPS ( 5 μg/ml ) or MALP-2 ( 50 ng/ml ) , compared to that of the isotype control ( Fig 2C ) . MALP-2 is a 2-kDa synthetic derivative of the macrophage-activating lipopeptide and it is a specific agonist for TLR2 andTLR6 . Blocking of TLR2 and TLR6 also reduced the amount of IL-6 produced by PBMC during dengue virus infection , this suggested that TLR2 and TLR6 are activated during dengue virus infection and this activation led to increase in IL-6 secretion . Similar observation was made for TNF-α production by PBMC ( Fig 2D ) . This suggested that TLR2 and TLR6 are the receptors activated during DV infection to result in the increase in IL-6 and TNF-α expression . To determine if any specific viral protein is responsible for the activation of TLR2 and TLR6 , IL-6 and TNF-α expression by PBMC after treatments with individual viral proteins were assayed . The detection of up-regulation of IL-6 and TNF-α by PBMC would indicate possible activation of receptors by the dengue viral proteins . ELISA was performed to quantify the amount of IL-6 secreted into the supernatant by PBMC after treatment with the individual dengue viral proteins on day 2 post-treatment . Among the dengue viral proteins , DV NS1 protein is the only viral protein which stimulated high amount of IL-6 expression ( 5864 pg/ml ) ( Fig 3A ) . IL-6 expression was slightly down-regulated by dengue envelope protein ( 296 pg/ml ) and NS3 protein ( 297 pg/ml ) compared to His-tag-treated PBMC ( 346 pg/ml ) . The IL-6 level of His-tag-treated PBMC was comparable to that of the untreated , suggesting that His-tag did not trigger IL-6 production and the IL-6 detected in the culture supernatant of the His-tag-treated PBMC was due to basal expression . The IL-6 level of UV-inactivated DV2-treated PBMC was also comparable to that of the untreated . This suggested that non-replicative virus cannot induce IL-6 expression . The positive control , LPS was found to stimulate IL-6 production by PBMC . ELISA was also performed to determine which of the viral protein can induce up-regulation of TNF-α by PBMC . DV NS1 protein is the only viral protein which stimulated high amount of TNF-α expression ( 293 pg/ml ) compared to that of the His-tag-treated PBMC ( 30 pg/ml ) ( Fig 3B ) . Similar to IL-6 , the TNF-α level of His-tag-treated PBMC was comparable to that of the untreated and the TNF-α level of UV-inactivated DV2-treated PBMC was also comparable to the untreated . The positive control , LPS was also found to stimulate TNF-α production by PBMC . The result suggested that DV NS1 protein is the viral protein that stimulates IL-6 and TNF-α production by PBMC during DV infection . Next , lower concentration of DV NS1 protein ( 1 μg/ml ) was used to stimulate PBMC . This concentration of DV NS1 protein is within the concentration range detected in dengue patients ( several nanograms per millilitre to several micrograms per millilitre ) [49] . ELISA was performed to quantify the amount of IL-6 in the supernatants of DV NS1-treated PBMC on day 1 to day 3 post-treatment . DV NS1 protein-treated PBMC produced significantly higher amount of IL-6 compared to that of the His-tag-treated PBMC from day 1 post-treatment ( Fig 3C ) . The up-regulation was faster than that of the DV2-infected PBMC which only produced significantly higher IL-6 from day 2 post-treatment ( Fig 2A ) . The delay observed in the DV2-infected PBMC could be due to time required for DV NS1 protein synthesis during DV replication and secretion . The secreted DV NS1 protein can then be detected by the cell surface receptors , TLR2 and TLR6 . The IL-6 produced by DV NS1 protein-treated PBMC peaked on day 2 post-treatment ( 2917 pg/ml ) . Similarly , the amount of TNF-α produced by DV NS1 protein-treated PBMC was quantified using ELISA . DV NS1 protein-treated PBMC produced significantly higher amount of TNF-α compared to that of the His-tag-treated PBMC from day 1 post-treatment ( Fig 3D ) . The amount of TNF-α produced by DV NS1 protein-treated PBMC peaked on day 1 post-treatment ( 226 pg/ml ) . The amount of TNF-α decreased from day 2 to day 3 . To determine if the IL-6 production by PBMC upon DV NS1 protein stimulation is through TLR2 and TLR6 , TLR2 and TLR6 neutralizing antibodies were used . The specificity of TLR2 and TLR6 blocking antibodies were tested using TLR4 specific ligand , ultrapure LPS ( S4 Fig ) . TLR2 and TLR6 blocking antibodies did not affect TLR4 . TLR2 and TLR6 of PBMC were blocked by the neutralizing antibodies prior to addition of DV NS1 protein into the PBMC culture ( 1 μg/ml ) . The supernatant of the treated PBMC were collected on day 1 post-treatment and IL-6 was quantified using ELISA . Day 1 was chosen as the time point as IL-6 was found to be significantly up-regulated from day 1 post-treatment in Fig 3C . With both TLR2 and TLR6 blocked , IL-6 secreted by DV NS1 protein-treated PBMC was significantly reduced compared to that of the isotype control ( Fig 3E ) . With only TLR6 blocked , IL-6 secreted by DV NS1 protein-treated PBMC was comparable to that of both TLR2 and TLR6 blocked ( Fig 3E ) . Therefore , DV NS1 protein stimulation of IL-6 requires both TLR2 and TLR6 . The stimulation is inhibited when one of the receptors is blocked . With only TLR2 blocked , IL-6 secreted by DV NS1 protein-treated PBMC was significantly reduced and surprisingly lower than that of the His-tag-treated PBMC ( Fig 3E ) . High amount of TLR2 neutralizing antibody may have some effect on the basal IL-6 expression of PBMC . TLR2 neutralizing antibody was found to be more effective than TLR6 neutralizing antibody . The expected level of IL-6/TNF-α for DV NS1 protein-treated PBMC with 500 ng/ml of TLR2 and 500 ng/ml of TLR6 neutralizing antibodies should be between the level of IL-6/TNF-α for DV NS1 protein-treated PBMC with 1000 ng/ml of TLR2 only and those with 1000 ng/ml of TLR6 only . The presence of the more efficient TLR2 blocking antibodies in the treatment group with both blocking antibodies should be able to more efficiently block the TLR2/6 pathway compared with the treatment with only TLR6 blocking antibody . However , the observation was not the case . The expected result would only happen if the TLR2 and TLR6 antibodies can sterically hinder the binding of each other to prevent one TLR2/6 complex from binding both TLR2 and TLR6 antibodies at the same time . The observed result suggested that the two antibodies did not sterically hinder each other . Thus , one TLR2 and one TLR6 antibodies can bind and inhibit the same TLR2/6 complex , an inhibition which can be achieved initially with just either one TLR antibody . In summary , DV NS1 protein-treated PBMC which were also treated with TLR2 or TLR6 neutralizing antibodies or both secreted less IL-6 compared to the isotype control . Together , these data implied that TLR2 and TLR6 are the receptors activated by DV NS1 protein . Similar to what was observed for IL-6 , the TNF-α amount secreted by His-tag-treated PBMC in general , was not affected by the neutralizing antibodies ( Fig 3F ) . With both TLR2 and TLR6 blocked , TNF-α secreted by DV NS1 protein-treated PBMC was significantly reduced compared to that of the isotype control . With only TLR6 blocked , TNF-α secreted by DV NS1 protein-treated PBMC was comparable to that of both TLR2 and TLR6 blocked . With only TLR2 blocked , TNF-α secreted by DV NS1 protein-treated PBMC was significantly reduced . With 1000 ng/ml of TLR2 neutralizing antibody , the basal TNF-α expression of His-tag-treated PBMC was affected , as shown by the lower TNF-α level of the TLR2 blocked His-tag-treated PBMC compared to that of the isotype control His-tag-treated PBMC . This may suggest that TLR2 activation partially contributed to the basal expression of IL-6 and TNF-α detected in our PBMC culture . In summary , PBMC which were treated with TLR2 and/or TLR6 neutralizing antibodies secreted less TNF-α compared to the isotype control . Together , the data implied that TLR2 and TLR6 are the receptors activated by DV NS1 protein . In addition , SEAP reporter assay was used to further confirm if DV NS1 protein is activating TLR2 and TLR6 using the HEK 293 cells . HEK 293 cell line which naturally does not possess many of the TLRs was also used for the reporter assay . HEK 293 cells have good transfection efficiency to allow expression of desired TLR and the SEAP reporter plasmid for investigating specific TLR ligand . HEK 293 cells were found to express low level of endogenous TLR6 but not TLR2 [50 , 51] . The reports of low level of expression of TLR6 and no expression of TLR2 in HEK 293 cells were further confirmed in our western blot results ( S5 Fig ) . LPS and MALP-2 were used as positive control . For HEK 293 cells transfected with only SEAP reporter plasmid , the SEAP secretion by HEK 293 cells treated with DV NS1 protein and the positive controls were not significantly different from the negative controls ( untreated and His-tag-treated HEK 293 cells ) ( Fig 3G ) . This suggested that DV NS1 protein , LPS and MALP-2 cannot stimulate NFκB activation in the absence of TLR2 . DV2-infected HEK 293 cells produced significantly higher SEAP than mock-infected HEK 293 cells . This suggested that DV2-infection can trigger NFκB activation through pathway independent of TLR2 . For HEK 293 cells transfected with SEAP reporter , TLR2 and TLR6 expression plasmids , the SEAP secretion by HEK 293 cells treated with DV NS1 protein and the positive controls were significantly different from the negative controls from day 1 post-treatment ( Fig 3H ) . The result suggested that activation of NFκB by DV NS1 protein is dependent on both TLR2 and TLR6 . DV2-infection was found to up-regulate TLR6 in PBMC ( Fig 1E and 1H ) . To determine if this up-regulation is contributed by DV NS1 protein effect on the cells , Western blot analyses were used . PBMC were treated with His-tag ( 1 μg/ml ) , DV NS1 protein ( 1 μg/ml ) , LPS ( 5 μg/ml ) , mock-infected or DV2-infected ( M . O . I of 10 ) . TLR6 bands of DV2-infected , DV NS1 protein-treated and LPS-treated PBMC were of higher intensity than those of mock-infected and His-tag-treated PBMC ( Fig 4A ) . The relative density of the TLR6 bands normalized against the actin bands was plotted on a graph ( Fig 4B ) . The result suggested that DV NS1 protein can stimulate up-regulation of TLR6 in PBMC . Similarly , TLR2 bands of DV2-infected , DV NS1 protein-treated and LPS-treated PBMC were of higher intensity than those of mock-infected and His-tag-treated PBMC ( Fig 4C ) . The relative density of the TLR2 bands normalized against the actin bands was plotted on a graph ( Fig 4D ) . The results suggested that DV NS1 protein can stimulate up-regulation of TLR2 and TLR6 in PBMC . TLR2 and TLR6 expression on PBMC were further investigated using immunofluorescence analyses . Mock-infected and DV2-infected PBMC were harvested on day 3 post-infection and stained for TLR2/TLR6 and CD14 . The staining of untreated PBMC ( Fig 4E and 4J ) were comparable to that of the mock-infected ( Fig 4F & 4K ) and His-tag-treated PBMC ( Fig 4H and 4M ) . Similar to the results obtained in flow cytometric and western blot analyses , TLR2/TLR6 was up-regulated in DV2-infected PBMC ( Fig 4G and 4L ) , indicated by the denser red spots compared to the mock-infected PBMC ( Fig 4F and 4K ) . TLR2/TLR6 was also up-regulated in DV NS1 protein-treated PBMC ( Fig 4I and 4N ) compared to the His-tag-treated PBMC ( Fig 4H and 4M ) . Colocalization of both TLR2 and TLR6 with CD14 were observed for untreated , mock-infected , DV2-infected , His-tag-treated and DV NS1 protein-treated PBMC ( yellow stains ) . Hence , the colocalization of the receptors could be independent of infection or DV NS1 protein stimulation . It was reported that TLR2 and TLR6 heterodimers pre-exist and are not induced by ligand [45] . The activation of TLR2 and TLR6 could be a double-edged sword that is both beneficial and detrimental to the host . To assess the potential role of the activation of TLR2 and TLR6 plays during dengue virus infection , the use of cell model is not sufficient , an animal model is required . Wild-type and TLR6 knockout ( TLR6-/- ) C57BL/6 mice were used in this part of the study . In order to determine if TLR6 activation during dengue virus infection contributes to the pathogenesis of the disease , wild-type and TLR6-/- mice were injected with 2 . 7 x 108 PFU of DV2 on day 1–2 day-old ( Fig 5A ) . The survival rate of the DV2-infected wild-type mice was 61 . 4% at the end point of the study . The survival rate of the TLR6-/- DV2-infected mice was 83 . 0% at the end point of the study . Knockout of TLR6 increased the survival rate of the mice at the end point of the study by 21 . 6% , suggesting that activation of TLR6 may contribute to the pathogenesis of the disease , leading to higher fatality observed in the DV2-infected wild-type mouse population . Using Log-rank test , DV2-infected wild-type mice survival curve was found to be statistically different from DV2-infected TLR6-/- mice . Hence , knockout of TLR6 significantly enhanced the survival rate of the DV2-infected mice . Next , we investigated what could have resulted in the difference in survival rate of wild-type and TLR6-/- mice . Pups which were 1–2 day-old were injected with 2 . 7 x 108 PFU of DV2 and quantified for virus titer in the sera and livers . DV2 were detected in all the DV2-infected pups from day 1 to day 2 post-infection . The average virus titer detected in the sera of the DV2-infected wild-type mice on day 1 was 1 . 51 x 105 PFU/ml while that on day 2 was 9 . 17 x 102 PFU/ml and that on day 3 was 1 . 81 x 102 PFU/ml ( Fig 5B and Table 1 ) . This suggested that the pups were susceptible to dengue virus infection . 1–2 day-old TLR6-/- mice were also infected in the same way as the wild-type . Virus in the sera of TLR6-/- mice was also quantified . The average virus titer detected in the sera of the DV2-infected TLR6-/- mice was 2 . 73 x 106 PFU/ml on day 1 while that on day 2 was 2 . 40 x 103 PFU/ml and that on day 3 was 2 . 54 x 101 PFU/ml ( Fig 5B ) . Comparing the virus titers obtained in the sera of DV2-infected wild-type and TLR6-/- mice , virus titers were not statistically significantly different . This suggested similar susceptibility of wild-type and TLR6-/- mice to DV2 . Viremia persisted in both wild-type and TLR6-/- mice till day 3 . By day 4 post-infection , virus can no longer be detected in the sera of mice except for one TLR6-/- mice whose serum detected presence of DV2 on day 5 post-infection . Virus titers in the livers of wild-type and TLR6-/- mice were also quantified using plaque assay ( Fig 5C ) . Unlike what was observed for the sera , DV2 was not detected in every liver of the DV2-infected mice on day 1 and 2 post-infection . On the contrary , DV2 were detected in the livers of DV2-infected mice more frequently on day 4 and day 5 post-infection compared to that of the sera . This may suggest that though not all the DV2 can establish infection in the liver organ , for those that established , it can persist longer in the liver than in the sera . The sera and livers of both the wild-type and TLR6-/- mock-infected mice were detected to be absent of DV2 . DV2-infected mice developed some abnormal signs like enlarged belly , hind limb paralysis , moribundity and death ( Table 2 ) . Hindlimb paralysis was also observed in DV2-infected mice . Symptoms of paralysis of extremities which has been observed in some dengue patients were also observed in the murine model [52] . However , such occurrences were rare . From the observations of the mice on a daily basis , the occurrence of paralysis was observed on day 10–14 post-infection . Some of the DV2-infected mice were found to succumb to the infection . No viable virus was detected in the tissues of the dead mice which could be due to decomposition . Blood of the dead mice could not be harvested due to the clotting of the blood . High virus titers were detected in the brain , liver and limbs of the moribund mice , the virus titers were higher than the average virus titers detected in the brain , liver and limbs of the asymptomatic DV2-infected mice ( Table 2 ) . However , no virus was detected in the sera of the moribund mice which was similar to what was observed for the asymptomatic DV2-infected mice on day 5 post-infection . The amount of IL-6 in the sera of one of the moribund mice was assayed and high amount of IL-6 was detected ( 2690 . 5 pg/ml ) ( Table 2 ) . Paraplegia was observed in some of the DV2-infected mice but not for any of the mock-infected mice . As paraplegia was observed in the DV2-infected mice , hindlimbs of the mice were also harvested and quantify for DV2 titer using plaque assay ( Fig 5D ) . Similar to what was observed for the DV2 titers of the liver , DV2 was also not detected in the limbs of every DV2-infected mouse on day 1 and day 2 post-infection and virus was detected on day 4 , day 5 and day 21 post-infection . No virus was detected in the limbs of mock-infected wild-type and TLR6-/- mice . Paralysis of the limb could be due to presence of virus in the central nervous system [53] . In view of that , the brains of DV2-infected wild-type and TLR6-/- mice were harvested . DV2 was able to gain entry into the brain and persisted there in both the wild-type and TLR6-/- mice ( Fig 5E ) . DV2 was able to replicate in the brain of TLR6-/- mice from day 1 post-infection while DV2 was only detected in the brain of DV2-infected wild-type mice from day 3 post-infection . DV2 was only detected from day 3 post-infection in the brains of wild-type mice . DV2 can still be detected at the endpoint of the experiment in both wild-type and TLR6-/- mice . No virus was detected in the brain of the mock-infected mice . When the virus titers of mice which displayed lower limb paralysis were titered using plaque assay , it was found that most of the viruses were localized in the brain rather than the limb , liver or the serum ( Table 2 ) . This suggested that DV2 persisted in the brains of these mice and affected the central nervous system , leading to the paralysis . High virus titers were found in the homogenized brains of the mice which displayed symptoms of paralysis , much higher than the asymptomatic mice . One of the mice was found to have only one limb paralyzed , the virus titer in each of the limb was titered separately to determine if there would be a difference in virus titers in the two limbs . The virus titer in the paralyzed limb ( 1 . 4 x 103 PFU/g ) was comparable to that of the normal limb ( 4 . 0 x 103 PFU/g ) , suggesting that paralysis was not due to virus replication in the limb ( Table 2 ) . Moreover , some of the mice which exhibited limb paralysis were not detected with DV in the limbs , further substantiating that paralysis was not due to DV in the limbs ( Table 2 ) . It has been shown using the PBMC cell model that DV2 infection up-regulates IL-6 expression . IL-6 expression in sera of DV2-infected mice was investigated using ELISA . It was noticed that not all the mice up-regulated IL-6 expression upon dengue virus infection ( Fig 6A ) . Some of the mice , both DV2-infected wild-type and TLR6-/- , remained unresponsive to the infection . The amount of IL-6 in the sera of those mice was comparable to that of the mock-infected mice . Among those that responded , DV2-infected wild-type mice secreted higher amount of IL-6 compared to that of the DV2-infected TLR6-/- mice , indicating that TLR6 activation contributed to the IL-6 expression during dengue virus infection . This observation is similar to what was seen in the human PBMC cell model . In addition , it was noticed that IL-6 up-regulation in the sera of DV2-infected TLR6-/- mice subsided by day 5 post-infection while that of responsive wild-type mice remained up-regulated . In general , there was an increasing trend observed in the IL-6 expression of those responsive DV2-infected wild-type mice from day 1 to day 5 post-infection . The amount of TNF-α in the sera of DV2-infected mice was also determined using ELISA . TNF-α expression in sera of DV2-infected mice was similar to IL-6 expression ( Fig 6B ) . Among those that responded , DV2-infected wild-type mice secreted higher amount of TNF-α compared to that of the DV2-infected TLR6-/- mice , indicating that TLR6 activation contributed to the TNF-α expression during dengue virus infection . DV NS1 protein was found to be the viral protein responsible for activating TLR2 and TLR6 using the PBMC model . As DV NS1 protein could be the viral protein responsible for the IL-6 and TNF-α up-regulation in the mice as well , the presence of DV NS1 protein in the sera of mice after intraperitoneal injection of DV2 was determined using Bio-Rad Platelia Dengue NS1 Antigen detection kit . DV NS1 protein persisted in the sera of mice after injection of DV2 for both wild-type and TLR6-/- mice ( Fig 6C and 6D ) . In general for both wild-type and TLR6-/- mice , the DV NS1 protein level started to decrease from day 4 post-infection and on day 5 , DV NS1 protein level in one of the wild-type mice fell close to the relative OD of the mock-infected mice . The amount of DV NS1 protein in the sera of the DV2-infected wild-type and TLR6-/- mice was comparable . This could be due to the comparable virus titers in the DV2-infected wild-type and TLR6-/- mice , suggesting comparable replication level and thus similar DV NS1 protein production . Next , we determined if TLR6 of the mice was activated by DV NS1 protein during DV infection . The effect of DV NS1 protein on IL-6 expression of murine peritoneal macrophages was investigated . Similar to what was observed for human PBMC cell model , without the presence of TLR6 , DV2-infected murine peritoneal macrophages secreted significantly lesser amount of IL-6 ( Fig 7A ) . The amount of IL-6 produced by DV NS1 protein-treated wild-type murine peritoneal macrophages was significantly much more than DV NS1 protein-treated TLR6-/- murine peritoneal macrophages . The level of IL-6 produced by DV NS1 protein-treated TLR6-/- murine peritoneal macrophages was comparable to that produced by the mock-infected TLR6-/- murine peritoneal macrophages . In the absence of TLR6 , DV NS1 protein cannot stimulate the production of IL-6 by murine peritoneal macrophages . The amount of IL-6 produced by DV2-infected TLR6-/- murine peritoneal macrophages was higher than that of the mock-infected , suggesting that the stimulation by DV NS1 protein only contributed partially to the amount of IL-6 detected in the DV2 infection . In addition , the effect of MALP-2 on the secretion of IL-6 by the murine peritoneal macrophages was eliminated in the absence of TLR6 . Similar to IL-6 , TNF-α production by the murine peritoneal macrophages upon stimulation with DV NS1 protein was significantly reduced in the absence of TLR6 ( Fig 7B ) . Ultrapure LPS , a TLR4-specific agonist can induce IL-6 and TNF-α production by murine peritoneal macrophages of both wild-type and TLR6 knockout mice . These results suggested that TLR6 of mice can be activated by DV NS1 protein . As DV NS1 protein can induce IL-6 and TNF-α production by the murine peritoneal macrophages , the effect of introducing DV NS1 protein into the mice was investigated . Wild-type and TLR6-/- mice were injected with 20 μg of DV NS1 protein via intraperitoneal injection . The control mice were injected with 20 μg of His-tag protein . The survivability of the DV NS1 protein-treated and His-tag-treated mice were monitored for 7 days post-treatment ( Fig 7C ) . At the endpoint , 94 . 4% of the His-tag-treated wild-type mice survived the treatment while only 27 . 8% of the DV NS1 protein-treated wild-type mice survived . At the endpoint , 100% of the His-tag-treated TLR6-/- mice survived the treatment while 88 . 9% of the DV NS1 protein-treated TLR6-/- mice survived . The survival rate of the DV NS1 protein-treated wild-type and TLR6-/- mice were significantly different . The knockout of TLR6 increased the survivability of mice after treatment with DV NS1 protein . IL-6 ( Fig 7D ) and TNF-α ( Fig 7E ) of the treated wild-type mice were assayed . Similar to DV-infected mice , IL-6 and TNF-α in the DV NS1 protein-treated wild-type mice were found to be significantly higher than that of the His-tag-treated wild-type mice .
Among the PBMC , monocytes have been implicated in both the protection and immunopathogenesis of dengue [54] . Depletion of monocytes and macrophages in mice using clodronate-loaded liposomes resulted in 10-fold higher systemic DV titers , highlighting the important roles of monocytes and macrophages in DV control during an infection [55] . Ironically , monocytes were found to be the cells among PBMC that supported DV infection and the cells responsible for antibody-dependent enhancement of DV infection [56 , 57] . Although other cell types in the PBMC like T cells and B cells were found to be less susceptible to DV infection , they are likely to play important roles during DV infection [56] . There are evidences that cell-cell cross-talks between various immune cells in PBMC affect cytokine production during an infection [58 , 59] . Hence , PBMC culture would be a more representative and physiological model of infection than using monocytes alone . In the recent years , it has become evident that PRRs play a major role in infectious and even in non-infectious diseases [60 , 61] . One family of PRRs , the TLR family has emerged as a key component of the innate immune system and it can activate signals which are crucial for the initiation of adaptive immune responses [61] . Studies in recent years have shown the presence of mRNA and protein expression of TLRs in various immune and non-immune cells [62–64] . In our study , TLR2 and TLR6 were found to be up-regulated in PBMC upon DV infection . This up-regulation suggested the possible involvement of TLR2 and TLR6 in dengue virus infection . TLR6 was found to be up-regulated by PBMC on day 3 post-infection ( Fig 1C ) . As TLR2 is partner of TLR6 , its expression by PBMC during dengue virus infection was also investigated . Like what was observed for TLR6 , TLR2 was found to be up-regulated by PBMC on day 3 post-infection ( Fig 1D ) . The mechanism of TLR2 regulation has not been fully elucidated [65–68] . It was reported that chromatin remodelling involving DNase I and restriction enzyme occurs at TLR2 promoter region following infection [67] . This remodelling of chromatin increases accessibility of transcription factors resulting in greater transcription of TLR2 [67] . In addition , two pathways were found to be important for TLR2 regulation . IKKβ-IκBα-dependent NFκB pathway activation and MKK3/6-p38α/β pathway inhibition are essential for TLR2 expression [65] . One study supported the involvement of NFκB in TLR2 expression . Pyrrolidine dithiocarbamate ( PDTC ) , a pharmacologic inhibitor of NFκB was shown to prevent the up-regulation of TLR2 by TLR2 and TLR4 agonist [66] . On the other hand , the up-regulation of TLR6 is not well-studied and remained unclear . Upon dengue virus infection , PBMC secretes both IL-6 and TNF-α ( Fig 2A and 2B ) . This is consistent with what was observed in the sera of dengue patients . Dengue patients’ sera have been found to contain high level of IL-6 [20 , 69 , 70] . Similarly , TNF-α level was also increased in the sera of dengue patients [20 , 69 , 70] . Similar to monocytes , IL-6 and TNF-α are implicated in both the protection and immunopathogenesis of dengue virus infection [71 , 72] . Upon sensing the presence of foreign microbes through recognition of PAMPs , biological mediators like IL-6 and TNF-α are released . Although these mediators initiate and regulate the inflammatory response and adaptive immune response to eliminate foreign microbes , they have also been found to be involved in lethal manifestations like septic shock syndrome , vascular leakage and cachexia , resulting from disease , infection or injury [73–75] . This provided evidence that the manifestation of illness could also be caused by the host own immune system , not necessarily by exogenous pathogens . It was noticed that IL-6 production by the DV2-infected PBMC ( Fig 2A ) was lower than that of the antibody-treated DV2-infected PBMC ( Fig 2C ) . This difference could be due to the presence of antibodies which are originated from rabbit and mouse . The presence of foreign proteins can trigger immune response . Another possibility contributing to the difference in IL-6 production observed could be donor variability . The PBMC used for the two set of experiments were from different donors . The dengue viral protein responsible for the activation of TLR6 and TLR2 were first screened using ELISA . Among the 10 dengue viral proteins , only DV NS1 protein up-regulated both IL-6 and TNF-α expression of PBMC ( Fig 3A and 3B ) , making it the most likely candidate . DV NS1 protein was documented to be secreted by infected cells and the presence of DV NS1 protein was detected in the sera of patients [76–78] . Moreover , the amount of DV NS1 protein in the sera of patients was found to correlate with the severity of the dengue disease [76] . This correlation suggested that DV NS1 protein plays an important role in the pathogenesis of dengue disease . In addition , DV replication was found to be critical for the up-regulation of IL-6 and TNF-α during DV infection as UV-inactivated DV did not induce the up-regulation . DV NS1 protein being a non-structural protein requires DV replication to be synthesized . Hence , DV NS1 protein being the dengue viral protein fits the results we obtained using the PBMC in vitro cell model . In this study , we have developed a murine model for dengue virus infection using 1–2 day old C57BL/6 mouse . Although consistent viremia was detected in the mice infected at 1–2 day old for both wild-type and TLR6-/- mice , the virus titers were observed to decrease as the day of infection progressed ( Fig 5B ) . This suggested that the DV2-infected mice were able to mount an effective immune response to fight the infection . The fast clearance of DV may suggest that the innate immunity is sufficient for the clearing . Published studies have demonstrated that innate immunity was sufficient to clear DV infection using human cell-engrafted scid mice [79 , 80] . Similar trend was observed for the virus titers in the livers of the DV2-infected mice for both wild-type and TLR6-/- mice . However , the virus titers of the livers were not as consistent compared to that of the sera , only a few of the livers of DV2-infected mice were detected to contain infectious DV2 ( Fig 5C ) . A point to be taken into consideration is that the DV detected in the liver could be contributed partially by the virus found in the blood . However , the blood contamination has been minimized as the blood of the pups was harvested before the harvest of the liver . Hence , the liver should contain minimal amount of blood when harvested . The observation that virus was detected in all the serum samples but not in all the liver samples of infected pups on day 1 and day 2 post-infection showed that the above mentioned contamination was kept to a minimum . One clinical sign observed in dengue patients and the murine model is paralysis of extremities [52] . The occurrence of paralysis was observed to be between day 10 to day 14 of infection ( Table 2 ) . Paralegia was not unique to the murine model used in our studies . Paralegia was also observed in other murine models of DV infection and the time of development was similar [81 , 82] . AG129 mice were reported to develop paralysis within 7 to 14 days post-infection [82] . The development of paralysis was faster than the wild-type counterpart of the mice and thus the authors attributed the difference to the AG129’s deficiency in IFN receptors . Among the asymptomatic mice , virus was detected in the brain as early as day 1 post-infection for the DV2-infected TLR6-/- mice and the virus persisted in the brains of the mice till the endpoint of the experiment . This suggested that virus clearance is least efficient in the brains of the mice . Similar trend was observed for AG129 murine model [82] . AG129 mice harboured DV in the extraneural tissues and neural tissues on day 3 post-infection , with higher viral titers in the extraneutral sites than the neural sites . By day 7 post-infection , virus was only detected in the neural tissues . This result supported our data ( Fig 5B–5E ) . It was noticed that the viral loads in the brain of the asymptomatic mice ( < 104 PFU/g ) were much lower than that of the mice displaying hindlimb paralysis ( 2 . 8 x 104 PFU/g , 5 . 2 x 105 PFU/g , 8 . 2 x 105 PFU/g , 7 . 1 x 105 PFU/g ) ( Table 2 ) . Hence , extensive replication of DV in the brain of the mice could have resulted in the paralysis observed in the mice . Similarly , AG129 mice with paralysis were reported to carry high viral loads in the brain [82] . The viral loads reported were comparable to ours , between 104 to 106 PFU/g ( Table 2 ) . Mice which were not sacrificed but were monitored for disease progression , recovered two days after the onset of paralysis . The brain , liver and limb of one of the mice were harvested and quantified for virus . No virus was detected in the liver and limbs of the recovered mouse while virus was still detected in the brain . The viral load ( 2 . 12 x 104 PFU/g ) was still higher than that of the asymptomatic mice but lower than that of the symptomatic mice ( Table 2 and Fig 5E ) . This suggested that viral load in the brains of the mice can be controlled by the mouse immune system even though the clearing of the virus in the brain was not as efficient as compared to the sera , livers and limbs . The microglial cells are the main cell type of the innate immune system in the brain [83] . The microgial cells also express TLRs and produce pro-inflammatory mediators in response to TLR ligands [84 , 85] . Human microgial cells express high levels of TLR2 and TLR3 , moderate levels of TLR4 , TLR5 , TLR6 , TLR7 and TLR8 but low level of TLR9 [86] . Mouse microgial cells express similar TLRs except for TLR5 [87] . As there is no lymphatic system in the brain for immune cells to migrate through and microglial cells are poor antigen-presenting cells , the immune responses in the brain are limited [83] . This may explain why the virus can persist in the brain for a longer time in comparison to other organs and sera . As human IL-6 and TNF-α were detected in our human cell-based model upon DV infection , murine IL-6 and TNF-α were assayed for in the sera of the DV2-infected mice . Unlike what was observed for the cell-based model , IL-6 and TNF-α were only detected to be up-regulated in the sera of some of the DV2-infected mice ( Fig 6A and 6B ) . For both wild-type and TLR6-/- mice , the level of IL-6 and TNF-α detected in some of the DV2-infected mice were comparable to that of the mock-infected mice . This suggested only some of the DV2-infected mice responded to the DV-infection by up-regulation of IL-6 and TNF-α . This high variability of hyporesponsiveness of young mice to stimulation was also documented by other research groups [88–90] . Among the responsive mice , the IL-6 and TNF-α of the DV2-infected wild-type mice were higher than the DV2-infected TLR6-/- mice and the up-regulation lasted for a longer time . Knockout of TLR6 reduced IL-6 and TNF-α production , suggesting TLR6 activation contributed to IL-6 and TNF-α production in mice during DV infection . As DV NS1 protein was found to be the viral protein that is activating TLR6 , the duration in which DV NS1 protein remained in circulation in the mice injected with DV was investigated . The presence of DV NS1 protein was detected in all the sera of DV2-infected wild-type and TLR6-/- mice using Bio-rad platelia kit DV NS1 antigen detection kit from day 1 to day 5 ( Fig 6C and 6D ) . The level of DV NS1 protein detected from the DV2-infected wild-type mice was not significantly different from that of the DV2-infected TLR6-/- mice . This was probably a consequence of similar virus titers in the sera of the DV2-infected wild-type and TLR6-/- mice . DV NS1 protein remained in circulation in the mice longer than DV ( Figs 5B , 6C and 6D ) . DV NS1 protein remained detectable in the sera of DV2-infected mice on day 5 post-infection while DV were no longer detected in most of the sera by day 4 post-infection . Slower rate of DV NS1 protein clearance compared with DV from the plasma of dengue patients were also reported [76] . DV NS1 protein can be detected for a longer period of time in the sera of dengue patients compared to DV [91] . The presence of DV NS1 protein level in the mice contributes to IL-6 and TNF-α level in the mice . DV NS1 protein level remained relatively high from day 1 to day 5 post-infection . This could be the reason why wild-type mice still observed high IL-6 and TNF-α expression even when virus titer dropped to 0 PFU/ml in the sera for most of the mice while IL-6 and TNF-α of TLR6-/- mice dropped after the elimination of DV from the sera ( Fig 6A and 6B ) . This may suggest that IL-6 and TNF-α in the sera at the later part of infection was mostly contributed by DV NS1 protein activating TLR6 . The Kaplan-meier survival plot was used to estimate the survival of the wild-type and TLR6-/- mice population after DV infection for over 21 days . The survival plots of the DV2-infected wild-type and TLR6-/- mice intercept , indicating that the probability of survival for one population of the mice were higher for a period of time during DV infection but became lower compared to the other population as the infection progresses ( Fig 5A ) . The DV2-infected TLR6-/- mice have a lower survival probability at earlier time points and the DV2-infected wild-type mice have a lower survival probability at later time points . This could be due to the replication of DV in the brain of the TLR6-/- mice . Viral loads were detected in the brain of the TLR6-/- mice on day 1 post-infection but not for wild-type mice . This suggested that the brains of pups were more vulnerable to DV infection in the absence of TLR6 . Sensing of DV through other PRRs may be more limited for the microgial cells during the early development of the mice and thus TLR6 appeared to play a more critical role . This vulnerability decreased with age as TLR6-/- mice suffering from paraplegia were found to be able to recover from it . The overall survival probability of wild-type mice during DV2 infection was lower than TLR6-/- mice . In the absence of TLR6 activation , the overall survival probability of the mice to DV infection increased . This suggested the involvement of TLR6 in the immunopathogenesis of DV infection . Activation of TLR2 and TLR6 by DV NS1 protein up-regulates IL-6 and TNF-α . High expression of IL-6 and TNF-α have been shown to be associated with fatality of mice [92 , 93] . Prolonged up-regulation of IL-6 and TNF-α due to stimulation of TLR6 by DV NS1 protein may be the cause of death for the wild-type mice . Prolonged up-regulation of IL-6 and TNF-α may increase the risk of the mice developing complications from the proinflammatory cytokines . Murine peritoneal macrophages from 4-week old wild-type and TLR6-/- C57BL/6 mice were used to further verify the involvement of TLR6 in IL-6 and TNF-α expression during DV infection . Murine peritoneal macrophages were widely used to elucidate TLR ligands and TLR6 ligands were among those tested [32 , 33 , 94 , 95] . MALP-2 was also used to further confirm the functionality of TLR6 of the wild-type and TLR6-/- murine peritoneal macrophages . Wild-type murine peritoneal macrophages up-regulated both IL-6 and TNF-α upon stimulation by MALP-2 while TLR6-/- murine peritoneal macrophages were non-responsive . During DV infection , TLR6-/- murine peritoneal macrophages produced significantly less IL-6 and TNF-α compared to that of the wild-type murine peritoneal macrophages . This corroborates the result obtained from the sera of the mice . Knockout of TLR6 did not completely abrogate IL-6 and TNF-α up-regulation during DV infection , suggesting TLR6 activation only partially contributed to the IL-6 and TNF-α detected during DV infection . The redundancy of pathogen sensing pathways was documented [96] . One pathogen can be recognized by multiple PRRs and the signalling pathways activated downstream of TLRs have redundancy [97] . The synergistic effect of activating more than one PRR has also been reported . Synergy between TLR2 and TLR4 can potentiate the up-regulation of cytokine production [98] . This observation may also provide some explanation on why wild-type and TLR6-/- mice did not have significant difference in virus detected in the sera of the mice . Knockout of TLR6 did not prevent the activation of macrophages . The macrophages can still sense the presence of pathogen through other PRRs and gets activated to produce IL-6 and TNF-α . Similar to our human PBMC model , DV NS1 protein stimulated the production of IL-6 and TNF-α by wild-type murine peritoneal macrophages . TLR6-/- murine peritoneal macrophages were unresponsive to DV NS1 protein stimulation , suggesting DV NS1 protein activates TLR6 of murine peritoneal macrophages to produce IL-6 and TNF-α . Using TLR6-/- murine cellular model , TLR2 and 6 antibody blocking assay and SEAP reporter assay , DV NS1 protein has been shown to be the viral protein responsible for TLR2/6 stimulation during DV infection and both receptors are required . However , whether the stimulation is direct or indirect has not been elucidated . Studies have demonstrated that host-derived molecules may also stimulate TLR signalling [99] . Hence , there is a possibility that DV NS1 protein may stimulate the release of endogenous ligands to trigger TLR2 and TLR6 activation rather than binding to TLR2/6 complex itself It was found that mice injected with DV NS1 protein alone without DV can induce up-regulation of IL-6 and TNF-α ( Fig 7D and 7E ) . Hence , the result suggested that DV NS1 protein contributed to the up-regulation of IL-6 and TNF-α production observed in DV2-infected wild-type mice ( Fig 6A and 6B ) . In addition , results from the murine peritoneal macrophages suggested that DV NS1 protein stimulates IL-6 and TNF-α production primarily through TLR6 . Together , these results suggest that the higher survivability of the TLR6-/- mice during DV infection could be due to their non-responsiveness to DV NS1 protein . The survival rate of the DV NS1 protein-treated wild-type mice ( 27 . 8% ) was lower than that of the DV-infected wild-type mice ( 61 . 4% ) . This could be due to the amount of DV NS1 protein injected was more than what was produced in the mice by the DV infection . It was shown in our studies that DV NS1 protein is able to activate TLR2 and TLR6 to induce up-regulation of IL-6 and TNF-α . This production of cytokines could be the cause of the development of dengue hemorrhagic fever as cytokines were found to play important roles in several viral hemorrhagic fevers [100 , 101] . Furthermore , cytokines were found to have prognostic value in DV infection in other studies [20 , 102 , 103] . All these findings suggest that a possible treatment for dengue would be to control the proinflammatory cytokine production during DV infection . It was reported that when an immunomodulator , tetracycline hydrochloride was administered into Tick-Borne Encephalitis virus patients , the concentration of IL-6 and TNF-α were reduced and the patients have a faster clinical recovery [101] . This study suggested that modulation of the amount of IL-6 and TNF-α can have a positive effect on patients with viral hemorrhagic fevers . Since TLR6 activation during DV infection can contribute to the production of proinflammatory cytokines , immunomodulation approaches that target TLR6 can reduce the proinflammatory cytokines . The reduction of proinflammatory cytokines can potentially prevent the progression of the disease to the more severe forms . Recent studies have shown that TLRs may be responsible for the manifestation of autoimmune diseases , allergy , cancer , infectious diseases and sepsis [104 , 105] . In our study , the activation of TLR6 decreases the survival of mice during DV infection , suggesting a role for TLR6 in the immunopathogenesis of DV infection . The roles of TLRs in human diseases are not fully understood but there are in vitro and animal model data to support TLR roles in disease initiation and progression [97 , 106] . There is a growing interest in exploring TLRs as the therapeutic targets for these diseases [97 , 104–107] . It was proposed that inhibition of TLR function might limit disease pathogenesis in conditions such as sepsis , rheumatoid arthritis and systemic lupus erythematosus , in which the immune system is inappropriately overactive [97 , 104 , 106] . Antimalarial drugs such as hydroxychloroquine which act as a TLR7 , TLR8 and TLR9 antagonist are used for the treatments of rheumatoid arthritis and systemic lupus erythematosus [106 , 108] . TLR2 has been implicated in the pathogenesis of systemic lupus erythematosus , diabetes , Alzheimer’s disease [109 , 110] . A TLR2-specific monoclonal antibody , OPN-305 which inhibits TLR2-mediated proinflammatory cytokine production is being tested for the potential treatment of inflammatory diseases [106] . Drugs or antibodies that target TLR2 are likely to have an effect on TLR2 and TLR6 signaling as shown by PBMC model , in which inhibition of IL-6 and TNF-α was achieved by the blocking of either TLR2 or TLR6 . The host may not be vulnerable to pathogens in the duration of TLR6-targeted therapy , due to the redundancy of PRR pathways . TLR6-targeted therapies have a potential for intervention in dengue virus infection and amelioration of disease symptoms . Besides using small-molecule agonists or antagonists for targeting TLRs , the use of microRNAs in the regulation of TLRs may be available in the near future [111 , 112] . In our study , we have found that TLR2 and TLR6 were involved in the detection of the presence of DV during DV infection . However , mice without TLR6 were still able to secrete IL-6 and TNF-α during DV infection . Therefore , other PRRs are also likely to be involved . It would provide a better understanding of the DV infection if the identities of those PRRs were elucidated . Some of the proposed PRRs are TLR3 , TLR7 and TLR8 [28] . In conclusion , DV NS1 protein is found to be responsible for triggering TLR2 and TLR6 during DV infection in our study . This stimulation partially contributes to IL-6 and TNF-α expression during DV infection . Activation of TLR6 may play a role in the immunopathogenesis of DV infection in the mice as survivability of the mice increased in the absence of TLR6 . Lastly , our results provide an insight into the possibility of using TLR6 antagonist in therapeutic treatment for DV infection .
Human peripheral blood mononuclear cells ( PBMC ) were isolated with informed consent from healthy blood donors as whole blood donation , from the Division of Haematology , Department of Laboratory Medicine , National University Hospital , Singapore and was approved by National University of Singapore Institutional Review Board ( NUS-IRB: 10-072E ) . Animal research was approved by NUS IACUC ( protocol no: 090/10 , R15-0033 , BR023/10 , BR14-1255 ) . The mice were anesthesized using isoflurane . Euthanasia was performed using carbon dioxide asphyxiation , followed by cervical dislocation . The Baby Hamster Kidney ( BHK ) cells ( ATCC ) , Human Embryonic Kidney ( HEK ) 293 cells and Aedes albopictus C6/36 cells were grown in RPMI-1640 ( Sigma Aldrich ) supplemented with 10% fetal calf serum [ ( FCS ) , PAA] , DMEM ( Sigma Aldrich ) supplemented with 10% FCS and L-15 media supplemented with 10% FCS respectively . Human peripheral blood mononuclear cells ( PBMC ) were isolated with informed consent from healthy blood donors as whole blood donation , from the Division of Haematology , Department of Laboratory Medicine , National University Hospital , Singapore and was approved by National University of Singapore Institutional Review Board ( NUS-IRB: 10-072E ) . PBMC were isolated from the donors’ buffy coats by centrifugation on a density gradient ( 400x g/30 mins in Ficoll-Paque Plus , GE Health Science ) according to manufacturer’s procedures . Isolated PBMC were grown in RPMI-1640 supplemented with 10% FCS and 1% penicillin-streptomycin of concentration: 10 , 000 units penicillin and 10 mg streptomycin/ml . LPS-treated PBMC were added lipopolysaccharide ( Sigma Aldrich , L-2630 ) into PBMC culture medium . Ultrapure LPS-treated PBMC were added ultrapure lipopolysaccharide ( InvivoGen , LPS-EB Ultrapure ) . His-tag-treated PBMC were added 1 μg/ml of His-tag ( Abcam ab14943 ) into PBMC culture medium . DV NS1 protein-treated PBMC were added 1 μg/ml of DV NS1 protein ( Abcam ab64456 ) into PBMC culture medium . Dengue virus serotype 2 ( DV2 ) , strain ( Den2STp7c6 ) , a low passage isolate from a dengue-infected patient in Singapore and DV2 strain 16681 , a kind gift from Professor Gubler from DUKE NUS were used in this study . The virus was propagated in C6/36 cells . PBMC were transferred separately into 50 ml falcon tubes and centrifuged at 300x g for 5 mins to remove the culture medium . PBMC were infected with DV2 at a multiplicity of infection ( MOI ) of 10 and incubated at 37°C for 1 . 5 hour with intermittent shaking . The cells were washed with PBS once to remove residual virus before RPMI-1640 medium with 10% FCS was added to the cells . PBMC were seeded into each well of 24-well plates ( NUNC ) . HEK 293 cells were seeded in each well of 24-well plates 1 day before infection . Prior to infection , the culture medium was aspirated from the wells and the HEK 293 cells were infected with DV2 at an MOI of 10 with incubation at 37°C for 1 . 5 hour with intermittent shaking . The cells were subsequently washed with PBS before culture medium was added to the cells . Supernatant from uninfected C6/36 culture was denoted as the mock-infected controls . RPMI-1640 supplemented with 10% FCS and 1% penicillin-streptomycin was the culture medium used for PBMC while DMEM supplemented with 2% FCS was used for HEK 293 cells . UV-inactivated virus was obtained by irradiation of the virus under the ultraviolet lamp for 1 . 5 hours . The UV-inactivated virus in the medium was then purified in 100 kDa nominal molecular weight limit centricons ( Millipore , UFC910096 ) and centrifuged at 4000x g for 25 mins in a swing-out centrifuge . PBS was then added into the centricons to wash the virus and centrifuged again at 4000x g for 25 mins . The virus was then collected and reconstituted with L-15 medium . The inactivation of the virus by UV-irradiation was confirmed by performing virus plaque assay . Plaque assay was carried out to quantify the number of infectious virus particles using BHK cells . Briefly , BHK cells were cultured to approximately 80% confluency in 24-well plates . The virus stock was 10-fold serially diluted from 10−1 to 10−6 dilution in RPMI 1640 . BHK monolayers were infected with 100 μl of each virus dilution . After incubation in 5% CO2 atmosphere at 37°C for 1 hour with rocking at 15 mins intervals , the medium was aspirated and 1 ml of 1% ( w/v ) carboxymethyl cellulose in RPMI supplemented with 2% FCS was added to each well . After 6 days of incubation at 37°C in 5% CO2 incubator , the cells were fixed and stained for 1 hour with 200 μl of 1% crystal violet in staining solution . After thorough rinsing with water , the plates were dried and the virus plaques were scored visually . Cell pellets were lysed using CelLytic M cell lysis reagent ( Sigma Aldrich ) with EDTA-free protease inhibitor cocktail ( Roche ) for 10 mins on ice . The total cellular protein in samples was quantified by Bradford Assay ( Bio-Rad ) . 15 μg of protein was loaded in each lane and separated by SDS-PAGE before being transferred onto a nitrocellulose membrane via the semi-dry transfer system ( Bio-Rad ) . Western blot was performed to detect human TLR6 , using rabbit IgG anti-TLR6 ( sc-30001 , Santa Cruz Biotechnology ) ( 1:200 dilution ) and TLR2 , using rabbit IgG anti-TLR2 ( ab86754 , Abcam ) ( 1:200 dilution ) . Blots were incubated with HRP-conjugated goat anti-rabbit IgG ( H+L ) secondary antibody ( Pierce ) ( 1:2500 dilution ) . Analyses were performed using enhanced chemiluminescence detection system with Pierce ECL Western Blotting Substrate . The density of the bands was quantified using GelQuant . NET software provided by biochemlabsolutions . com . PBMC infected with DV2 at an MOI of 10 or mock-infected were transferred from 24-well plates into 15ml falcon tubes . The cells in the falcon tubes were centrifuged at 300x g for 5 mins . The supernatant were then discarded and 5ml of PBS were added for the washing of the cells . The cells were spun down once more to remove the PBS . PBS containing 5% BSA was used to resuspend the cells before the cells were incubated on ice for 20 mins . Primary antibody [anti-TLR6 ( Santa Cruz SC-30001 ) , anti-TLR2 ( Santa Cruz SC-21759 ) or anti-CD14 ( Millipore CBL453F ) ] was then added at a dilution of 1: 200 to the cell suspension and incubated on ice for 30 mins . The cells were then spun down and the supernatant removed . 5 ml of PBS was used to wash the cells before the cells were spun down again to remove the PBS . Following that DyLight 633/FITC-conjugated goat anti-rabbit or anti-mouse IgG ( H+L ) secondary antibody ( Pierce ) , was added at 1: 200 and incubated on ice for 30 mins . The cells were then washed twice with 5ml of PBS before fixing using 4% paraformaldehyde at room temperature for 10 mins . After which the cells were washed and resuspended in 1 ml of PBS . For the staining of two different antigens in the same sample , the above procedure of staining was repeated once more using primary antibodies derived from a different species . The cells were analyzed using Beckman Coulter CyAn ADP Analyzer . Samples were gated to exclude cell debris . PBMC were stained with anti-TLR6 antibody ( Santa Cruz , SC-30001 ) or anti-TLR2 ( Santa Cruz SC-21759 ) and anti-CD14 ( Millipore CBL453F ) at a dilution of 1:200 for 30 mins , followed by FITC-conjugated goat anti-rabbit IgG ( H+L ) secondary antibody for 30 mins and fixed using 4% paraformaldehyde . The cells were then incubated with 4’-6-Diamidino-2-phenylindole ( DAPI ) at a concentration of 300nM for 5 mins at room temperature . The cells were spun down at 300x g for 5 mins and washed twice in 5 ml of PBS . The cells were resuspended in 10 μl of PBS . 10 μl of the cell suspension was placed onto a glass slide , mounted on coverslip and viewed under the microscope ( IX81 Olympus , Japan ) at 1000x magnification . Quantification of cytokines ( IL-6 and TNF-α ) was carried out using sandwich enzyme-linked immunosorbent assay ( ELISA ) which was performed in 96-well plate . ELISA for human and murine IL-6 and TNF-α were performed using commercial kits ( BD biosciences , Pharmingen ) and according to manufacturer’s protocol . Briefly , 100 μl of anti-IL-6 or anti-TNF-α antibody diluted 1:250 with coating buffer were added into each well to coat the antibody onto the plate through an overnight incubation at 4°C . The plates were then washed three times using wash buffer ( PBS with 0 . 05% Tween-20 ) before blocking using 200 μl of assay diluent per well . After adding the standards and the samples , the plates were washed three times using wash buffer and incubated with 100 μl of anti-IL-6 or anti-TNF-α biotinylated antibody and streptavidin-conjugated horseradish peroxidase diluted 1:250 with assay diluent for an hour . The plate was then washed seven times , followed by adding tetramethyl benzidine substrate solution to each well . Absorbance was measured using ELISA reader ( Tecan ) at wavelength of 450 nm with reference wavelength of 570 nm . The concentrations of the cytokine in experimental samples were determined from a standard curve with known concentrations of the cytokine . Samples were performed in triplicates . PBMC were incubated with TLR2 or TLR6 blocking antibodies ( IgG1 ) ( InvivoGen , San Diego , USA ) at a concentration of 1000 ng/ml for 30 mins on ice . Unbound antibodies were washed off with PBS before infection or mock-infection was performed . For PBMC to be blocked by both TLR2 and TLR6 blocking antibodies , 500 ng/ml of each antibody were used instead . Normal mouse IgG1 ( Santa Cruz Biotechnologies , Santa Cruz , USA ) from unstimulated mice was used as isotype control at a concentration of 1000 ng/ml . Activation of NFκB was determined using a reporter plasmid ( pNF-κB/SEAP , IMGENEX ) which expresses secreted alkaline phosphatase ( SEAP ) protein under the control of the NFκB promoter . These plasmids were transfected into HEK 293 cells using Invitrogen Lipofectamine LTX according to manufacturer’s protocol . SEAP catalyzes the hydrolysis of p-Nitrophenyl phosphate producing a yellow product that can be read using ELISA reader at 405 nm . Stable cell clones of the transfected cells were obtained by selection using G418 ( PAA ) at 500μg/ml . In brief , 2 x 105 transfected HEK 293 cells were seeded into 24-well plate 1 day prior to treatment . The cells were then treated under various conditions [infected with DV2 at an MOI of 10 , mock-infected , DV NS1 recombinant protein ( 1 μg/ml ) , LPS ( 5 μg/ml ) or MALP-2 ( 50 ng/ml ) ( Imgenex , IMG-2206 ) added into the culture medium] . Supernatant were harvested 1 to 3 day post-treatment . The amount of SEAP in the supernatant was assayed according to manufacturer’s protocol and read using an ELISA reader ( Tecan ) at wavelength of 405 nm . TLR2 and TLR6 in HEK 293 were expressed using a plasmid co-expressing the human TLR2 and TLR6 genes ( pDUO-hTLR6/TLR2 , InvivoGen ) which was transfected into the NFκB-SEAP HEK 293 cell clones obtained as mentioned in the previous paragraph . Stable cell clones of the transfected cells were obtained by selection using both blasticidin ( Invitrogen ) at 10 μg/ml and G418 ( PAA ) at 500 μg/ml . The expression was confirmed with immunoblotting after the transfected cells were stained for TLR2 or TLR6 using the antibodies mentioned above . Dengue viral recombinant proteins ( Capsid , PrM , envelope , NS1 , NS2A , NS2B , NS3 , NS4A , NS4B , NS5 ) with 6x his-tag and protein tag ( 6x his-tag ) at concentration of 1 mg/ml were expressed using BaculoDirect Baculovirus Expression System ( Invitrogen ) according to manufacturer’s protocols . Sera of mock-infected and DV2-infected mice were harvested for DV NS1 antigen detection assay using the Platelia Dengue NS1 Antigen detection kit ( Bio-Rad , #72830 ) for day 1 to day 5 and day 21 post-infection . The relative amount of DV NS1 protein was measured in optical density and was read using Tecan plate reader at wavelength of 450 nm with reference wavelength of 620 nm . C57BL/6 mice used in this study were obtained from InVivos and the former NUS CARE ( NUS , Singapore ) . TLR6 knock-out C57BL/6 breeder mice were obtained from Oriental BioService , Kyoto , Japan and bred in NUS , Singapore under NUS IACUC approved breeding protocols , BR023/10 and BR14-1255 . The use of mice for this study was approved by NUS IACUC under protocols , 090/10 and R15-0033 . One to two days old C57BL/6 mice were infected with 5 . 4 x 108 PFU/ml of 16681 DV2 via intraperitoneal injection ( IP ) at a volume of 0 . 05 ml/g . For mock-infection , C6/36 culture supernatant of the same volume as the virus was injected instead . For DV NS1 protein treatment , one to two days old C57BL/6 mice were injected with 20 μl of DV NS1 recombinant protein of concentration 1 mg/ml . For His-tag treatment , 20 μl of His-tag of concentration 1 mg/ml was injected instead . Mice were euthanized before blood was collected by cardiac puncture . The blood was left to clot at room temperature and centrifuged at 3300x g for 5 mins to obtain the serum . It was observed that some mice had a bulge at the site of injection on day 1 post-infection . Peritoneal fluid was extracted from the bulge using 27 G needle and syringe for virus quantification as well . Brains of mice were harvested by removing the skin on top of the head and making an incision at the centre of the scalp using scissors . Livers of mice were harvested by making an incision at the abdomen . Hindlimbs of mice were harvested by cutting the hind limbs of the mice at the pelvis joint . Brains , livers or hind limbs of mice were placed in hard tissue homogenizing tube containing ceramic beads ( Precellys , Bertin , Germany ) . The weight of the tissues in each of the tubes was recorded and 0 . 5 ml of PBS was added to each tubes . The tissues in the tubes were homogenized using a tissue homogenizer ( Precellys , Bertin , Germany ) . The conditions used were 6500 rpm for 10 secs with 3 repetitions and 5 secs rest in between . The tubes were then centrifuged at 3500x g for 10 mins . The supernatant was collected in a new eppendorf tube and centrifuged at 10 , 000x g for 10 mins . DV2 in the serum or peritoneal fluid or supernatant of homogenized tissues were determined using plaque assays . 1% penicillin-streptomycin , 1% amphotericin B ( MP Biomedicals , Southern California , USA ) and 0 . 5% gentamycin ( PAA , GE Healthcare , Piscataway , USA ) were added to the overlay medium . As the volume of the serum or peritoneal fluid harvested from each of the pups may be less than 100 μl , there may not be neat sample and the calculation of PFU/g was adjusted according to the volume of sample used . IL-6 and TNF-α in the supernatant of homogenized tissues were determined using ELISA . 4% thioglycollate medium was prepared and autoclaved . 4-week old mice were injected with 1 ml of 4% thioglycollate medium via intraperitoneal injection . Four days after injection , the mice were euthanized and the skin around the abdomen of the mice was removed to expose the intraperitoneal cavity . Ice cold PBS was injected into the intraperitoneal cavity without bursting the peritoneal membrane . Precaution was taken to avoid puncturing any organ or intestine . The abdomen of the mice was gently massaged before withdrawing the PBS containing macrophages from the intraperitoneal cavity . The murine peritoneal macrophages in PBS were collected and centrifuge at 450x g for 5 mins at 4°C . One ml of Red blood cell lysing buffer Hybri-Max ( Sigma-Aldrich ) was added to the cell pellet and resuspended for 3 mins . Fourteen ml of PBS was added and the tube was centrifuged at 450x g for 5 mins at 4°C . The cells were washed again with PBS before culturing in RPMI-1640 supplemented with 10% heat-inactivated FCS , 1% penicillin/streptomycin , 1% amphotericin B and 0 . 5% gentamycin . DV2-Infected or mock-infected wild type or TLR6-/- C57BL/6 mice were monitored daily and observed for any abnormal signs which could be symptoms of infection for up to day 21 post-infection . DV NS1 protein-treated or His-tag-treated wild type or TLR6-/- C57BL/6 mice were monitored daily and observed for any abnormal signs which could be symptoms of infection for up to day 7 post-infection . The statistical comparisons were carried out using two tailed Student’s t-test for repeated measurements when applicable . The significance level was set at *: p < 0 . 05 , **: p < 0 . 005 , ***: p < 0 . 0001 . Data shown are obtained from three independent experiments unless stated otherwise . Kruskal-Wallis test was used for non-parametric data set . Log-rank test was used to compare the survival curves of mice . | Despite the prevalence of dengue virus infection and the heavy economic burden it puts on the endemic countries , the immunopathogenesis of dengue virus infection remains unclear . Plasma leakage in dengue hemorrhagic fever ( DHF ) develops not when the viremia is at its peak in infected patients but when viremia has been significantly reduced or cleared . This suggests that host immune response is responsible for the development DHF . The interactions of the viral factors with host factors which trigger the host immune responses are likely to play a significant role in the development of dengue diseases , thus are of great interests . In this study , we found that dengue NS1 protein activates TLR2 and TLR6 , leading to increase proinflammatory cytokine production . In addition , the interaction of viral factor with TLR6 was found to play an important role in the manifestation of dengue virus infection . Our study provides new insights into the involvement of TLR6 in dengue virus infection and the potential of using TLR6 anatagonist in therapeutic treatment for DV infection . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Activation of TLR2 and TLR6 by Dengue NS1 Protein and Its Implications in the Immunopathogenesis of Dengue Virus Infection |
Mouse early transposon insertions are responsible for ∼10% of spontaneous mutant phenotypes . We previously reported the phenotypes and genetic mapping of Polypodia , ( Ppd ) , a spontaneous , X-linked dominant mutation with profound effects on body plan morphogenesis . Our new data shows that mutant mice are not born in expected Mendelian ratios secondary to loss after E9 . 5 . In addition , we refined the Ppd genetic interval and discovered a novel ETnII-β early transposon insertion between the genes for Dusp9 and Pnck . The ETn inserted 1 . 6 kb downstream and antisense to Dusp9 and does not disrupt polyadenylation or splicing of either gene . Knock-in mice engineered to carry the ETn display Ppd characteristic ectopic caudal limb phenotypes , showing that the ETn insertion is the Ppd molecular lesion . Early transposons are actively expressed in the early blastocyst . To explore the consequences of the ETn on the genomic landscape at an early stage of development , we compared interval gene expression between wild-type and mutant ES cells . Mutant ES cell expression analysis revealed marked upregulation of Dusp9 mRNA and protein expression . Evaluation of the 5′ LTR CpG methylation state in adult mice revealed no correlation with the occurrence or severity of Ppd phenotypes at birth . Thus , the broad range of phenotypes observed in this mutant is secondary to a novel intergenic ETn insertion whose effects include dysregulation of nearby interval gene expression at early stages of development .
The molecular causes of vertebrate malformations and the molecular basis of the variability in Mendelian syndromes are incompletely understood . While coding alterations have received a substantial amount of attention , the contribution of variation or mutation in intergenic regions , as well as the role of genetic background/modifiers , epigenetic and environmental factors , retrotransposons and transgenerational genetic effects , are receiving more attention particularly in relation to penetrance , expressivity and pleiotropy [1]–[8] . Spontaneous mobile element insertions in mice can be associated with alterations in body plan and morphogenesis [9] . There are many types of transposable elements; however , those active in the mouse are mostly IAP or Type II early transposons ( ETn ) [9] . Type II early transposons carry long terminal repeats ( LTR ) and are classified into MusD , ETnI and ETnII subtypes . IAP , MusD and ETnII insertions are responsible for a substantial fraction ( ∼10% ) of spontaneous new mutations in mice [9] . Most previously reported mutagenic ETn insertions occur in the sense orientation within genes , resulting in disruption of exons , polyadenylation and/or splicing . ETn elements are highly transcribed during pre-gastrulation and at later stages of morphogenesis in selected tissues [10–12] and while promoter activation of adjacent genes has been demonstrated for IAP elements , it has not been observed for ETn insertions [9] . Moreover , ETn regulatory sequences such as enhancers and repressors upon random insertion in new genomic environments could exert deleterious or beneficial effects on neighboring gene expression . The activity of retrotransposons varies depending on their state of methylation , which is controlled by host factors , and many transposable elements act as metastable epialleles [9 , 13 , 14] . Previously we reported the phenotypes and genetic mapping of Polypodia , ( Ppd ) , a dominant , X-linked mouse mutation exhibiting malformations in 20–25% of newborn mutation carriers [15] . Postnatally affected mice predominantly exhibit ventral , caudal limb duplications ( Figure 1 ) and a variety of other defects including bilaterally asymmetric anomalies , partially duplicated snouts and whiskers , mirror-image pelvic duplication ( dipygus ) , extra digit-like bony growths on abdominal skin , cystic kidneys , renal agenesis , duplicated external genitalia with normal internal genitalia , kinked , curly or knotted tails , forelimb postaxial polydactyly , radial aplasia , spina bifida , microphthalmia ( unilateral ) , supernumerary nipples , yet no malignancy , duplicated upper extremities , or extra spinal elements . We localized the mutation to a ∼10 Mb interval on the mouse X-chromosome between markers DXMIT74 and rs13483835 [15] . The striking body plan alterations offer an opportunity to understand in molecular terms how such disorganization of the vertebrate body plan can occur and how these principles might inform our understanding of similar birth defects in humans . In this paper , we 1 ) show that Ppd mutant embryos are not born at expected Mendelian ratios due to fetal loss , 2 ) describe the discovery of a novel , intergenic ETnII-β insertion in the refined genetic interval , 3 ) recreate the mutation using homologous recombination in ES cells and recapitulate Ppd phenotypes , 4 ) show that one effect of the Ppd ETn insertion is dysregulated adjacent gene transcription in mutant ES cells , and 5 ) show that the state of DNA methylation of the 5′ LTR is not correlated with Ppd phenotypic variability .
Ppd arose on the CD-1 strain and mutants exhibit a variety of malformations as described above , although the ventral , caudal duplications with extra limbs are the most frequent and dramatic [15]; Figure 1 . We crossed Ppd hemizygous males and heterozygous females to the wild-type , inbred C3H/HeJ strain for over 10 generations and observed that ∼21% of mice born with Ppd interval genetic markers [15] showed abnormal phenotypes . We attempted crosses to produce a higher frequency of postnatal anomalies to facilitate later experimental studies by outcrossing Ppd mice ( male or female ) on the C3H background ( generation N8 ) to CAST/EiJ , CZECHII/EiJ , MSM/Ms , C3H/HeJ , C57BL/6J , DBA/2J , CD1 , and B6/D2 F1 hybrids . Offspring were evaluated at birth for any of the phenotypes observed in Ppd mutants and genomic DNA was collected and genotyped for the Ppd haplotype [15] . In this breeding scheme , inclusion of C57BL/6J genetic background did not change the frequency of observed postnatal malformations ( ∼21–22% ) in females or males bearing the Ppd genetic interval . Outcrossing for one generation to CAST/EiJ , CZECHII/EiJ and DBA/2J chromosomes resulted in the lowest percentage with birth anomalies ( ∼0–0 . 4% ) , whereas ∼11–14% of newborns of MSM/Ms , B6/D2 and CD1 outcrosses had anomalies at birth . This is not a formal measure of penetrance . It suggests , but does not prove , that genetic background could have a significant effect on the phenotypic outcome related to inheriting this mutation , but evidence to support that conclusion will require many generations on the individual strains as well as examination of both prenatal and postnatal phenotypes . We hypothesized that apparent variations in the frequency of postnatal malformations in mutants at birth might be influenced by embryonic lethality . To test this , we took advantage of a genetic cross for mapping purposes that produced Ppd heterozygous female mice with one wild-type CZECHII X-chromosome and one Ppd X chromosome ( C3H background ) and mated these females with wild-type C3H males . Offspring of this latter cross were genotyped for interval markers and sex as described [15] , which allowed us to determine the birth frequency of male and female offspring with the Ppd chromosome , which must come from the female . Table 1 shows the X-chromosome identity in offspring ( CZECHII/C3H refers to a female with CZECHII and C3H chromosomes; CZECHII/Y refers to a male with a CZECHII X-chromosome; Ppd/C3H refers to a female with Ppd and C3H X-chromosomes; Ppd/Y refers to a male with a Ppd X-chromosome ) . A 60% reduction of the Ppd haplotype was found in liveborn males and a 23% reduction was observed in liveborn females ( Fisher's Exact test , p<0 . 007 ) . A similar result was obtained in a cross involving only the C3H background ( 82% and 36% reductions , respectively; Table 2; p<0 . 055 ) . The data indicate that there are fewer Ppd mutants at birth than expected and males with Ppd are more likely than females to fail to be born . To determine if Ppd X-chromosomes are represented in offspring early in development as expected , we evaluated the genotypes and sex of conceptuses at E9 . 5 . Ppd males ( C3H background ) were crossed to CD-1 females , followed by a backcross of female Ppd offspring to CD-1 wild-type males . Evaluation of those offspring revealed expected numbers of Ppd X-chromosomes in conceptuses at E9 . 5 ( Table 3 ) . Thus , embryos must be dying between E9 . 5 and birth . Our preliminary data suggest that mutants occasionally display extensive early gastrulation abnormalities including overallocation of extraembryonic tissue at the expense of the epiblast and accumulation or piling up of cells in the primitive streak ( J . Innis , K . Downs , P . Wakenight , K . Millen , data not shown ) . Further work will be required to determine the basis of fetal loss in these mutants . We reported the location of Ppd in a 9 . 64 Mb genetic interval on the X- chromosome [15] . To narrow the interval , we crossed our Ppd mice on the C3H background to CZECHII/EiJ mice to exploit a greater number of polymorphic differences and improve crossover resolution . Using 2 visibly affected recombinant animals , we narrowed the interval to 1 . 85 Mb between DXMIT94 and rs13483824 . a at 72 . 02 Mb and 73 . 87 Mb , respectively ( GRCm38 ) . In addition , we test crossed the visibly unaffected critical recombinant F2 animals and looked for affected progeny , allowing us to refine our map based on the Ppd “carrier” haplotype . These efforts allowed us to locate Ppd in a ∼1 . 4 Mb interval between DXMIT119 and SNP rs13483824 . a ( data not shown ) . We previously reported a normal karyotype and no apparent submicroscopic gene dosage aberration by BAC array comparative genomic hybridization ( CGH ) [15] . To examine the X chromosome in more detail , we compared male Ppd DNA to wild-type male C3H DNA using an X-chromosome-specific NimbleGen array in a CGH experiment with average probe spacing every 500 base pairs . No variation was identified on the X-chromosome within the 1 . 4 Mb critical genetic interval ( data not shown ) . Thus , at this level of resolution Ppd is not due to a chromosomal deletion/duplication , leaving us to consider single gene smaller mutations , deletions or insertions . Our refined genetic mapping experiments on the X-chromosome defined a Ppd interval with over 30 annotated protein coding genes . To determine if Ppd was a mutation in one of these interval genes , we prioritized gene candidates based on known gene function and initiated a variant search with several methods . Southern analysis with non-repetitive , gene-centered DNA probes and Ppd genomic DNA disclosed altered restriction digest patterns with a Dusp9 gene probe ( Figure 2A ) . This alteration was not observed with this probe in other mouse strains ( Figure S1 ) . Using PCR primer walking and DNA sequencing of PCR products and clones spanning the entire insertion and flanking regions we identified a 5 . 5 kb insertion positioned 1 . 6 kb downstream of the 3′ end of the Dusp9 gene ( Figure 3 ) . No mutations of endogenous chromosomal material were observed in adjacent genomic regions . We demonstrated absence of this genomic alteration in representative background ( CD-1 ) male genomic DNA , as well as 21 different mouse strains using PCR ( Figure 2B ) . Similarly affected mutant mice were independently discovered by K . Millen and P . Wakenight in CD-1 animals at the University of Chicago . Blinded testing with a Ppd mutation-specific PCR assay utilizing unique primers to the adjacent X chromosome and the newly inserted sequences ( see Figure 3 , primers F5/R6; 248 base pair product ) , demonstrated the same insertion mutation in those affected mice ( data not shown ) . The DNA sequence of the inserted segment ( GenBank Accession: Mouse_ETnII-B_Polypodia_X_Chromosome_DNA KC512757 ) revealed it to be an early transposon type IIβ ( ETnII-β ) element . This conclusion is supported by 1 ) the sequences of the homologous 5′ and 3′ LTRs; 2 ) the presence of a putative Lys-tRNA binding site ( PBS ) 5′-TGGCGCCCGAACAGGGA-3′ , 3 ) the presence of a 6 bp direct duplication ( 5′-TCCTGT-3′ in the orientation shown in Figure 3 ) at the insertion junctions , 4 ) absence of coding sequences that would be more characteristic of MusD or IAP elements [16–18] , 5 ) absence of ETnI-specific sequences [19] , and 6 ) the presence of specific sequences found only in ETnII-β elements that cross an internal deletion ( ETnII-3636as = 5′-GTCACTTAATACCCCCTGACTAACAAATG-3′; [20 , 21] . The Ppd interval ETnII-β is highly related to several endogenous ETnII-β elements located on chromosome 5 ( AC163331 ) , chromosome 13 ( AC163684 ) and within the desmoglein locus , among others . As expected , the 317 bp LTRs of the newly identified ETn are identical and have 16 CpG dinucleotide sites . The Ppd interval ETn is located 1 . 6 kb downstream ( relative to Dusp9 transcription ) of the polyadenylation signal of Dusp9 , between two repetitive sequences ( SINE and LINE elements; Figure 3 ) at position ChrX: 73645160 ( GRCm38/mm10 ) . This insertion does not disrupt Dusp9 , Pnck , or any other known gene or noncoding RNA; examination of the EST databases shows no reported spliced or unspliced ESTs or isoforms beyond exon 4 of Dusp9 or of the last exon of Pnck . Sequencing of exons and exon/intron boundaries of Dusp9 and Pnck did not reveal any pathogenic sequence variants . The orientation of the ETn is antisense to Dusp9 gene transcription and the insertion site is located ∼10 . 8 kb from the 3′ end of the Pnck gene . Thus , the ETn insertion appeared to be a strong candidate for Ppd . While transposon insertions are well known mutagens , the intergenic position of the insertion was novel . To determine whether this novel intergenic ETnII-β insertion is Ppd , we sought to introduce this ETn into a wild-type genome to create an engineered ETn allele ( eETN ) . We first created a BAC library from male Ppd genomic DNA and then isolated a BAC clone spanning the genomic region including the ETn . We used BAC recombineering to construct a targeting vector for homologous recombination in mouse ES cells ( Figure 4 ) . DNA sequencing of 5′ and 3′ genomic targeting arms was employed to determine whether the ETn insertion was the only plausible candidate mutation in the targeting vector . Sequencing disclosed one common , non-coding SNP variant ( rs29038663; C>T; GRCm38/mm10 ) by comparison with the reference C57BL/6J sequence . Thus , the ETn insertion is the only candidate mutation within the targeting vector . We employed Bruce-4 . G9 ( a chromosomally stable sub-line generated at the University of Michigan Transgenic Animal Core Lab from Bruce4 ES cells ) [22] and UMB6J-D7 ( a pure BL/6 line generated here at the University of Michigan ) mouse ES cell lines to knock-in the ETn into the wild-type genome . Three hundred clones from each electroporation were picked and expanded . Southern blotting with Probe A ( see Figure 4 ) and Ppd ETn-specific locus PCR ( F5/R6 ) confirmed a high frequency of homologous recombination in both cell lines ( 27–50% ) . Five ES cell clones from each line were karyotyped and 5 cell lines ( 4 Bruce4 . G9 and 1 UMB6J-D7 ) from those clones were found to be euploid . All euploid lines were reexamined by Southern blotting ( Figure S2 ) and by Ppd-specific PCR ( not shown ) and were found to be correctly targeted . Blastocysts were injected with the Bruce-4 . G9 targeted ES cells , and chimeric males were produced . Germline transmission was successful in generating 10 female engineered ETn ( eETn ) heterozygotes ( Neo+/eETn+ ) ; none of these females exhibited an abnormal phenotype . We bred these females to β-actin FLPe males ( Jackson Lab stock #005703 ) , to excise the Neo cassette and demonstrated expected PCR products after excision ( Figure S3 ) . Figure 5A shows a Neo−/eETn+ progeny female with a caudal mass and ectopic legs . This observation confirmed our hypothesis that the ETn is the Ppd mutation . To determine if phenotypically unaffected Neo−/eETn+ mice could have offspring with Ppd phenotypes consistent with the original Ppd mutant , we bred Neo−/eETn+ carrier males to B6/D2 F1 hybrid or FVB females . Nine out of 69 ( 13% ) eETN+ offspring of B6/D2 mothers and 8 out of 31 ( 26% ) eETN+ offspring of FVB mothers , had caudal masses with ectopic limbs . These results demonstrate that germline transmission of the engineered allele from the male or female germline is associated with typical Ppd caudal malformations ( Figure 5B , C ) . Moreover , in this small cohort on mixed genetic backgrounds , the frequency of postnatal malformations and phenotypic variability in the engineered lines is similar to that of the original Ppd allele . These results confirm that the ETnII-β insertion is the Ppd mutation . Endogenous retroviral transpositions including ETnII-β insertions are the cause of ∼10% of spontaneous new mouse mutants [9 , 19] . Most , but not all , mutagenic ETn insertions occur within genes in the mouse and are sense-oriented [9 , 23] . Transcriptional interference with splicing or 3′ end formation , when ETn insertion occurs within genes due to the contribution of ETn splice sites and polyadenylation signals , is well documented and is the basis of most phenotypic effects of such insertions [9] . To begin to explore the mechanism by which the Ppd ETn insertion was interfering with development , we first examined the structure and expression of flanking genes Dusp9 and Pnck mRNAs in mutant embryos . Dusp9 encodes a MAP kinase tyrosine/serine/threonine phosphatase of which there are numerous family members [24 , 25] . Dusp9 is expressed in ES cells [26] , but it is not essential for ES cell viability , although BMP4 has recently been shown to activate Dusp9 transcription via SMAD1/5 , resulting in reduction of pERK in ES cells [27] . Expression also has been observed in the ectoplacental cone and chorion of the placenta as early as E7; at E8 . 5 Dusp9 is activated in the ventral foregut endoderm , which ultimately becomes the liver . It is also expressed in dorsal and ventral muscle groups of the forelimb and hindlimb at E9–E11; the face ( E9 ) , mandible and hypoglossal cord [24] . Dusp9 heterozygous and null mutants die prenatally by E10 . 5 due to failure of growth of the placental labyrinth [26] , and by tetraploid rescue mutants exhibit normal embryonic development [26] . Pnck encodes a pregnancy-upregulated , non-ubiquitously expressed calcium/calmodulin-dependent serine/threonine protein kinase [28] , and is known to be expressed in mammary glands , brain and during hippocampal dendritic growth . PNCK has also been shown to induce ligand-independent epidermal growth factor receptor degradation [29] . Therefore , we sought to test if the ETn alters Dusp9 or Pnck 3′ RNA structure by evaluating mRNA from E7–E9 . 5 whole mutant embryos compared to wild-type littermates by 3′ RACE . No major differences were detected in relative abundance or in 3′ RACE products of Dusp9 or Pnck RNA in mutant embryos at these developmental times ( Figure S4 ) . We hypothesized that the ETn may ectopically activate or interfere with the transcription of Dusp9 or Pnck , through modification of the chromatin environment or through enhancer provision , usage , or interference . This hypothesis seemed particularly relevant considering the burst of early transposon transcription that occurs during early stages of development from E3 . 5–E7 . 5 [10–12 , 30] . To test this hypothesis , we first examined the mRNA expression and structure of Dusp9 and Pnck in wild-type mouse embryonic stem cells . ES cells represent the inner cell mass at a developmental stage when early transposon transcription is high . Reverse-transcription PCR using oligo-dT primed synthesis followed by PCR using primers in different exons confirmed that Dusp9 and Pnck are normally expressed in wild-type ES cells ( data not shown ) . Due to the close location of the ETn to Dusp9 , we used mutant ES cells to evaluate Dusp9 splicing ( from exons 2–4 by RT-PCR ) and 3′ end formation as assessed by 3′ RACE . Neither were disrupted in mutant ES cells ( data not shown ) , consistent with the observations in mutant embryos . To determine if Dusp9 , Pnck or other X chromosome local interval gene transcription is dysregulated as a consequence of the ETn insertion , we examined steady-state mRNA from several independent mutant male ES cell lines using Affymetrix Mouse GeneChip 430 2 . 0 expression microarrays . We compared all 3 original Ppd ES lines with normal ES cell mRNA prepared from Bruce4 . G9 , ND-D3 and UMB6J-D7 lines . We focused our analysis to genes in 500 kb intervals on either side of the ETn insertion site on the mouse X chromosome . Within this 1 Mb interval are 35 RefSeq genes ( GRCm38/mm10 ) , for which 9 were not represented on the microarray used ( 2 microRNA genes; 4 X-linked lymphocyte regulated genes; and 3 newly added genes in mm10 , Haus7 , Naa10 and Tex28 not located close to the ETn insertion site ) . Both Dusp9 and Pnck were represented . Genes in this interval whose expression fulfilled quality measures ( see Materials and Methods ) , were increased or decreased at least 2 fold and exhibited a FDR≤0 . 05 , were Dusp9 ( all 3 probe sets , increased 3 . 12 , 2 . 74 and 2 . 6 fold ) and Slc6a8 ( only 1 of 2 probe sets , increased 2 . 34 fold and 1 . 07 fold ) . Pnck mRNA expression was not altered . Slc6a8 , which encodes a brain creatine transporter , is located telomeric to Pnck and was not examined further . We used Taqman real-time quantitative RT-PCR directed to Dusp9 , a MAP kinase phosphatase , to confirm the array result . Steady-state Dusp9 RNA expression was elevated in all ETn-bearing ES cells by 5–15 fold over wild-type cells ( Figure 6A , B ) . To determine if the elevated levels of Dusp9 steady-state mRNA are associated with higher levels of steady-state DUSP9 protein , we performed Western blots with protein extracts from mutant ES cell populations compared to 4 different wild-type ES cell lines ( Figure 6C ) . Western blots with DUSP9 antibody ( gift from Robin Dickinson; [24] ) revealed increased DUSP9 protein expression ( 7–14 fold ) , adjusted for β-actin , in all Ppd ES cell lines and all eETn ES cell lines . This was confirmed with an independent antibody ( data not shown ) . The specificity of both antibodies for DUSP9 was confirmed by testing the effects of pre-incubation with synthesized DUSP9 peptide versus control , nonspecific peptide ( Figure S5 ) . Thus , DUSP9 protein is over-expressed in Ppd mutant ES cells . We conclude that one consequence of ETn insertion is Dusp9 overexpression in pluripotent cellular representatives of the inner cell mass . Retrotransposon activity varies depending on the state of methylation of the locus [13 , 14] . CpG methylation increases from 5′ to 3′ within individual ETn LTRs [14] . We hypothesized that variable occurrence in the Ppd phenotype among ETn carriers or Ppd males at birth may be explained by variation in Ppd interval ETnII-β 5′ LTR methylation . To test this hypothesis , we used bisulfite sequencing of tail genomic DNA from affected versus unaffected Ppd ETn carrier ( female ) and male littermates . After bisulfite modification , we amplified 237 base pairs of the 317 bp 5′ LTR anchoring on adjacent X-chromosome specific genomic sequence , allowing us to interrogate seven 5′ LTR-specific CpG dinucleotides and 1 adjacent X chromosome genomic CpG dinucleotide immediately upstream of the transcription start sites mapped in ETnII-β elements [21] . Comparison showed that inter-individual differences in the occurrence of a Ppd phenotype at birth is not related to the methylation state of the 7 CpG dinucleotides in the 5′ portion of the 5′ LTR ( Table 4 ) in either females or males . We also examined the methylation of the ETn in Ppd ES cells; the ETn , as expected , was largely unmethylated at this stage of development . In addition , male Ppd animals , regardless of phenotype , exhibited a broader distribution of the degree of methylation of these 8 CpGs . To determine if variation in 5′ LTR methylation was observed between tissues within an affected animal , genomic DNA derived from normal tissue ( tail ) and from the caudal ectopic legs/mass from one adult Ppd female was subjected to bisulfite sequencing . No differences were observed in the degree or distribution of methylated CpG residues . These results suggest that if the methylation state of the ETn does affect the occurrence of postnatal phenotypes , it is not observable as a difference in 5′ LTR methylation in adult tissues .
Using genetic mapping and homologous recombination in ES cells , we have shown that a novel ETnII-β insertion discovered to lie 1 . 6 kb downstream of the Dusp9 gene is the Ppd genetic lesion . ETnII-β elements often insert into exons and disrupt splicing and polyadenylation [9] , yet we find no evidence of an altered Dusp9 transcript structure . Instead , in mutant ES cells , one apparent effect of the ETn in this new genomic environment is increased Dusp9 mRNA and protein expression . ES cells represent the pluripotent inner cell mass at a developmental time point associated with increased ETn transcription and it is attractive to speculate that interference , by an as yet unknown mechanism , with appropriate transcriptional regulation of Dusp9 at this or other stages of development , or of other genes in this region of the X chromosome , gives rise to the phenotypic effects in the Ppd mutant . ETn elements have been hypothesized to exert mutational effects on gene expression at a distance , but few examples have been identified . Dactylaplasia [31] is due to MusD ( ancestral ETn ) element insertion within ( Dac2J ) or upstream ( Dac1J ) of the dactylin gene [32] , and the two mutant alleles are suppressed by an unlinked modifier , Mdac [31] . Limb defects in Dactylaplasia mice may result from Mdac-suppressible transcriptional interference with apical ectodermal ridge expression of Fgf8 [32–34] , a gene located more than 70 kb away from the MusD insertion sites . Interestingly , MusD expression in the AER is increased in mutant limbs suggesting that Fgf8 AER enhancers may be co-opted by an active MusD element in this mutant [34] . In addition , Mdac appears to dominantly modulate the MusD methylation state , which inversely correlates with the phenotype . Recently , another intergenic ETn insertion 12 . 5 kb upstream of Ptf1a was elucidated as the cause of the semidominant Danforth's short tail ( Sd ) mutation , and this insertion is associated with upregulation of embryonic expression of Ptf1a leading to caudal regression phenotypes [35–37] . The addition of our example confirms that such intergenic insertions , while rare , are capable of modifying gene expression , although in all cases reported so far , the mechanism remains to be determined . In contrast to Dac mutants , the methylation state of the Ppd 5′ LTR is not correlated to phenotype . These results are consistent with prior conclusions indicating that ETnII transcriptional activity is regulated by more than methylation state and genomic environment [21] . Although we did not examine the 3′ LTR , which is closest to the Dusp9 gene , histone modification and chromatin structure across the Dusp9/ETn interval could be altered by the ETn and would be exciting to examine in future studies , with consideration given to analysis of selected cell populations earlier in development . We have not proven that upregulation of Dusp9 or modification of any other interval gene expression is the cause of the malformations and/or fetal death . It is conceivable that ETn transcriptional effects ( negative or positive ) could also occur at later developmental phases in different tissues . ETn expression occurs in two phases [10–12] . In the first phase , ETnII transcription occurs during E3 . 5–E7 . 5 beginning in the inner cell mass and extending into the epiblast and extraembryonic ectoderm . The 2nd phase occurs between E8 . 5–E11 . 5 beginning with E8 . 5 neural tube ETnII expression outlining the rhombomeres [12] . This neural expression gradually decreases as mesodermal expression increases in the somites at E8 . 5 . At E9 . 5–10 . 5 , expression is observed in the olfactory placode and then becomes concentrated along the nasal pit and lateral nasal processes . Strong branchial arch ETnII expression was observed at E8 . 5–E11 . 5 . Finally , the forelimb and hindlimb buds exhibited strong expression at E9 . 5 and E10 . 5 , respectively . At E11 . 5 , ETnII expression was noted in the condensing ulna/radius . Since there are 300–400 copies of type II ETn/MusD elements in the mouse genome , expression analyses likely reflect the contribution of expression from multiple genomic locations . Interestingly , this multiphasic , multiple tissue expression pattern could , in part , be related to the varied organ effects of the ETn insertion in Ppd mutant mice . For example , the ETn could ectopically activate Dusp9 in ES cells in association with the early burst of ETn transcription normally observed at E3 . 5 . In this situation , proximity to Dusp9 creates an opportunity for Dusp9 dysregulation consequent to the insertion of a transcriptionally activated ETn nearby . Potential interference with Dusp9 or other interval genes in specific tissues at later times is a natural hypothesis to examine as the etiology for malformations . It is intriguing that normal Dusp9 expression occurs later in development in other regions of the embryo as described [12 , 24] ( including the olfactory placode and nasal pit , somites and limbs ) that overlaps tissue malformations observed in some Ppd mutants: double snouts , spina bifida , and ulnar aplasia , syndactyly or hypodactyly [15] . Ppd mice strikingly resemble the mouse mutants Disorganization [38–41] and Duplicitas posterior [42–44] , as well as conceptuses exposed to the teratogen all-trans retinoic acid ( RA ) at pre-gastrulation stages , E4 . 5–E5 . 5 [45–48]; [Innis et al . , unpublished] . Ducks , cows , deer and other animals have also been reported ( not shown ) with similar Ppd-like , dramatic caudal or other ectopic limb duplications , suggesting that common fundamental vertebrate developmental pathways are susceptible to spontaneous mutations or environmental teratogens . Humans with ectopic lower limbs with and without pelvic anomalies or dipygus , have been described extensively in the literature [49–56]; all cases occurred sporadically , not unlike the occurrence of Ppd . Duplicitas posterior mice had varying pelvic masses and accessory limbs identical to Ppd mutants [42–44] . This mutation , which was never identified , arose on the stock carrying Sd , Danforth's short tail , had a penetrance of 20% in liveborn mice , caused prenatal death in some , and showed significant strain variation in penetrance and phenotype . Embryologically , Danforth noticed a thickening at mouse gestational age E11 of the “ventral tissues at the posterior end of the embryo in a region including , and extending in front of , the usual site of the cloacal pit” . The cloaca was noticed to widen out laterally and form two cloacal membranes , often resulting in two urethrae . Generally the mice had only 1 rectum , but occasionally two were observed , as might be expected from cloacal thickening . Duplicated pelvic bones , kinked tails , agenesis or hypoplastic kidneys ( suggesting interference with mesonephric duct development ) , microphthalmia and other anomalies were noted . These are quite similar to the defects we described for Polypodia mice [15] . Danforth also identified some mutants with double spinal cord at the lumbar/thoracic region and variations in between , as well as neural tube defects . Subsequent studies found a duplicate neural tube without notochord in some E11–E12 . 5 mutant pelvic masses suggesting bifurcation or budding off from the primary neural tube secondary to duplication of organizer tissue or the primitive streak , but this was not formally examined [44] . We have not observed duplicated neural tubes in Ppd mutants , although we have seen split tails and some spinal dysraphism on a few occasions on the genetic backgrounds presented . Unfortunately , Duplicitas posterior mice no longer exist ( E . Center , personal communication ) . The mouse mutant Disorganization ( Ds ) causes a wide variety of malformations in the mouse compatible with an early postimplantation patterning disruption . This mutation maps to mouse chromosome 14 . Ds mice share many malformations [38–41] in common with those of Polypodia , yet there are differences . Ds mice do not exhibit prenatal lethality , either as heterozygotes or homozygotes [40] . It will be interesting to compare the molecular pathways affected in both mutants . Exogenous retinoic acid ( RA ) , given at E4 . 5–E5 . 5 ( blastocyst stage ) , produces a mouse Ppd phenocopy . Such mouse conceptuses develop caudal limb and lower body duplications [45–48]; [Innis et al . , unpublished] , duplicated genital buds , facial defects and exencephaly . RA-treated embryos also display facial anomalies , which were not described in detail [45] , although these were more frequently observed when RA exposure occurred on E6–E7 . In most affected embryos , normal hindlimb development , single tails , and ectopic , ventral , rudimentary or complete lower limbs or caudal structures with or without duplicated pelvic structures are produced . The susceptible gestational times ( E4 . 5–5 . 5 ) correspond to post-implantation stages before gastrulation . Thus , provision of RA at E4 . 5–5 . 5 to pregnant dams clearly reorganizes the mouse body plan , and since RA is cleared within 12 hours of administration [57 , 58] the effect of RA is immediately confined to cells at pre-gastrulation stages . We believe that Ppd , Ds , and retinoic acid exposure at E4/5–E5 . 5 impact similar developmental pathways leading to caudal duplications and other malformations . Sporadic mutants for which coding alterations are elusive may be secondary to similar spontaneous insertions . However , it remains to be determined how Ppd and these other models intersect within known developmental pathways and at what developmental timepoint ( s ) . Moreover , the principles that influence penetrance , expressivity and pleiotropy in Ppd phenotypes are certainly relevant to human disease .
All mouse experiments were approved by the UM University Committee on the Use and Care of Animals , Protocol #07982 . Genetic crosses were carried out as described [15] . For narrowing the Ppd genetic interval , we genotyped visibly affected recombinant animals and utilized extended crosses ( offspring exceeding 80–100 animals for each ) of visibly unaffected CzechII/C3H F2 critical recombinants . Non-repetitive mouse genomic DNA segments were amplified by PCR and sequence verified to use as probes in Southern blots with ten micrograms of restriction enzyme digested mouse genomic DNA from wild-type and Ppd mutant mice . A 2212 bp Dusp9 probe , DUSP9 . 01 , corresponding to GRCm38 genomic coordinates ChrX:73641114–73643326 that includes Dusp9 gene sequences from the middle of intron 2 through most of the 3′ UTR of exon 4 , was amplified with primers 5′-GGGCACTTATCAGCCAAAGA-3′ and 5′-GGTGTGGACTGCAATGAATG-3′ . This DNA segment was labeled with 32P-dCTP and used according to standard Southern hybridization and washing protocols . ES cell genomic Southern blots were carried out as described [59] . X-chromosome specific primers used to amplify across the Ppd ETn as shown in Figure 2B were F1 ( 5′-AGCAAATGGTGGGACTGTGTAAT-3′ ) and R2 ( 5′-ACCCAGGACGATTGAAGATGTGC-3′ ) , which together generate a 1 . 278 kb product on wild-type DNA , but a 6 . 778 kb product including the ETn . Tail genomic DNA for genotyping was isolated by overnight proteinase K digestion , followed by extraction with phenol/chloroform/isoamyl alcohol and ethanol precipitation . Ppd mutation-specific PCR was performed using F5 ( X-chromosome specific ) and R6 ( ETn LTR ) primers that yielded a 248 bp Ppd-specific product in mutants . PCR success was assessed by including wild type forward and reverse primers in the same PCR that yielded a wild type product of 100 bp . Male Ppd mutant PCR yields only the 248 bp Ppd -specific product . F5 – 5′-TTACCAGGAGAAAGGACGCACTATGAG-3′ R6 – 5′-GCACCTTTCTACTGGACCAGAGATT-3′ WT Forward – 5′-TTGGGTCAAAGTTGAATGAAAATAGAAATAGC-3′ WT Reverse – 5′-CCCCGCCACTTCAGTGCTACC-3′ Thermocycling was carried out in 25 µL , 0 . 5 M betaine and 3 mM MgCl2 with an initial 2-min 97°C denaturation followed by 36 cycles of 97°C for 30 sec , 63°C for 30 sec and 72°C for 30 sec . The final extension was for 5 min at 72°C . Real-time RT-PCR was performed on an ABI Prism 7000 thermocycler ( Applied Biosystems , Foster City , CA . Gene-specific primers and probes were designed using Primer 3 program . Sequences for primers and probes for mouse Dusp9 , Pnck and β-actin are as follows: Mouse β-actin Forward Primer –AAGAGCTATGAGCTGCCTGA β-actin Reverse Primer – CAAGAAGGAAGGCTGGAAAAGAG Probe – 6FAMAACGAGCGGTTCCGATGCCCTGTAMRA Mouse Dusp9 Forward Primer – GGCATCCGCTATATCCTCAA Dusp9 Reverse Primer – GGGGATCTGCTTGTAGTGGA Probe – 6FAMCCCCAACCTTCCTAACCTCTTAMRA Mouse Pnck Forward Primer – CTCCCGGTTTTTCTTTCCTC Pnck Reverse Primer – ATGCATCACACCCAGTCTCA Probe – 6FAMTGGATCCTTGTCCTCCAGACTAMRA RNA was extracted using TRIzol reagent ( Invitrogen ) from at least three independent preparations of mouse ES cells , Ppd-ES cells and eETn ES cells . Each RNA sample ( 0 . 5 µg ) was tested in triplicate using TaqMan one-step RT-PCR master mix reagents from Applied Biosystems . Average cycle threshold ( CT ) was determined for each sample and normalized to β-actin . Relative gene expression ( using the formula 2−ΔΔCT ) was calculated using the comparative CT method , which assesses the difference in gene expression between the gene of interest ( Dusp9 ) and an internal standard gene ( β-actin ) for each sample to generate the ΔCT [59] . The difference of the ΔCT for each experimental cell line from the ΔCT the control cell line BRUCE4 . G9 is referred to as ΔΔCT . The average of the control sample ( BRUCE4 . G9 ) was set to 1 for each experiment , and the relative gene expression ( fold change ) for each experimental sample was compared with that . We obtained Ppd blastocysts by mating 24–28 day old pseudopregnant Ppd CD-1 ( >90% CD-1 ) females , recovering blastocysts at E3 . 5 by uterine flushing , and single-well plating on feeder cells . Following the identification of male cells carrying the Ppd ETn , we established mutant ES cell lines Ppd-D3 , Ppd-D5 , and Ppd-C4 . ES culture procedures were performed as described in [60] . Mouse ES cells were maintained on γ-irradiated mouse embryonic fibroblasts ( PTMN cells: pretreated , mouse embryonic fibroblasts , neomycin resistant ) in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with 15% fetal calf serum ( Atlanta Biologicals ) , 1000 U/ml LIF ( Millipore ) , 4 mM L-glutamine , 1% non-essential amino acids , 0 . 1 mM β-mercaptoethanol , 1% sodium pyruvate , and 1% penicillin/streptomycin . For RNA/DNA/protein analysis , ES cells were grown on gelatin coated plates without feeder cells , passed twice sequentially to eliminate PTMN feeder cell contamination , in DMEM with 15% fetal calf serum and 1000 U/ml LIF . RNA was isolated using TRIzol from ES cells after passage twice sequentially on gelatin coated plates without feeder cells . Biotinylated cDNA was prepared from 50 ng total RNA according to the Nugen ovation V2 kit protocol ( NuGen , Inc . ) . Following labeling , 4 µg of cDNA was hybridized for 16 hours at 45°C on GeneChip Mouse 430 2 . 0 arrays . GeneChips were washed and stained in the Affymetrix Fluidics Station 450 and then scanned with an Affymetrix 3000 7G GeneChip Scanner . Data quality analysis revealed no degradation and robust in vitro translation . Standard error estimates for each gene were derived and then standardized across all arrays , all of which showed high quality samples . A robust multi-array average ( RMA ) modeling strategy [61] was used to convert the PM probe values into expression values for each gene . Since we compared three normal ES cells lines to three Ppd ES cell lines , we used weighted linear models [62] , pooling information from all probe sets , to stabilize the variance estimate . Weighting was accomplished by a gene-by-gene algorithm that downweights samples deemed less reproducible [63] . We removed probe sets across sample comparisons ( Male WT versus Male Ppd ) that had a variance of less than 0 . 1 and then selected genes with a fold-change greater than 2 and an adjusted p-value ( adjusted for multiple comparisons using false discovery rate , FDR ) of less than 0 . 05 [64] . We used the Affy , AffyPLM and limma packages of Bioconductor in the R statistical environment . To place the ETn into a wild-type mouse genome , we first created a BAC library ( in vector pIndigoBAC5 ) from Ppd male genomic DNA utilizing the services of Bio S&T ( Lachine , Quebec ) and isolated 2 BAC clones spanning the Ppd ETnII insertion site on the X chromosome and surrounding genes spanning over 170 kb . We selected one clone ( Ppd BAC Clone 2 ) with a 170 kb insert and used BAC recombineering to construct a targeting vector through the UC Davis Mouse Biology Program ( http://mouse . ucdavis . edu/ineed/vectors_constructs . php ) . The strategy of construction began with the BAC . Ppd BAC Clone 2 was electroporated into EL350 and selection with chloramphenicol was used to isolate colonies . A frt-flanked PGK-Neo was inserted into the BAC just upstream of the 5 . 5 kb ETn insert via BAC recombineering and clones were selected with kanamycin ( PGK-Neo confers kanamycin resistance in bacterial cells ) , and chloramphenicol . The region containing the ETn , frted PGK-Neo , and 5′ ( 5 kb ) and 3′ ( 10 kb ) arms of homology was retrieved into a high-copy plasmid followed by selection with kanamycin and ampicillin ( retrieval vector confers Ampr ) . A Gateway reaction was then used to swap in the DTA negative selection marker followed by selection with kanamycin , which replaced the retrieval vector portion , and removed the Ampr cassette . Finally , a separate electroporation to isolate the targeting vector with the insertion followed by kanamycin selection was performed . Sequencing of all junctions created by recombineering revealed the expected insert structure . Sequencing of the 5′ ( 5 kb ) and 3′ ( 10 kb ) endogenous mouse genomic DNA arms of the targeting vector revealed not only the ETn , but also one common non-coding SNP , rs29038663 , a C>T substitution at ChrX:73646920 , 1 , 767 base pairs telomeric ( closer to the Pnck gene ) to the ETn . We targeted Bruce-4 . G9 and UMB6J-D7 ( a pure BL/6 line ) ES cell lines . Three hundred ES cell clones from each electroporation were picked and expanded . Southern blotting and Ppd ETn-specific locus PCR revealed a very high frequency of homologous recombination in both cell lines ( 27–50% ) . Germline transmission was successful in generating female engineered ETn ( eETn ) heterozygotes ( Neo+/eETn+ ) . We bred these females to β-actin FLPe males ( Jackson Lab stock #005703 ) , to remove the Neo cassette and obtained germline Neo−/eETn+ mutant mice for phenotypic analysis . Ppd-CD-1 mutant female mice were kept for overnight mating with a CD-1 WT male . Conception was defined by the presence of a vaginal plug the following morning , and the age of embryos calculated from midnight . Pregnant Ppd-CD-1 female mice were euthanized by carbon dioxide asphyxiation at E7 . 5 . Embryos were immediately dissected from the uterus in cold PBS under a dissecting microscope , and a portion of the ectoplacental cone and yolk sac were used for DNA isolation . Briefly , 20 µL alkaline lysis reagent ( 25 mM NaOH/2 mM EDTA ) was added to the tissue samples , and the mixture was incubated at 95°C for 20 minutes followed by neutralization using 20 µL 40 mM Tris-HCl . Genomic DNA was then used for genotyping using sex and Ppd genotyping . RNA was extracted from the embryos using Trizol reagent ( Invitrogen ) according to the manufacturer's instructions . Embryo sex was determined as described [15] using XX-XY forward and reverse primers that produce a ∼300 bp single product in females and a doublet in males . Thermocycling was carried out in 25 µL containing 0 . 5 M betaine and 3 mM MgCl2 with an initial 2-min 97°C denaturation followed by 36 cycles of 97°C for 30 sec , 63°C for 30 sec and 72°C for 30 sec . The final extension was for 5 min at 72°C . Primers: XX-XY forward: CCGCTGCCAAATTCTTTGG; XX-XY reverse: TGAAGCTTTTGGCTTTGAG . Ppd genotyping was as described above . ES cells grown on tissue culture plates were washed with phosphate-buffered saline ( PBS ) and lysed in 0 . 4 ml of ice-cold RIPA lysis buffer ( 1% sodium deoxycholate , 0 . 1% SDS , 0 . 15 M NaCl , 0 . 01 M NaH2PO4 , 2 mM EDTA , 0 . 5 mM NaF ) containing 2 mM sodium orthovanadate and 1∶1000 dilution of protease inhibitor mixture III ( Calbiochem ) . Protein concentrations were determined using the DC protein assay reagents from Bio-Rad ( Hercules , CA ) . SDS-PAGE and Western blot analysis were performed . Cell lysates were mixed with a 1∶5 v/v ratio of 6× gel loading dye ( 0 . 35 M Tris-HCl pH 6 . 8 , 30% glycerol , 10% SDS , 0 . 6 M DTT , 0 . 012% bromophenol blue ) and boiled at 95°C for 5 min to denature proteins . Sample mixtures were then loaded on 4–20% polyacrylamide gradient gels and subjected to electrophoresis . Proteins were electrophoretically transferred to a polyvinylidene difluoride membrane ( Immobilon–P , Millipore Inc . , Bedford , MA ) and incubated in 1× Tris-buffered saline ( pH 7 . 4 ) , 0 . 1% Tween 20 with 5% bovine serum albumin for 1 h at room temperature . The blot was incubated with 1∶1000 dilution of primary antibody in blocking buffer overnight at 4°C . Three washes with 1× TBS with 0 . 1% Tween 20 were performed prior to incubation with a secondary antibody conjugated to horseradish peroxidase . The washes were repeated five times , and the membrane was incubated with SuperSignal West Pico chemiluminescent substrate ( Thermo Scientific , Rockford , IL ) for 5 min . The blot was then exposed to chemiluminescent-sensitive HyBlot CL autoradiography film ( Denville Scientific Inc . , Metuchen , NJ ) . Image analysis was performed using a public domain NIH Image program available on the internet at rsb . info . nih . gov/nih-image . Sources of antibodies used in this study were as follows . Sheep anti-mouse DUSP9 polyclonal antibody , raised against two DUSP9 peptides ( residues 237–261 and residues 429–451; [24] ) was a gift from Dr . Robin Dickinson , University of Dundee , UK . From Santa Cruz Biotechnology ( Santa Cruz , CA ) : MKP-4 rabbit polyclonal antibody raised against a single DUSP9 peptide corresponding to residues 231–270 . From Bio-Rad: HRP conjugated anti-sheep secondary antibody . From Thermo Scientific ( Rockford , IL ) : Peroxidase conjugated goat anti-rabbit IgG and peroxidase conjugated anti-mouse IgG . Mouse monoclonal β-actin antibody was from Sigma . Synthesized peptides ( DUSP9 peptide 231–274 and a PNCK 30 amino acid peptide ) used in specificity assays were produced in the UM Protein Structure Facility . Tail samples were taken from 14 day old mice . Genomic DNA from an adult animal was used for comparison of LTR methylation between tail or other organ versus caudal ectopic mass . DNA was prepared from the samples and PCR was performed to confirm the presence of the ETn insertion . Once confirmed , the DNA was purified and treated with bisulfite using established protocols in the Qiagen EpiTect Bisulfite Kit . The bisulfite treated DNA ( btDNA ) samples were subjected to PCR using the primers EpiF4 ( 5′- GGTAAAAGAAGAAATGTAGTTAAGATAGTT-3′ ) targeting the modified LTR , and EpiR5 ( 5′- AAACTCCCCAAAACAAAACACTATA -3′ ) targeting the modified X chromosome sequences ( ChrX:73645196–73645220 ) upstream of the 5′ LTR . One reaction contained , 15 . 6 µL ddH2O , 2 . 5 µL 10× JumpStart PCR Buffer , 0 . 5 µL dNTP's , 1 . 25 µL Primer F4 , 1 . 25 µL Primer R5 , 0 . 4 µL JumpStart Taq , and 2 . 5 µL of 5 M Betaine . Each reaction also contained ∼200 ng of btDNA . The PCR program used was: 97°C ( 2 min ) , 97°C ( 30 sec ) , 46°C ( 30 sec ) , 72°C ( 1 min ) , Step 2 ( 40× ) , 72°C ( 10 min ) , 4°C ( ∞ ) . A second round of PCR was set up identical to the first , except 2 µL from the first round of PCR was used as the template for the second round PCR . No purification was necessary between PCR rounds . PCR reaction products were separated by electrophoresis on a 2% agarose gel . The bands were extracted and purified using a Qiagen Gel Extraction Kit . The PCR products were TA-cloned into a pGEM-T easy vector . The ligation was then electroporated into DH5α cells and plated onto LB agar with carbenicillin . Individual colonies were selected and grown overnight . Plasmid DNA from individual colonies was extracted and individual clones were sequenced in the University of Michigan DNA Sequencing Core with T7 and SP6 primers . Bidirectional sequences were scanned for the targeted CpG dinucleotide as well as unmethylated cytosine modifications . | Mobile genetic elements , particularly early transposons ( ETn ) , cause malformations by inserting within genes leading to disruption of exons , splicing or polyadenylation . Few mutagenic early transposon insertions have been found outside genes and the effects of such insertions on surrounding gene regulation is poorly understood . We discovered a novel intergenic ETnII-β insertion in the mouse mutant Polypodia ( Ppd ) . We reproduced the mutant phenotype after engineering the mutation in wild-type cells with homologous recombination , proving that this early transposon insertion is Ppd . Mutant mice are not born in expected Mendelian ratios secondary to loss after E9 . 5 . Embryonic stem cells from mutant mice show upregulated transcription of an adjacent gene , Dusp9 . Thus , at an early and critical stage of development , dysregulated gene transcription is one consequence of the insertion mutation . DNA methylation of the ETn 5′ LTR is not correlated with phenotypic outcome in mutant mice . Polypodia is an example of an intergenic mobile element insertion in mice causing dramatic morphogenetic defects and fetal death . | [
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] | [] | 2013 | A Novel Intergenic ETnII-β Insertion Mutation Causes Multiple Malformations in Polypodia Mice |
Several conditions associated with reduced gastric acid secretion confer an altered risk of developing a gastric malignancy . Helicobacter pylori-induced atrophic gastritis predisposes to gastric adenocarcinoma , autoimmune atrophic gastritis is a precursor of type I gastric neuroendocrine tumours , whereas proton pump inhibitor ( PPI ) use does not affect stomach cancer risk . We hypothesised that each of these conditions was associated with specific alterations in the gastric microbiota and that this influenced subsequent tumour risk . 95 patients ( in groups representing normal stomach , PPI treated , H . pylori gastritis , H . pylori-induced atrophic gastritis and autoimmune atrophic gastritis ) were selected from a cohort of 1400 . RNA extracted from gastric corpus biopsies was analysed using 16S rRNA sequencing ( MiSeq ) . Samples from normal stomachs and patients treated with PPIs demonstrated similarly high microbial diversity . Patients with autoimmune atrophic gastritis also exhibited relatively high microbial diversity , but with samples dominated by Streptococcus . H . pylori colonisation was associated with decreased microbial diversity and reduced complexity of co-occurrence networks . H . pylori-induced atrophic gastritis resulted in lower bacterial abundances and diversity , whereas autoimmune atrophic gastritis resulted in greater bacterial abundance and equally high diversity compared to normal stomachs . Pathway analysis suggested that glucose-6-phospahte1-dehydrogenase and D-lactate dehydrogenase were over represented in H . pylori-induced atrophic gastritis versus autoimmune atrophic gastritis , and that both these groups showed increases in fumarate reductase . Autoimmune and H . pylori-induced atrophic gastritis were associated with different gastric microbial profiles . PPI treated patients showed relatively few alterations in the gastric microbiota compared to healthy subjects .
Gastric adenocarcinoma is the third most common cause of cancer related mortality worldwide[1] and most cases are associated with chronic Helicobacter pylori infection . Gastric cancer usually develops via the premalignant condition of gastric atrophy , which is associated with the loss of acid-secreting parietal cells[2] . The resulting hypochlorhydria potentially leads to alterations in the composition of the gastric microbiota by providing a more favourable environment for colonisation . It is currently unclear to what extent the non-H . pylori gastric microbiota contributes towards gastric carcinogenesis . Although the hypochlorhydria associated with autoimmune atrophic gastritis also increases the risk of developing gastric adenocarcinoma[3] , it is more frequently associated with the development of another tumour , the type I gastric neuroendocrine tumour ( NET ) [4] . However , hypochlorhydria does not always increase the risk of gastric tumour development , as observed following chronic proton pump inhibitor ( PPI ) use[5] . Therefore , factors in addition to hypochlorhydria affect gastric cancer risk and one of these could be the gastric microbiota . Although originally thought to be sterile , several bacterial communities have been shown to survive in the normal human stomach[6] . Differences have also been observed depending upon H . pylori status[6] . There is now overwhelming evidence that certain bacteria influence cancer development . Potential mechanisms include altering the host immune system , exacerbating inflammation , or converting dietary nitrates to produce carcinogens such as N-nitrosamines and nitric oxide[7–13] . We therefore hypothesised that three stimuli which result in hypochlorhydria , namely H . pylori-induced atrophic gastritis , autoimmune atrophic gastritis and proton pump inhibitor use cause specific changes to the composition of the gastric microbiota . In addition , the gastric microbiota that is present in these conditions contributes towards the specific gastric tumour risk that is associated with each of these hypochlorhydric states . We have used 16S rRNA sequencing to determine the gastric mucosal microbiota profiles in patients with these causes of hypochlorhydria and have compared these with samples obtained from healthy subjects and from patients with H . pylori-induced gastritis , but no evidence of gastric atrophy .
Patients were selected from the larger cohort according to criteria defined in the methods section and Table 1 . Characteristics of the selected patients are shown in Table 1 and Fig 1A . One sample from the normal stomach group and four from the PPI-treated group were subsequently excluded because sequencing showed the presence of >15% H . pylori despite this organism being undetected by conventional clinical tests ( most likely due to the higher sensitivity of 16S rRNA sequencing compared to routine clinical tests ) . This is likely to be genuine H . pylori carriage since technical controls were included in each sequencing run and these controls showed lower diversity and levels of H . pylori than the samples ( Figs 2 & 3 ) . Ninety-five samples were therefore analysed . Negative extracts from the RNA extraction procedures , a water sample in the first PCR and a mock bacterial community were also sequenced . In total 10 , 386 OTUs were identified . Extraction controls contained fewer OTUs than the patient samples , whilst the mock communities showed consistency between MiSeq runs ( Figs 1–3 ) . Despite the negative extracts being theoretically sterile , as expected they generated 16S signals due to known background reagent contamination[14] . Samples from the autoimmune atrophic gastritis group contained the largest number of OTUs , whilst all other patient groups were comparable ( Fig 1B ) . Mock communities demonstrated the expected bacterial ratios ( Fig 3B ) . Twenty-three known phyla were identified , mainly Proteobacteria , Firmicutes , Bacteroidetes , Actinobacteria , Fusobacteria and Cyanobacteria . Bacteroidetes , followed by Proteobacteria and Firmicutes were most common in normal stomachs , whereas samples from PPI-treated patients contained slightly more Firmicutes and fewer Bacteroidetes . The H . pylori gastritis and H . pylori atrophic gastritis samples were dominated by Proteobacteria ( as Helicobacter itself is a member of this phylum ) , whilst biopsies from patients with autoimmune atrophic gastritis contained the largest proportion of Firmicutes compared to all other patient groups . Patients with H . pylori-induced atrophic gastritis and those receiving PPIs had similar fasting serum gastrin concentrations ( median 100pM and 140pM respectively ) , possibly suggesting similar degrees of hypochlorhydria ( although H . pylori infection may have directly contributed to the hypergastrinaemia in the former group ) . In contrast patients with autoimmune atrophic gastritis were associated with higher fasting serum gastrin concentrations ( median 800pM; Table 1 ) . No direct association between fasting serum gastrin concentration and bacterial taxa was observed between the different groups ( PERMANOVA Unifrac P = 0 . 512 , weighted Unifrac P = 0 . 721 and Bray-Curtis P = 0 . 556 ) . This is reflected in the evidence that patients with H . pylori-induced atrophic gastritis and those receiving PPIs exhibited marked differences in 16S rRNA microbiota profiles , co-occurrence networks and predicted pathways , despite similar gastrin levels . And that patients with autoimmune atrophic gastritis showed similarities to individuals with H . pylori-induced atrophic gastritis by predicted pathway analysis , despite markedly different serum gastrin concentrations ( S3 Table ) . Samples from patients with autoimmune atrophic gastritis contained significantly more Streptococci than all other groups ( Fig 3 & S1 Table ) . Streptococcus did not appear to be similarly increased in H . pylori-induced atrophic gastritis; this may have been due to the negative relationship observed between Helicobacter and Streptococcus identified in co-occurrence networks ( Fig 5C ) . Gastric biopsies from patients with autoimmune atrophic gastritis and those on PPIs both showed greater bacterial diversity than was observed in the stomachs of patients with H . pylori-induced atrophic gastritis ( Fig 2 ) . At the genus level , patients with autoimmune atrophic gastritis showed significant increases in Tannerella , Dorea , Streptococcus , Fusobacterium and Campylobacter compared to the patients with H . pylori-induced atrophic gastritis ( S4 Table ) . The stomachs of PPI-treated patients also contained significantly higher proportions of Fusobacterium and Campylobacter than the stomachs of H . pylori-induced atrophic gastritis patients . Furthermore , patients receiving PPI treatment showed significantly higher proportions of Flavisolibacter and Dermacoccus in their stomachs than autoimmune atrophic gastritis patients , but significantly less Paludibacter , Granulicatella , Streptococcus , and Neisseria . Patients who had atrophic gastritis due to H . pylori or an autoimmune aetiology both showed over-representation of several mutual pathways compared to controls ( S3 Table ) . However , differences between the two groups were also observed . For example , glucose-6-phosphate 1−dehydrogenase and D−lactate dehydrogenase pathways were over-represented in the stomachs of patients who had H . pylori-induced atrophic gastritis compared to those who had autoimmune atrophic gastritis ( S3 Table ) .
Our findings indicate that H . pylori colonisation and hypochlorhydria ( other than that which was caused by PPI treatment ) result in changes in gastric bacterial abundance and only rarely in loss/gain of bacteria . PPI treatment did not significantly alter the gastric microbiota from that of a normal stomach , despite serum gastrin concentrations being comparable to those found in patients with H . pylori-induced atrophic gastritis . Microbial patterns were not found to correlate with gastrin levels , although it should be noted that factors including H . pylori infection status may have confounded this relationship . Autoimmune atrophic gastritis resulted in a different , more diverse microbial pattern than that observed in the stomachs of patients who had H . pylori-induced atrophic gastritis . This may be due to differences in acid secretion between these conditions or other factors such as different immune profiles . Several biochemical pathways were represented in similar fashions in both atrophic gastritis groups . In particular , gastric-atrophy was associated with changes in the citric acid cycle ( biochemical pathway that is known to be associated with gastric carcinogenesis ) and our findings suggest that the microbiota may be an important contributor to this . The development of gastric cancer is multifactorial , and data from the present study suggest that the non-H . pylori microbiota may be a participating factor .
Acquisition of the biopsies used in this study was approved by Liverpool ( 08/H1005/37 ) and Cambridge East ( 10/H0304/51 ) Research Ethics Committees as previously described[37 , 38] . All patients gave written informed consent . One hundred gastric biopsy samples in 5 different groups were selected from a cohort of 1400 prospectively recruited patients who underwent diagnostic upper gastrointestinal endoscopy at Royal Liverpool University Hospital[37] and from 8 patients with type I gastric NETs who had been recruited to a clinical trial[38 , 39] ( Table 1 ) . The patients in the 1400 cohort had the following characteristics: Females 57 . 5% , median age 60 years with an interquartile range 48–70 years and 98 . 4% were Caucasian . Overall more than half the cohort ( 52 . 3% ) reported PPI use , 21 . 8% were positive for H . pylori infection by histology , and 43 . 3% were positive by serology . Patients were selected from this cohort according to the criteria described below and that are outlined in Table 1 . None of the selected patients were taking PPIs , except those in the PPI treated group . In some patient groups ( e . g . those with H . pylori associated atrophy and autoimmune atrophic gastritis ) all samples which matched the inclusion criteria were sequenced , but for other groups ( e . g . normal and PPI treated groups ) , subjects were chosen for inclusion based on the availability of tissue ( as biopsy samples from this cohort have also been used for other studies ) . Patients in the normal stomach group had a normal endoscopy , no evidence of H . pylori infection by histology , rapid urease test or serology , were not taking a PPI and were normogastrinaemic . Patients belonging to the H . pylori gastritis group were positive for H . pylori by rapid urease test , histology and serology , had no histological evidence of atrophic gastritis , were not taking a PPI and were normogastrinaemic . Patients in the H . pylori-induced atrophic gastritis group showed histological evidence of corpus atrophic gastritis and/or intestinal metaplasia , had no dysplasia or cancer , were positive for H . pylori by serology , were not taking a PPI and were hypergastrinaemic . Six out of the 23 patients in this group were also H . pylori positive by urease test and/or histology . Details of histological Sydney scoring [40] can be seen in S4 Fig . Patients in both H . pylori infected groups showed higher scores in both antrum and corpus than patients in the normal stomach and PPI treated groups . Patients in the autoimmune atrophic gastritis group had histological evidence of atrophic gastritis , no evidence of H . pylori infection by rapid urease test or histology , positive anti-gastric parietal cell and/or intrinsic factor antibodies , were markedly hypergastrinaemic and 8 out of 11 also had grade 1 type I gastric NETs . Patients in the PPI-treated group were currently taking PPIs , had no evidence of H . pylori infection by serology , rapid urease test or histology , had no histological evidence of atrophic gastritis and were hypergastrinaemic ( suggesting significant hypochlorhydria ) . At least two biopsies per site were obtained from the gastric antrum and corpus for histopathology . Eight additional corpus biopsies were stored in RNA later immediately after removal and were extracted using a modified Tri- reagent protocol[41] . Briefly , samples were thawed and separated from RNA later , before being homogenised in Tri-Reagent ( Sigma-Aldrich , Gillingham , UK ) . Chloroform was added and the resulting clear aqueous layer was combined with isopropanol before centrifugation to produce a precipitated RNA pellet . This was washed with 75% and 100% ice cold ethanol before being allowed to dry and then resuspended in diethylpyrocarbonate ( DEPC ) -treated water ( Sigma-Aldrich , Gillingham , UK ) . RNA was stored in ethanol at -80°C . Ethanol was removed and pellets were resuspended in DEPC-water prior to reverse transcription . Serum gastrin concentrations were measured by radioimmunoassay ( RIA ) as previously described[42 , 43] . Fasting serum gastrin concentrations were all <40pM in normogastrinaemic subjects and >40pM ( with the majority >100pM ) in hypergastrinaemic subjects . Samples and random primers were denatured together for 5 minutes at 65°C before Proto reaction mix and Proto enzyme from a ProtoScript II First Strand cDNA Synthesis kit ( NEB , E6560L ) were added . Samples were then incubated at 25°C for 5 minutes , 42°C for 20 minutes , and 80°C for 5 minutes . Newly synthesised cDNA was then measured using a Qubit high sensitivity assay ( ThermoFisher Ltd , Paisley , UK ) . The 16S rRNA gene was targeted using V1-V2 ( 27F and 388R ) primers[44] with slight modifications: forward primer 5'ACACTCTTTCCCTACACGACGC TCTTCCGATCTNNNNNAGAGTTTGATCMTGGCTCAG’3 , reverse primer 5’GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGCTGCCTCCCGTAGGAGT’3 . Primers were validated using a mock community described in supplementary methods . The following cycling conditions were used: initial denaturation 94°C for 5 minutes , followed by 10 cycles of denaturation at 98°C for 20 seconds , annealing at 60°C for 15 seconds , and elongation at 72°C for 15 seconds , followed by a final elongation step of 72°C for 1 minute . PCR amplicons were purified to remove excess primers , nucleotides , salts , and enzymes using the Agencourt AMPure XP system ( Beckman Coulter Ltd , High Wycombe , UK ) . Purified amplicons were used in a second PCR reaction with the same conditions except with 20 cycles . This second step was used to add dual index barcodes . The PCR amplicons were purified as above . All PCR reactions used Kapa HiFi HotStartStart 2× master mix ( Anachem Ltd , Bedfordshire , UK ) and all primers were used at 10μM . Amplicon sizes were checked using a fragment analyser ( Advanced Analytical , Ankeny , USA ) and size selection was performed using a Pippin prep ( Sage Science , Beverly , USA ) . The quantity and quality of the samples in the final libraries were checked using a SYBR Green qPCR assay and the Illumina Library Quantification kit ( Kapa ) on a Roche Light Cycler LC480II , according to the manufacturer's instructions . Prior to loading samples onto the MiSeq , PhiX was added ( 10–15% ) to increase diversity , and samples were then denatured with NaOH according to the Illumina MiSeq protocol . ssDNA library fragments were diluted to a final concentration of 8pM . 600μl of ssDNA library was loaded into a MiSeq Reagent Cartridge and a 500–cycle PE kit v2 was used . Paired-end sequencing was performed according to the manufacturer’s instructions ( Illumina , SanDiego , CA , USA ) . Sequence analysis methodology is described in the supplementary methods . Reads were submitted to EBI short-read archive accession-PRJEB21104 . Details are described in the supplementary methods ( S1 Text ) . | Different conditions such as autoimmune atrophic gastritis and Helicobacter pylori associated atrophic gastritis are associated with different types of gastric cancer , specifically neuroendocrine tumours and adenocarcinoma . Both conditions result in reduced gastric acid secretion , potentially allowing non-H . pylori bacteria to colonise the stomach . However patients receiving proton pump inhibitors ( PPI ) experience similar levels of acid secretion , but do not develop gastric cancer . The aims of this study were to investigate the contribution of non-H . pylori microbiota to gastric tumour development in the presence of reduced gastric acid secretion . 16S rRNA sequencing identified relatively few alterations in the gastric microbiota in patients receiving PPI therapy , despite reduced acid secretion , but more substantial alterations in those patents who had atrophic gastritis . Significant differences were also found between the patients who had atrophic gastritis of autoimmune and H . pylori associated types . Differences in biochemical pathways that potentially contribute to gastric tumorigenesis were also predicted . This work increases understanding of the mechanisms involved in gastric tumour development , and demonstrates how non-H . pylori bacteria may be important . This work may eventually lead to the development of novel chemopreventive therapies for stomach cancer that are based on altering the composition of the gastric microbiota . | [
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] | 2017 | Comparison of the human gastric microbiota in hypochlorhydric states arising as a result of Helicobacter pylori-induced atrophic gastritis, autoimmune atrophic gastritis and proton pump inhibitor use |
Despite half-a-century of research since the seminal work of Hubel and Wiesel , the role of the dorsal lateral geniculate nucleus ( dLGN ) in shaping the visual signals is not properly understood . Placed on route from retina to primary visual cortex in the early visual pathway , a striking feature of the dLGN circuit is that both the relay cells ( RCs ) and interneurons ( INs ) not only receive feedforward input from retinal ganglion cells , but also a prominent feedback from cells in layer 6 of visual cortex . This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing . It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields , i . e . , the suppression of the response to very large stimuli compared to smaller , more optimal stimuli . Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed , single-compartment and multicompartment neuron models of RCs , INs and a population of orientation-selective layer 6 simple cells , consisting of pyramidal cells ( PY ) . We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed ( ‘push-pull’ ) and phase-matched ( ‘push-push’ ) , as well as different spatial extents of the corticothalamic projection pattern . Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and , even more prominently , for patch gratings . This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells . The increased center-surround antagonism in the model is accompanied by spatial focusing , i . e . , the maximum RC response occurs for smaller stimuli when feedback is present .
Visual signals from the retina pass through the dorsal geniculate nucleus ( dLGN ) , the visual part of thalamus , on the way to the visual cortex . However , this is not simply a one-way flow of information: cortical cells feed back to both relay cells ( RCs ) and interneurons ( INs ) in the dLGN and thus shape the transfer of visual information in the circuit [1–6] . Although there is no broad consensus about the effects of cortical feedback on sensory processing , there are many experimental studies that provide insight into its potential roles [7–20] . For example , cortical feedback has been observed to switch the response mode of RCs between tonic and burst modes [21 , 22] and to synchronize the firing patterns of groups of dLGN cells [17] . Further , the studies have reported both enhanced and reduced responses of dLGN neurons from cortical feedback , and the functional role of cortical feedback is still debated [3 , 23 , 24] . One line of inquiry has addressed the question of how cortical feedback modulates the receptive-field properties of RCs . Cortical feedback was early shown to affect the length tuning of RC responses [12] , and a series of studies from Sillito and co-workers have investigated how cortical feedback influences the RC responses to flashing spots and patch gratings , i . e . , circular patches of drifting gratings [4 , 13 , 15 , 16 , 18 , 19] . Retinal ganglion cells ( GCs ) provide the feedforward input to the dLGN circuit , and the receptive fields of both GCs and RCs have a roughly circular shape where an excitatory center is surrounded by an inhibitory surround [25–27] . For a flashing-spot stimulus the maximum response occurs for a spot centered on the receptive field which exactly covers the receptive-field center [27] . When the spot size is gradually increased to also stimulate the inhibitory surround , the response is gradually reduced until the entire surround is also covered . This phenomenon is referred to as center-surround suppression , and it is known that such suppression is increased for RCs compared to the GCs that provide the dominant feedforward input [27] . A part of this increased suppression likely stems from feedforward mechanisms in the dLGN circuit , i . e . , a broad feedforward retinal input to LGN interneurons , in turn providing increased feedforward surround inhibition to the RCs [27 , 28] . Increased center-surround suppression implies that the neurons are less responsive to broad visual stimuli and instead more tuned to narrow stimuli or sharp spatial variations in the visual scene . Thus dynamical tuning of this suppression may be a mechanism for the nervous system to adapt to changing light conditions and viewing demands to create an efficient representation of the stimulus [29] . Although the receptive fields of dLGN cells appear largely determined by the feedforward retinogeniculate input , corticothalamic feedback has been shown to increase the inhibitory surround , i . e . , increase the suppression to very large stimuli [4 , 12 , 13 , 15 , 16 , 19 , 30] . Other studies have reported enhanced responses of dLGN neurons [18 , 30 , 31] when using smaller stimuli . Interestingly , cortical feedback has been experimentally observed to increase the surround suppression both for flashing spots [32] and patch gratings [4 , 19] , though , the increase has been found to be larger for patch gratings [2 , 4] . The topic of the present modeling study is to investigate what aspects of the thalamocortical loop , and in particular what type of cortical feedback pattern , may underlie these observed changes in RC center-surround antagonism . While the use of computational modeling to study the effect of cortical feedback on visual processing is not new , previous projects have investigated feedback effects on the temporal processing of RCs [33–38] . Modeling studies of spatial aspects have to our knowledge been limited to relatively simple firing-rate models [39 , 40] where , for example , dLGN INs have not been explicitly included . The focus in [39] was on exploring cortical feedback effects on observed effects of RC responses to discontinuity in orientations in gratings in bipartite stimuli . In [40] the extended DOG ( eDOG ) model was introduced , allowing for analytical explorations of effects of cortical feedback in certain settings , i . e . , with certain combinations of excitatory and ( indirect ) inhibitory feedback from ON- and OFF-center cortical cells onto RCs . In that study a preliminary use-case showed that a phase-reversed ( ‘push-pull’ ) arrangement of cortical feedback where ON-center RCs receive direct excitation from OFF-driven cortical cells and balanced indirect inhibitory feedback from ON-driven cortical cells , may provide increased center-surround antagonism . Here we instead consider a biophysically detailed model where RCs and INs , as well as orientation-selective layer-6 pyramidal cortical cells ( PYs ) , are explicitly included . The model is an extension of a recently developed network model of the feedforward part of the dLGN circuit [41] . The neuron models include a host of Hodgkin-Huxley type active conductances [42–44] , and an important feature is the multicompartment IN model that incorporates both axonal and triadic inhibition of RCs [45] . Another key element of our model circuit is the explicit incorporation of both ON-symmetry and OFF-symmetry cells which , unlike for the rate-based eDOG model [40] , allows exploration of a wide range of putative synaptic patterns for the feedback from cortical cells to RCs and INs , i . e . , both same symmetry ( ON to ON , OFF to OFF ) and cross-symmetry ( ON to OFF , OFF to ON ) . By comparing results from a wide range of feedback patterns , we find that our results support that a phase-reversed arrangement of the cortical feedback seems most effective in increasing the center-surround antagonism observed both for flashing spots and , even more significantly , for patch gratings .
The core of the network model comprises two-dimensional grids of synaptically connected dLGN and cortical neurons of ON and OFF receptive-field arrangements . The network is driven by dLGN neurons that receive spikes encoding visual input from the retina . The network includes populations of retinal ganglion cells ( GC ) , dLGN RCs and INs , and PYs of layer 6 in the primary visual cortex ( Fig 1 ) . Each layer is scaled to span a monocular patch of 10 deg × 10 deg in the visual field and contains 10 × 10 neurons of each symmetry type ( ON/OFF ) , except in the case of dLGN INs for which there are 25 per symmetry type ( 20% of the total number of dLGN cells [46] ) . Based on the wiring rules of the cat dLGN , it has been estimated that a 1 deg × 1 deg patch of the dLGN contains about 10 RCs of one symmetry type on average at an eccentricity of 7 deg [47] . Thus , one simulated RC in our model would correspond to about 10 RCs of the cat dLGN . In the tuning of the model , we have chosen model parameters giving GC and RC responses similar to the cat experiments described in [27 , 28] . Here the recordings were done on cells with receptive fields centered in areas of the visual field some distance away from the center of gaze ( area centralis in cat ) . Retinal GCs have a circularly symmetric center-surround receptive field that is inherited by dLGN RCs through one-to-one excitatory synapses as shown for cells of the ON and OFF pathways in Fig 1 . In these receptive fields , the center and surround present an antagonistic push-pull arrangement [48] . A bright stimulus confined to the center of the ON-cell receptive field or a dark stimulus placed on the surround of the receptive field evoke a depolarization of the ON cell . By contrast , an ON cell is hyperpolarized by projecting either a dark stimulus to the center of the receptive field or a bright stimulus to the surround . The opposite behavior applies for OFF-center cells . The feedforward elements of the dLGN are the same as in [41] . LGN INs receive input from four retinal ganglion cells via the triadic synapses and the proximal IN dendrites . RCs receive axonal inhibition through the IN axon and triadic inhibition by the IN dendrites at the triadic synapses , resulting in fast inhibition . The cortical populations of PYs receive strong input from an elongated area of three RCs of the same symmetry and weak input from an adjacent row of three RCs of the opposite symmetry . PYs come in two different orientation-selectivity variants: horizontally-selective or vertically-selective . Further , each of these two cortical populations also come with ON and OFF symmetry making a total of four distinct cortical populations . This is a simplified representation of the thalamocortical loop as it neglects that the strongest thalamic input to primary visual cortex arrives in layer 4 while the feedback inputs to dLGN cells come from cells in layer 6 . The models for the dLGN and cortical neurons are all biophysically detailed in the sense that they include a variety of Hodgkin-Huxley type active conductances explicitly reproducing generation of action potentials . The GC spiking mechanism is not modeled explicitly , instead this input is modeled by means of phenomenological filter models as in [41] . Conductance-based synapses were assumed , i . e . , I syn ( t ) = w f syn ( t - t s - t Δ ) ( V - E syn ) θ ( t - t s - t Δ ) , ( 10 ) for a presynaptic spike arriving at ts . Here the weight w is the maximal conductance of the postsynaptic receptors and Esyn is the reversal potential . fsyn is the temporal envelope of the synaptic conductance modeled as the difference between two exponential functions specified by time constants τrise and τdecay ( Eqs . 6 . 4–6 . 6 in [56] ) . tΔ is the conduction time delay from the generation of the presynaptic spike to the initiation of the postsynaptic response and was set to a fixed value of 1 ms for all synaptic connections . Action potentials of RCs , INs and PYs were detected by upward somatic voltage crossings at −10 mV . While AMPA receptors mediate all excitatory connections in this model , GABAA receptors mediate all inhibitory synaptic interactions . Parameters of synaptic connections are shown in Table 3 . Parameters of retinogeniculate and intrathalamic connections remain similar to those presented in [41] . An exception is the GC input to the IN part of the triad , for which we reduced the synaptic weight to compensate for the added excitatory input from corticothalamic connections not present in the previous model [41] .
Before studying the effects of cortical feedback on the RC response specifically , we describe the feedforward response of the different cell types in the network model when the cortical feedback is deactivated , i . e . , corticothalamic synapses from PYs to dLGN relay cells ( RCs ) and interneurons ( dLGN INs ) are disconnected . In this situation the RC response is driven only by excitation from its GC afferents and feedforward inhibition from INs . After exploring above the feedforward response of the different cell types in the network model , we now move on to investigate how cortical feedback to the dLGN circuit affects the spatial response properties of RC cells . This will depend on the detailed corticothalamic connectivity pattern which is not yet experimentally fully resolved . In the next sections , we thus present simulation results for the different alternatives considered in Fig 3 .
The main results from our model study were the area-response curves for flashing-spot and patch-grating stimuli , a commonly used measure of visual responses for cells in the early stages of the visual system [2 , 4 , 18 , 19 , 27 , 28 , 40 , 80 , 81] . We first considered the case with a rough balance between excitatory and inhibitory feedback so that the main effect of cortical feedback is on the shape of the area-response curves , not the magnitude ( Figs 10 and 14 ) . With a phase-reversed feedback arrangement a clear feedback-induced increase in surround suppression is observed both for flashing spots and patch gratings ( Fig 10 ) , as quantified by the center-surround antagonism coefficient α ( Eq 12 ) ( Table 4 ) . Such a feedback-induced increase of surround suppression has been observed in experiments with both flashing spots [32] and patch gratings [4 , 19] , although the effect appears more significant for patch gratings [2 , 4] . Our model results gave a larger increase of surround suppression for the patch-grating stimulus , but not as prominent as the increase reported by Sillito et al . [4] . With the same choice of parameters , a phase-matched feedback arrangement resulted in very little change in surround suppression for both types of stimulus ( Fig 14 ) . Increased surround suppression implies that RC cells in relative terms become more responsive to small stimuli and , thus , the cell more selective in spatial tuning . An additional effect of the phase-reversed feedback is the shrinking of the stimulus size giving the maximum responses in the area-response curves , clearly observed for the phase-reversed feedback , but largely absent for phase-matched feedback ( Figs 10 and 14 ) . We next did a parameter sweep , i . e . , investigated the effects of cortical feedback on the RC area-response curves for a wide range of different synaptic weights between PYs and dLGN neurons and for the different spatial feedback kernels ( 1 × 1 and 2 × 2 ) ( Figs 16–19 ) . The results for our two key area-response curve measures , the stimulus diameters giving the largest response and the center-surround antagonism coefficient α , were summarized in Fig 20 . A first observation was that both for flashing-spot and patch-grating stimuli , the phase-reversed and phase-matched cases gave very different dependency of the center-surround suppression , i . e . , center-surround antagonism coefficient α , on synaptic weights ( Fig 20A ) . For the phase-reversed case , high values of the center-surround antagonism coefficient were achieved by those parameter combinations that exert both strong excitation and ( indirect ) inhibition to the RC ( towards the bottom right corner ) . Here the ON-center inhibition and the OFF-center excitation both contribute to increasing the surround suppression . Thus large values of the surround suppression can be achieved even when excitatory and inhibitory effects are roughly balanced [18 , 83] . In contrast , for the phase-matched case , feedback-induced increases in the center-surround antagonism coefficient α required the inhibition to dominate the excitation . This reflects that the effects of ON-center inhibition and ON-center excitation in the feedback tend to cancel each other out . This is in accordance with the observation in Figs 10 and 14 where the area-response curve for the ‘inhibition-only’ case was seen to represent an intermediate case between the phase-reversed and phase-matched situations . When comparing the different spatial feedback patterns for the phase-reversed case , the 2 × 2 feedback pattern was seen to be more effective in increasing surround suppression in the RC response than the 1 × 1 . Incidentally , a spatially widespread feedback pattern has been suggested by anatomical studies of the innervation pattern of corticothalamic axons in the dLGN [63] . For flashing-spot stimuli only small variations in the diameters producing the maximal RC response were observed when varying the synaptic weights ( Fig 20B ) . However , for patch-grating stimuli a reduction was observed in the maximum-response diameter was observed when one or both types of cortical feedback were present . Other modeling studies have also investigated the effect of cortical feedback on spatial processing of RCs with different stimulus patterns [39 , 40] . The focus in [39] was on exploring the role of cortical feedback in modulating RC responses to discontinuity in orientations in gratings in bipartite stimuli . In [40] the extended DOG ( eDOG ) model was introduced , allowing for analytical explorations of effects of cortical feedback in certain settings , i . e . , with certain combinations of excitatory and ( indirect ) inhibitory feedback from ON- and OFF-center cortical cells onto RCs . There a preliminary use-case showed that a phase-reversed ( ‘push-pull’ ) arrangement of cortical feedback where ON-center RCs receive direct excitation from OFF-driven cortical cells and balanced indirect inhibitory feedback from ON-driven cortical cells , may provide increased center-surround antagonism . Our biophysical model and the above-discussed firing-rate models represent opposite extremes in terms of biological detail in LGN circuit models [86] . Models at an intermediate complexity level where the cells are modeled as integrate-and-fire neurons have also been used to explore cortical feedback effects on LGN cell [33–36] . However , these have focused on temporal response properties such as feedback-induced spike synchronization [35] , long-lasting correlations [36] and effects of feedback on visual latency [33] , not the spatial properties which has been the main topic here . An obvious next application of the present model would be to explore temporal response properties of LGN cells and , in particular , how these are affected by various types of cortical feedback . One line of inquiry would be to explore the relative roles of feedforward and feedback connections in shaping the temporal receptive fields of LGN cells , analogous to the questions addressed by the firing-rate models in [37] and [38] . Another line of research would be on studying spike synchronicity and correlations as addressed earlier with integrate-and-fire models [35 , 36] . A third line could be to explore in detail how the temporal structure of the PSTH , and in particular the ‘interval histogram’ of RC spikes , is affected by feedback [34] . In addition to feedback from cortex , both RCs and INs receive inhibitory feedback from neurons in the thalamic reticular nucleus ( TRN ) [5] . TRN neurons are thought to play a key role in the process of sleep spindle oscillations generated within the thalamic circuitry [42 , 43] . The TRN also contributes to the control of visual attention and awareness [87] , but the effects on procession of visual signals remain poorly understood [88] . TRN neurons do not receive direct input from the retina as LGN INs , instead they receive feedforward visual signals from collaterals of geniculocortical axons . TRN neurons also receive cortical feedback through corticothalamic axons , and their synapses on RCs are situated in close proximity to those of corticothalamic axons [1] . Given this organization of synaptic connections and its position within the network , TRN cells are likely to influence the transfer of visual information in a different manner than LGN INs . Modeling studies exploring the putative role of TRN neurons on visual processing have already been pursued [89] , and the present biophysical model could be extended to include also such neurons when more is known about these neurons and their possible role in visual processing . The present model assumes static synapses while a number of studies have demonstrated short-term plasticity in different synapses of the thalamocortical circuit , i . e . , short-term depression at the retinogeniculate [90 , 91] and geniculocortical [92 , 93] synapses , as well as in the feedback connection from cortex to INs [94] . In contrast , the feedback connection from cortex to RCs appears to be facilitating [90 , 95] . Such plasticity opens up for an even richer dynamical repertoire of the circuit , and would be an interesting topic for a future study using the present model with static synapses as a starting point . In particular , it would be interesting to explore if short-term synaptic plasticity could affect our prediction that phase-reversed cortical feedback is the most effective mechanism for increasing center-surround antagonism . dLGN cells have two different response modes , burst and tonic , suggested to relate of the animal [5 , 96 , 97] . Modulatory inputs from other parts of the brain may switch between these modes by shifting the baseline membrane potentials of RCs and INs . Tonic firing has been suggested to be more suitable for transferring visual information because it avoids nonlinear distortions created during burst firing , while burst firing was suggested to be best suited as an ‘alarm clock’ , i . e . , rapid stimulus detection [5] . Recent studies have demonstrated , however , that thalamic bursts can also contribute to sensory processing [98–101] . In the current study , our RC and IN models were based on data from dLGN neurons that rested on relatively depolarized membrane potentials , -60 mV and -63 mV , respectively , and fired predominantly in the tonic mode ( Fig 2 ) . An exploration of the functional roles of the two firing modes , and putative switches between them , would be another natural extension of the present work . The present model of primary visual cortex is obviously simplified . Cells in layer 4 of cortex are the main targets of projections from RCs , while the feedback from cortex to dLGN comes from cells in layer 6 . Even though there are also projections from RCs to layer-6 cells , there are likely cross-layer processing in cortex that affects the thalamocortical feedback loop and difficult to capture by a single-layer cortex model . Despite the model simplicity , the pyramidal-cell receptive fields produced by our network model ( Figs 4 , 12 and 15 ) are nevertheless seen to resemble the receptive fields of simple cells which also has been observed in layer 6 of cat visual cortex [102] . Thus the error introduced by our simplified cortical network model could be modest for the present application , but this needs further exploration when thalamocortical models including more comprehensive cortical circuitry becomes available . Further , there are several neural mechanisms that our simplified model of cortical orientation tuning does not account for , such as recurrent cortical excitation or horizontal inhibitory connections [58 , 103–105] , which can amplify a weak orientation bias . Although the area-response curves of cortical cells to the patch grating in Figs 8 and 9 showed a marked difference for gratings at preferred and non-preferred orientations , stimuli presented at non-preferred orientations did not suppress cortical response to the background rate as observed experimentally in some cells [106] . A stronger orientation selectivity of the cortical cells would likely affect the feedback-induced changes in RC response , but how , and to what extent , remains to be explored . While one option for extending the present model would be to add more neuron types to a single-layer cortex model , it might be tempting to aim to connect the present biophysically detailed model for the dLGN circuit with an equally detailed model for the primary visual cortex . However , at present such models are lacking , and a comprehensive model based on biophysical neuron models including both the dLGN and , say , V1 would anyway be computationally extremely demanding . An alternative could be to instead model V1 dynamics with simpler neuron models such as the Potjans-Diesmann network model based on integrate-and-fire neurons [107] . Experimental studies of cortical feedback effects on response properties in the dLGN have been ongoing for at least 40 years ( see , e . g . , [7] ) . However , a recurring challenge has been to reversibly remove cortical feedback in a controlled manner to compare physiological responses of dLGN cells with and without cortical feedback . Both cooling [11] and pharmacological manipulations [18] have been used . However , the advent of optogenetics now offers unprecedented opportunities for highly-controlled activation or deactivation of individual cell types . In [108] the role of layer-6 cells in providing gain control for the visual responses in the upper layers of mouse visual cortex was studied by such techniques . A similar study where visual responses of dLGN cells are measured while the corticothalamic cells in layer 6 are selectively activated or deactivated by photostimulation , would be most welcome for testing predictions of the present model . | The functional role of the dorsal lateral geniculate nucleus ( dLGN ) , placed on route from retina to primary visual cortex in the early visual pathway , is still poorly understood . A striking feature of the dLGN circuit is that dLGN cells not only receive feedforward input from the retina , but also a prominent feedback from cells in the visual cortex . It has been seen in experiments that cortical feedback modifies the spatial properties of dLGN cells in response to visual stimuli . In particular , it has been shown to increase the center-surround antagonism for flashing-spot and patch-grating visual stimuli , i . e . , the suppression of responses to very large stimuli compared to smaller stimuli . Here we investigate the putative mechanisms behind this feature by means of a comprehensive network model of biophysically detailed neuron models for RCs and INs in the dLGN and orientation-selective cortical cells providing the feedback . Our results support that the experimentally observed feedback effects may be due to a phase-reversed ( ‘push-pull’ ) arrangement of the cortical feedback where ON-symmetry RCs receive ( indirect ) inhibitory feedback from ON-dominated cortical cell and excitation from OFF-dominated cortical cells , and vice versa for OFF-symmetry RCs . | [
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] | 2018 | Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells |
Abscission is the final event of cytokinesis that leads to the physical separation of the two daughter cells . Recent technical advances have allowed a better understanding of the cellular and molecular events leading to abscission in isolated yeast or mammalian cells . However , how abscission is regulated in different cell types or in a developing organism remains poorly understood . Here , we characterized the function of the ESCRT-III protein Shrub during cytokinesis in germ cells undergoing a series of complete and incomplete divisions . We found that Shrub is required for complete abscission , and that levels of Shrub are critical for proper timing of abscission . Loss or gain of Shrub delays abscission in germline stem cells ( GSCs ) , and leads to the formation of stem-cysts , where daughter cells share the same cytoplasm as the mother stem cell and cannot differentiate . In addition , our results indicate a negative regulation of Shrub by the Aurora B kinase during GSC abscission . Finally , we found that Lethal giant discs ( lgd ) , known to be required for Shrub function in the endosomal pathway , also regulates the duration of abscission in GSCs .
Abscission is the last step of cytokinesis when sister cells linked by a thin cytoplasmic bridge become physically separated . It takes place on the side of an electron dense structure called the midbody that resides within the bridge . Unexplored for many years , this late step of cell division has begun to be characterized at the cellular and molecular level in the last decade as a result of recent advances in microscopy and genetic engineering [1] . Our understanding of abscission originates from studies carried out mainly in yeast and in mammalian cells in culture . However , features like the duration of abscission vary greatly from one cell type to another . It lasts a few hours in mammalian cells , while in sea urchin embryos , the completion of cell division only occurs during the S phase of the next cycle [2] . Abscission is completely blocked in germ cells of most species at some point during normal development [3] . How abscission timing is regulated in a developmental context remains however poorly characterized . During abscission , membrane scission happens at a secondary ingression point in the bridge that appears just before the cut [4 , 5 , 6] . At this site , microtubules overlapping in the bridge are severed by the AAA ATPase Spastin , and actin filaments are cleared by modifications of the lipid content of the membrane mediated by the PIP2-phosphatase OCRL [7 , 8] . A secondary constriction is thought to be formed and then abscised , by a set of proteins belonging to the Endosomal Sorting Complex Required for Transport-III ( ESCRT-III ) machinery and the vacuolar protein sorting 4 ( VPS4 ) . The subunits of the ESCRT-III complex , including CHMP4B , and the most downstream component VPS4 are relocated at the exact site of the cut just before abscission occurs [5 , 6] . The ESCRTs have the ability to self-assemble into spiral filaments , a structure that has been described beside the midbody that would allow membrane curvature and scission [1 , 9] . The timing of abscission depends on the local recruitment of the ESCRT-III machinery . This can only occur after mitotic exit when PLK1 gets degraded , and thereby allows the centrosomal protein 55 ( CEP55 ) to localize to the midbody [10] . This in turn permits the sequential recruitment of the ESCRT-I component TSG101 and ALIX , and finally the ESCRT-III machinery [11 , 12 , 13] . Although recruited by the ESCRT-I complex during Multi Vesicular Bodies ( MVBs ) formation , the ESCRT-II complex does not appear to be involved in abscission in mammalian cells . In mouse males spermatocytes , the binding of CEP55 to ALIX and TSG101 is inhibited , therefore abscission does not occur and a stable bridge is formed [14] . Abscission can also be blocked or delayed by the presence of lagging strands of DNA in the cytoplasmic bridge between two sister cells . Elegant work identified this checkpoint in yeast and mammalian cells , and demonstrated that it delays abscission until the lagging DNA bridges are resolved . It has thus been named the NoCut checkpoint . An important molecular player of this checkpoint is the essential mitotic kinase Aurora B [15 , 16] . Aurora B delays abscission by phosphorylating a member of the ESCRT-III complex , CHMP4C , a close paralog of the filament forming CHMP4B required for abscission [17 , 18] . Recent work suggests that this delay may be mediated by the retention at the midbody ring of the terminal effector of abscission Vps4 by CHMP4C and ANCHR proteins [19] . The temporal control of abscission is thus highly regulated by a complex molecular machinery that is still not fully understood . In addition , whether the conserved ESCRT machinery is regulating abscission in Drosophila has not yet been explored . Recently , we have used the Drosophila female germline to study abscission in a developmental context and in a genetically amenable system [20] . Drosophila germ cells regulate abscission differentially according to the developmental stage . Germline stem cells ( GSCs ) are located at the very anterior of region 1 of the germarium , in contact with somatic cells called cap cells and escort cells , which regulate their behavior[21] . Each stem cell divides asymmetrically to generate one stem cell , which stays in contact with cap cells in the niche , and a second daughter cell positioned outside of the niche . The daughter cell starts to transcribe the gene bam , which is necessary and sufficient to trigger the differentiation of the daughter cystoblast ( CB ) . This differentiation is characterized by four rounds of synchronous and incomplete divisions , giving rise to a cyst of 16 cells made of 15 nurse cells and one oocyte . In the resulting cyst , each cytokinesis is arrested and all sister cells share the same cytoplasm through ring canals . In contrast , cytokinesis between the GSC and the CB is complete . It is , however , very slow and GSCs and CBs remain linked at least until the following S-phase . The orientation and synchrony of these divisions are controlled by a germline-specific organelle , called the fusome , which is made of ER-derived vesicles ( Fig . 1A ) [21] . The fusome is partly inherited from the round spectrosome of the GSCs ( also made of ER-derived vesicles ) , and partly newly formed at the midbody during each division . Fusion between fusome precursors creates a continuum of vesicles penetrating each canal and connecting all the cells within a cyst . The fusome thus appears branched in dividing germline cysts . The fusome starts to degenerate and disappears when the germline cyst enters the meiotic zone or region 2 of the germarium [22 , 23] . In a genetic screen , we isolated the first mutations in aurora B and survivin , a regulatory subunit of the Chromosomal Passenger Complex ( CPC ) in Drosophila [20 , 24] . Using allelic series of gain- and loss-of-function of these genes , we demonstrated that the function of Aurora B as an abscission timer is conserved during the development of germline cells . Enhancing Aurora B activity delays abscission in GSCs and multiple divisions can occur before the preceding abscissions are completed . This leads to the formation of stem-cysts , a structure composed of several cells with stem cell-like properties still linket to the anterior GSC . In contrast , reducing Aurora B activity induces precocious abscission in GSCs and complete abscission in 2-cell cysts . A simple readout of these events is the number of germ cells per cyst . 32 cells or more per cyst are found when abscission is delayed in cyst , while 8 cells or less are observed in the case of a precocious abscission in the cyst [20] . In this study , we have analyzed the consequences of the loss of function of Shrub ( Shrb ) , the single Drosophila homolog of CHMP4 , on the development of the germline lineage . We found that Shrb was positively required for abscission , as mammalian CHMP4B; and it negatively regulated by Aurora B . In addition , we showed that Lethal giant discs ( Lgd ) , which is known to be required for Shrb function in the endosomal pathway , was also involved in GSCs abscission regulation .
We performed a pilot RNAi screen for mutants affecting the number of germ cells per egg chamber . Mutations in cyclin A , cyclin E or their regulators affect the number of germ cells by modifying the number of divisions . High levels of Cyclin A or mutations in encore induce the formation of egg chambers with 32 cells by triggering a fifth mitosis in cysts ( Fig . 1B ) [25 , 26] . In contrast , mutations in cyclinE or half-pint give rise to egg chambers with 8 cells due to only 3 divisions [27 , 28] . Recently , we showed that changing the duration of abscission could alter the number of germ cells per egg chamber without modifying the number of cyst mitosis . We showed that delaying abscission in GSCs induces the formation of cystoblasts made of two cells instead of one , which results in the formation of egg chambers containing 32 cells after four divisions ( Fig . 1C ) . In contrast , a faster abscission after the first cyst mitosis allows for the completion of cytokinesis in 2-cell cysts , and leads to the formation of two cysts of 8 cells after the remaining three divisions [20] . To find novel genes involved in these divisions , we used a collection of transgenic flies expressing shRNA designed to be efficient in germ cells ( TRiP collection , [29] ) . We selected 230 transgenic lines targeting kinases , phosphatases and regulators of membrane trafficking , and expressed shRNAs specifically in germ cells using a nanos-GAL4 driver . Three females were dissected for each line and ovaries were stained with Hoechst to count the number of cells . One line ( HMS01767 ) induced a high percentage ( 61% , n = 558 ) of egg chambers containing 32 cells . In these mutant egg chambers , the oocyte was linked to nurse cells by 5 ring canals instead of 4 indicating that the extra germ cells were not the result of packaging defects ( Fig . 1D-F ) . We also observed less penetrant phenotypes , such as binucleated cells , polyploid cells and a few egg chambers filled with tumor-like germ cells ( S1 Fig . ) . The HMS01767 line encodes a short hairpin RNA directed against shrub ( shrb ) . shrb encodes a subunit of the ESCRT-III complex and is the Drosophila homologue of Snf7/CHMP4 . We tested the specificity of the RNAi line by using several shrb alleles: shrbG5 , shrbO3 and shrbEY05194 . We could not recover any shrb homozygous mutant germ cells using the Flp/FRT technique . However , we noticed a high percentage of 32-cell egg chambers in flies heterozygous for these alleles: 27% ( n = 172 ) ; 32% ( n = 406 ) and 54% ( n = 342 ) of the egg chambers has 32 cells in the shrbEY05194/+ , shrbO3/+ and shrbG5/+ females , respectively . We concluded that the RNAi was specific and that the gene dosage of shrb was important to regulate the number of germ cells per egg chamber . The cyst goes through four rounds of mitosis in a subpart of region 1 that can be identified by the expression of the gene bam . bam is weakly expressed in cystoblasts and 2-cell cysts , increases in 4-cell cysts , and peaks at 8-cell cysts before being switched-off quickly[30] . In mutants inducing one extra round of mitosis , the bam-expressing region is expanded posteriorly , indicating that the corresponding gene acts during the cyst divisions . In contrast , in abscission-defects mutant giving rise to 32-cell cysts , the genes are required in the GSCs before the cyst divisions . To distinguish between both possibilities , we expressed RNAi against shrb differentially in GSCs and dividing cysts . nanos-GAL4 drives expression in all germ cells of the germarium , whereas bam-GAL4 only in dividing cysts ( Fig . 2A-B ) . We also expressed the same shRNA ( HMS01767 ) against shrb , driven by bam-GAL4 to test if shrb was required in dividing cysts to control the number of divisions . In the later conditions , all egg chambers had 16 cells ( 0% , n = 543 ) , in contrast to 80% ( n = 349 ) of 32-cell cysts when driven by nanos-GAL4 ( Fig . 2D ) . This result suggested that Shrb function is required in germ cells expressing nanos , but not bam , which are mainly the GSCs and a few pre-cystoblasts . To confirm this hypothesis , we combined nanos-GAL4 with a GAL80 repressor under the control of the bam promoter . In this background GAL80 repressed the activity of GAL4 in the bam expressing domain ( Fig . 2C ) ; as a consequence , UAS-shrb-RNAi was expressed only in GSCs and some pre-cystoblasts . In such ovaries , we found that 68% ( n = 303 ) of egg chambers had 32 germ cells . We concluded that shrb was required in GSCs to regulate non-autonomously the number of germ cells per cyst . The requirement for Shrb in GSCs rather than in cysts to regulate the number of germ cells strongly indicated that Shrb regulates abscission rather than the number of cyst divisions . We had previously shown that a delayed abscission in GSCs led to the formation of group of cells that remained connected by cytoplasmic bridges . We named these clusters “stem-cysts” as they express stem-cell markers but are linked by a branched fusome as found in germline cysts . We thus looked for such stem-cysts in nanos-GAL4; UAS-shrb-RNAi ovaries . We found that the fusome of mutant GSCs did not have a round or exclamation point shape as a regular GSC , but was instead branched and apparently passing through several cells ( Fig . 3A-B ) . Next , we examined p-Mad staining , a nuclear marker of GSC identity induced by Dpp signal secreted by the cap cells [31] . We found that the mutant GSC attached to the cap cells was positive for p-Mad , as in wild type , indicating that stem cell identity was not affected upon shrb loss of function ( Fig . 3A-B ) . In wild type GSC , Dpp signaling blocks the transcription of bam , which is necessary and sufficient for the differentiation of the cyst and therefore , Bam protein is not present in the GSC ( Fig . 3C-D ) [30] . We found that upon shrb loss of function , all the cells that were linked to the anterior most GSC by a fusome were devoid of Bam protein . Finally , Nanos protein is weakly expressed in control GSCs , and is completely lost in early differentiating cysts ( Fig . 3E ) [32] . Upon UAS-shrb-RNAi expression , we found weak expression levels of Nanos in the anterior GSC and in cells connected to it by a branched fusome ( Fig . 3F ) . We also observed clusters of cells with the same characteristics in ovaries heterozygous for shrbG5 and shrbO3 alleles . These groups of cells expressed Nanos but not Bam , like wild type GSCs . Moreover , they were also linked by a branched fusome like germline cysts ( S2 Fig . ) thus corresponding to our definition of stem-cysts . In addition , we found that the penetrance of stem-cysts formation was high 50% ( n = 558 ) for nanos-GAL4;UAS-shrb-RNAi , and 55% ( n = 342 ) , 41% ( n = 406 ) , 28% ( n = 172 ) , for germarium heterozygous for shrbG5; shrbO3 and shrbEY05194 , respectively . The high penetrance of stem-cysts was consistent with the high number of 32-cell cysts . Stem-cysts are formed by the synchronous divisions of GSCs and connected cells , while previous abscissions have not been completed . To test the synchronicity of GSCs with other cells , we first analyzed EdU incorporation after a 15 min pulse to mark the S-phase . In control condition , we found that GSCs and their daughter cystoblasts incorporated similar amount of EdU , indicating that they were still synchronized and connected as previously described [20 , 22] . However , we never detected additional neighboring cells labelled by EdU ( Fig . 4A , n = 45 ) . In germarium expressing shrb-RNAi , we observed that in addition to the anterior GSC and its direct neighbor , additional neighboring cells had incorporated EdU , indicating that all these cells had replicated synchronously their DNA ( Fig . 4B , n = 9 ) . These cells were all linked by a common fusome . To test if the synchrony of the cell cycle extended to M-phase , we used the mitotic marker pH3 . We found that in control conditions , GSCs always divided non-synchronously with their neighbors , including their daughter cystoblasts ( Fig . 4C , n = 27 ) . In contrast , in germ cells expressing shrb-RNAi , all cells linked to a GSC by a fusome exhibited similar levels of pH3 staining . This indicated that these cells were all performing mitosis synchronously ( Fig . 4D , n = 15 ) . Finally , to directly analyze cell cycle synchrony in stem-cysts , we used live imaging of heterozygous shrbO3/+ ovaries expressing an H2B-RFP transgene to label chromosomes , and G147 , a protein-trap insertion marking microtubules . We were able to follow 10 GSCs undergoing mitosis , and found that 4 of them were dividing synchronously with neighboring cells ( Fig . 4F ) . This result is consistent with the percentage of stem-cysts observed by immunostaining . Synchronous divisions were never observed in wild type control ( Fig . 4E , n = 21 ) . Altogether , these results demonstrated that cells within stem-cysts induced by shrb loss-of-function were cycling synchronously . The cell cycle synchronicity within stem-cysts suggested that these cells shared the same cytoplasm and that shrb loss-of-function induced a strong delay in abscission . To determine precisely when abscission took place in wild type and mutant conditions , we expressed a diffusible α-tubulin tagged with a photo-activatable GFP ( Tubulin-PA-GFP ) . Activation of the GFP in one cell allowed tracing labeled tubulin to the neighboring cell , and thus determining whether or not abscission had been completed . Indirect assays , using EdU incorporation , had already established that abscission between GSCs and cystoblast happens during or after S-phase in wild type condition [20 , 22] . To time more precisely abscission in GSCs , we used the shape of the fusome as a timer , as it has been shown to follow stereotypical changes during the different phases of the cell cycle [22 , 33] . We used germaria co-expressing Tubulin-PA-GFP with a UAS-Par-1-GFP transgene to label the fusome during live-imaging . We activated Tubulin-PA-GFP in one GSC with a brief pulse of a 2-photon laser , and recorded its diffusion to the attached cystoblast for each stage of the fusome cycle as defined in [33] . We observed diffusion of Tubulin-PA-GFP in the cystoblast only when the GSC and the cystoblast were visibly linked by a fusome ( n = 61 ) . We observed diffusion in GSC/CB pairs harboring a fusome shaped as a plug ( n = 2 , G1 phase ) , a bar ( n = 6 , G1/S phase ) , dumbbell ( n = 15 , S phase ) , fusing ( n = 16 , G2 phase ) and an exclamation point ( n = 22 , G2 phase , Fig . 5A , S1 Movie ) . However , we also observed some GSC/CB pairs linked by an exclamation point fusome , in which Tubulin-PA-GFP did not diffuse from GSC to CB ( n = 21 , Fig . 5B , S2 Movie ) . Tubulin-PA-GFP never diffused when the fusome was round ( late G2 phase , n = 13 ) . These results indicate that Tubulin-PA-GFP can diffuse from GSC to CB until the exclamation point stage of the fusome , i . e . mid-G2 phase . We thus established that in wild type condition , abscission between GSC and CB happens during mid-G2 phase ( Fig . 5 ) . We carried out the same experiment in shrbG5/+ mutant GSCs . We selected stem-cysts with at least three cells , including an anterior GSC , linked by a Par1-GFP positive fusome . We activated Tubulin-PA-GFP in the anterior GSC . We observed diffusion of Tubulin-PA-GFP in all cells of a single stem-cyst in 96% stem-cysts analyzed ( Fig . 5C , n = 27 , S3 Movie ) . This result demonstrated that cells within one stem cyst shared a common cytoplasm , and that abscission was almost never completed in GSCs , although scission eventually happened at other cytoplasmic bridges of stem-cysts . To analyze the dynamic localization of Shrb in germ cells , we generated an N-terminal fusion protein , GFP-Shrub ( GFP-Shrb ) , under the control of a UASp promoter to express it in GSCs and germline cysts with the nanos-GAL4 driver . In GSCs , we found that GFP-Shrb localized as dots along the fusome and at the transient ring canal linking the GSC and CB before abscission ( Fig . 6A ) . In mid-G2 phase , when the fusome adopts an exclamation point shape , we found that GFP-Shrb localized additionally to a strong focus at the site where the fusome splits . We hypothesized that this dot could be the midbody , and therefore co-stained ovaries for the midbody marker Pavarotti ( Pav ) , which is the Drosophila homologue of MKLP1 . We found a perfect co-localization of GFP-Shrb and Pav on this structure and on the surrounding ring canal ( Fig . 6B ) . This result indicated that GFP-Shrb localized at the midbody . At a later stage , when the fusome between the GSC and the CB is about to break , both Shrb and Pav disappeared from the shrunk ring canal , but remained co-localized at the midbody ( Fig . 6C ) . Similarly , after scission when the fusome is retracting to reform the typically round spectrosome in the GSC , Shrb and Pav co-localized at the posterior tip of the fusome ( Fig . 6D ) . In late G2 and mitosis , we occasionally observed midbodies co-stained by Pav and GFP-Shrb next to the spectrosome ( Fig . 6E ) . This dynamic behavior of GFP-Shrb is consistent with a function of Shrb in GSCs abscission , and with a recent report demonstrating that the midbody is asymmetrically inherited by the GSCs in ovaries [34] . We further observed that this asymmetric inheritance of the midbody occurs concurrently to the retraction of the fusome to reform a round spectrosome . In germline cysts of the mitotic region ( region 1 ) , we found that GFP-Shrb was almost not visible even in cytoplasmic vesicles ( S3 Fig . ) . In contrast , in meiotic cysts ( region 2 of the germarium ) , GFP-Shrb localized as bright dots along the fusome and at ring canals ( S3 Fig . ) . While studying the localization of GFP-Shrb , we noticed a weak but consistent appearance of 32-cell cysts in an otherwise wild type background . Depending on the expression levels of different insertions of UASp-GFP-Shrb transgenes , and using the same nanos-GAL4 driver , we observed between 4% and 15% of egg chambers with 32 cells . This result suggested that expression of GFP-Shrb could have a dominant-negative effect , as it gave the same phenotype as a loss-of-function of shrub . Alternatively , a high expression of Shrb could induce the same phenotype as a low expression . To distinguish between these alternatives , we expressed GFP-Shrb in a shrb heterozygous background . If GFP-Shrb acts as a dominant-negative allele , it should aggravate the 32-cell phenotype , while it should rescue it if GFP-Shrb is a functional protein . We found that the phenotype of 32-cell cysts decreased from 44% in shrbO3/+ ovaries to 12% in shrbO3/+ ovaries expressing GFP-Shrb ( S3 Fig . ) . We concluded that GFP-Shrb was not a dominant-negative allele , and that abscission was very sensitive to the levels of Shrb whether increased or reduced . Lgd is a tumor suppressor known to regulate endosomal trafficking and is a direct interactor of Shrb . In Drosophila and vertebrates , Lgd was shown to interact physically with Shrb via its DM14 domain . This interaction is required in flies for Shrub endosomal function [35] . In contrast , the mammalian homologue of Lgd was suggested to be an inhibitor of CHMP4B , a Shrb orthologue [36] . To assess the function of Lgd in germ cell abscission , we induced germline clones homozygous mutant for null alleles of Lgd . We found that 21% ( n = 270 ) of lgdd7 mutant egg chambers contained 32 cells ( Fig . 7A-B ) . Furthermore , we observed that 69% of lgdd7 mutant GSC formed stem-cysts ( Fig . 7C-D , n = 48 ) . We concluded that in the absence of Lgd , abscission is delayed in GSCs , and thus that Lgd is required positively for abscission to be completed . To investigate whether Lgd and Shrb act in the same pathway to regulate abscission , we performed genetic interactions between lgd and shrb alleles by crossing heterozygous shrbG5/+ flies with lgdd7 null allele . We found that the number of stem-cysts was significantly increased in shrbG5/lgdd7 ( 85% , n = 112 ) compared to shrbG5/+ ( 58% , n = 154 ) ( Fig . 7D ) . We concluded that Lgd and Shrb interacted positively for GSCs abscission . Surprisingly , we found that the number of egg chambers with 32 cells was reduced in double heterozygous flies . We counted 13% ( n = 901 ) of egg chambers with 32 cells in shrbG5/ lgdd7 flies , compared to 51% ( n = 980 ) in shrbG5/+ flies ( Fig . 7B ) . This negative genetic interaction between lgd and shrb suggested that Lgd might have another function in germline cysts . We concluded that Lgd and Shrb interacted positively in GSCs and negatively in germline cysts . In human cells , CHMP4A , B and C are three isoforms of CHMP4 , the vertebrate homologue of Shrb . Both CHMP4B and C regulate abscission timing in vertebrate cells , albeit with opposite activity . CHMP4B is known to regulate positively abscission , whereas CHMP4C can delay it [17 , 37] . The activity of CHMP4C is regulated by Aurora B ( AurB ) -dependent phosphorylation [17 , 18] . We previously showed that in flies , AurB negatively regulates abscission , and that abscission occurs precociously in GSCs and 2-cell cysts mutant for aurB . In contrast , increasing the activity of AurB leads to the formation of stem-cysts as observed in shrub loss-of-function [20] . Shrub was further shown to interact physically with Borealin , a regulatory subunit of the AurB complex [18] . We thus tested genetic interactions between shrbG5/+ flies and two null alleles of aurB , aurB2A43 and aurB3533 . Both single alleles aurB2A43 and aurB3533 have no phenotype when heterozygous ( Fig . 8A-B ) . We found that the number of stem-cysts in double heterozygous flies shrbG5/aurB2A43 ( 37% , n = 95 ) and shrbG5/aurB3533 ( 19% , n = 27 ) was greatly reduced compared to shrbG5/+ flies ( 60% , n = 172 ) ( Fig . 8A ) . Furthermore , the number of egg chambers with 32 cells was also rescued from 50% ( n = 1123 ) in shrbG5/+ flies to 25% ( n = 889 ) in shrbG5/aurB2A43 , and 14% ( n = 249 ) in shrbG5/aurB3533 ovaries ( Fig . 8B ) . These results demonstrated that AurB negatively interacts with Shrb during GSCs and germline cysts divisions .
The duration of abscission is developmentally regulated in different cell types . We have previously shown that negative feedback loops between two kinases , AurB and CycB/Cdk-1 , control the timing of abscission in Drosophila germline cells and in vertebrate cells in culture [20] . This mechanism is thus probably conserved in many different cellular contexts . In a genetic screen for genes regulating the number of germ cells per egg chamber , we found that loss of Shrb induced the same phenotype as the overactivation of AurB . Shrb seemed an interesting candidate as it is the Drosophila homologue of yeast SNF7 and mammalian CHMP4B/CHMP4C , which have been previously implicated in the regulation of abscission [17] . Furthermore , Drosophila Shrb was shown to physically interact with Borealin , a regulatory subunit of the AurB complex [18] . Interestingly , CHMP4B and CHMP4C have opposite effect on abscission; CHMP4B is a positive regulator of abscission , while CHMP4C delays abscission when phosphorylated by AurB [17 , 37] . Our results demonstrate that Shrb is a positive regulator of abscission in GSCs , as reducing Shrb levels delayed abscission and led to the formation of stem-cysts . In addition , we found that reducing AurB levels could rescue a reduction of Shrb levels for the formation of both stem cysts and 32-cell egg chambers . This negative genetic interaction indicates that a delay in abscission caused by lower levels of Shrb can be compensated by lower levels of AurB , which accelerate abscission . We also analyzed genetic interactions between shrb and lgd , as Lgd is known to be required for Shrub function in Drosophila [35] . Accordingly , we found that loss of lgd induced the formation of stem-cysts and 32-cell egg chambers . Furthermore , decreasing Lgd levels in a shrb mutant background increased the delay in abscission as shown by the higher number of stem-cysts . However , we observed surprisingly that the 32-cell phenotype was rescued in transheterozygous shrbG5/lgdd7 females . This result indicated that lgd and shrb interacted negatively in the cyst , contrasting with the positive interaction they showed in the GSC for abscission . We propose that lgd may have another function in the cyst that can compensate for shrb loss of function . We speculate that Shrub is required for the maintenance of the incomplete cytokinesis of the cyst cells . Reduced levels in shrbG5/ lgdd7 females would allow the presumptive 32-cell cysts originating from 2-cell precursors to break into two 16-cell cysts , as observed in aurB loss-of-function . The “rescued” 16-cell cysts could thus result from a combination of two successive phenotypes , delayed abscission in GSCs followed by a failure to maintain incomplete abscission in cysts at the oldest ring canal . Unfortunately , it is not currently possible to remove lgd function only in germline cysts to test this hypothesis . In addition , Lgd and Shrb are both involved in endosomal sorting , and their loss of function may therefore affect signaling pathways and other processes , complicating the interpretation of genetic interactions [38 , 39 , 40 , 41] . Indeed , we observed that loss of Shrb also induced additional phenotypes in ovaries , such as tumorous egg chambers . One remarkable finding of our study is the great sensitivity of abscission to the levels of Shrb . We observed a gradation in the penetrance of phenotypes depending on the levels of Shrb in the germline . A moderate overexpression of GFP-Shrb using the nanos-GAL4 promoter produced less than 15% of egg chamber with 32 cells . Removing one copy of shrb induced up to 60% of 32-cell cysts , and the appearance of polyploid germ cells in the germarium . These polyploid cells probably resulted from a complete failure of cytokinesis , and we interpret it as a stronger phenotype than the formation of stem-cysts . Stronger phenotypes were obtained by using shRNAs targeting shrub , with up to 80% of egg chambers with 32 cells , many polyploid cells and in addition , the formation of egg chambers containing tumor-like germ cells . Finally , we could not even obtained homozygous shrb mutant cells using the Flp/FRT technique indicating that Shrb is required for cell viability in the germline . The levels of Shrb thus appear to be essential for its proper functions , including the regulation of abscission timing in GSCs . In mammalian cells , the final step of abscission is thought to be mediated by the formation of 17 nm-diameter filaments spiraling from the midbody to the constriction zone . The formation of these filaments depends on the Shrb homologue , CHMP4B , and helices of CHMP4B have been described by structured illumination microscopy [6] . However , even though CHMP4B can form filaments in cells , the filaments formed in these CHMP4B over-expressing cells had only a diameter of 5 to 6 nm[42] . Therefore , it is tempting to speculate that the helical filaments observed during abscission are hetero-polymers , comprising other components in addition to Shrb/CHMP4B subunits . Changing the stoichiometry of these components by decreasing or elevating the levels of Shrb/CHMP4B may affect the ability of the subunits to form filaments of the proper diameter to perform abscission . This could explain why overexpression of Shrb or removing one copy of shrb can both lead to a delay in abscission . In mammalian cells , delay in abscission often induces the regression of the cytoplasmic furrow and the formation of bi-nucleated cells [16] . In contrast , we found that in Drosophila germ cells , abscission delay resulted in the formation of stem-cysts . In stem-cysts , we demonstrated that all cells shared the same cytoplasm as shown by the diffusion of Tubulin-GFP between ring canals . However , each cells remained individualized and only the most anterior cell , i . e . the cell in contact with the niche , had pMad translocated in the nucleus . This result could be explained if pMad cannot diffuse in the cytoplasm . This intriguing result could also be in agreement with the proposal that cells away from the niche are actively induced to differentiate by neighboring escort cells [43] . We speculate that posterior escort cells can promote the differentiation of distal cells in stem-cysts . Stem-cysts are formed by several rounds of mitosis of GSCs before the completion of preceding abscissions . These mitoses are synchronous and thus form stem-cysts of 2 , 4 or 8 cells . However , abscission is only delayed , and ultimately takes place at the oldest ring canals , releasing cystoblasts made of 2 or 3 cells . These multicellular cystoblasts then undergo the regular four mitosis giving rise to 32-cells cyst ( 2×16 ) originating from 2-cell cystoblasts; or 48-cell cysts ( 3×16 ) originating from 3-cell cystoblasts . In this study , we have only occasionally observed 48-cell cysts , obtained with a strong over-activation of AurB . Reduction of shrb or lgd mostly generated 32-cell cysts , originating from 2-cell CBs . In agreement , we found stem-cysts mainly formed of 4 cells . We can thus speculate that abscission takes about twice as long in these mutant conditions . In mammalian cells , the recruitment of ESCRT proteins to the midbody is tightly regulated in time to prevent premature abscission [1] . Intriguingly , we found that in Drosophila GSCs , GFP-Shrb localizes on the fusome long before abscission , and also later on at the midbody , which remains associated with the fusome . Since Shrub is present at the site of scission before abscission takes place , its activity must be inhibited to prevent premature abscission . Our genetic interactions between shrb and aurB suggest that AurB and the CPC could inhibit Shrb activity . There is still no evidence in Drosophila that AurB phosphorylates Shrb , as the residues phosphorylated by AurB in CHMP4C are not conserved in Drosophila Shrub . In contrast , it has been proposed that direct binding between Shrub and Borealin , a member of the AurB—CPC complex , could block Shrb activity by keeping Shrb in a closed conformation [18] . Consistent with this hypothesis , we have shown that Survivin , another member of AurB complex , is localized on the fusome in GSCs [20] . It is thus possible that precocious activity of Shrb in GSCs is prevented by its binding to the CPC on the fusome . Interestingly , we could barely detect GFP-Shrb on the fusome in dividing cysts when abscission remains incomplete . This indicates that Shrb levels are regulated developmentally , and that there is a correlation between the absence of Shrub protein on the fusome and incomplete cytokinesis in germline cysts . Furthermore , GFP-Shrub was expressed using the exogenous nanos-Gal4 promoter ( i . e . not under the endogenous transcriptional regulation ) indicating that Shrub is regulated at the protein level . This raises the exciting possibility that the absence of Shrb in dividing cysts may block abscission in differentiating germline cysts . Elegant works performed in the mouse testis have shown that TEX14 blocks abscission in spermatogonia [14] . There is no homologue of TEX14 in Drosophila , and what blocks abscission in the differentiating cysts remains a major question in the field . We believe that elucidating how Shrb protein levels are regulated in the fly germline cyst may help understand how incomplete cytokinesis is controlled .
The Drosophila alleles or transgenes used in this study are HMS01767 ( TRiP line; [29] ) ; shrbG5 and shrb03 [41]; shrbEY05149 ( Bloomington Stock Center ) ; H2B-RFP [44]; G147 [45]; UASp-tubulin-PA-GFP [46]; lgdd7 [47]; lgdEY04750 ( Bloomington Stock Center ) ; aurB2A43 and aurB3533 [20]; UASp-par1-GFP[48] . Overexpression experiments were performed using the Gal4/UASp system [49] with the nanos-GAL4-VP16 [50] or the bam-GAL4 [51] drivers . We generated the bam-GAL80 construct ( see later ) , and combined it with a nanos-GAL4 driver devoid of VP16 activation domain ( a kind gift of M . Fuller ) . The germline clones were generated using the Flp/FRT technique [52 , 53] . Clones were induced by heat-shocking third instar larvae at 37°C for 2 hours , females were dissected 2 days after eclosion . To generate the bam-Gal80 construct , we synthetized a 3886 bp DNA fragment encoding the bam promoter ( −898 to +133 , between 5’ AGATCTAACCATTGATTAAC 3’ and 5’GATTTGTGTGATTTAACTTA 3’ ) , the Gal80 coding sequence ( 5’ ATGGACTACAACAAGAGAT 3’ to 5’ TCTCGCATTATAGTTTATAA 3’ ) and terminated by the K10 terminator , between Not1 sites ( eurofins/MWG ) . The NotI fragment was then cloned into pCasper vector . To generate the pUASp-GFP-shrb construct , we subcloned the shrb fragment from a pDONR221 vector for Nter fusion construct ( a kind gift from Pier Paolo D’Avino; [18] ) by LR recombination to pPGW destination vector . Transgenic lines were generated by BestGene . Antibody staining and Hoechst staining were performed according to standard protocols . Briefly , ovaries were dissected in PBS , fixed in 4% PFA , permeabilized in PBT ( PBS-0 , 2%Triton ) for 30 min , left overnight with primary antibodies in PBT at 4°C , washed 2 h in PBT , left with secondary antibody for 2 hrs at room temperature , washed 1 h in PBT and mounted in Cityfluor . The primary antibodies used in flies were the following: mouse-anti-α-spectrin ( clone 3A9 , DSHB ) 1:500; rb anti-α-spectrin 1:1000 [54] , rat-anti-BamC 1:1000 [30]; rb-anti-Nanos 1:200 [55]; rb-anti-pSMAD 1:100 ( a king gift of Peter ten Dijke ) ; rb-anti-Pav 1:150 [56] , rb-anti pH3S10 1:1000 ( Upstate ) . Fluorescent secondary antibodies were from Jackson Immunoresearch; rhodamin-phalloïdin and Hoechst were from Molecular Probes . For Edu treatment ( Click-iT Edu Imaging kit , Invitrogen ) , ovaries were dissected in Schneider medium complemented with 10% FBS . There were then incubated at 25°C for 15 min in 20μM Edu in Schneider medium+ 10% FBS . Edu detection was performed according to manufacturer’s instructions . The number of cell per egg chamber was quantified on DAPI and Rhodamin-phalloïdin stained ovaries . We counted the number of nuclei with the DAPI staining . In addition , the number of ring canals stained by phalloïdin was counted for the oocyte so that chambers formed of 32 cells having 2 oocytes with 4 ring canals each ( due to encapsulation defects ) are not included . Quantification of the percentage of egg chambers having more or less than 16 cells were done on one day old females . Chi-square tests were used to compare the proportions of egg chambers having 16 or 32 cells . Stem-cysts quantification was done on germaria immunostained with alpha-spectrin antibody; stem-cysts were identified as a group of 3 cells minimum , linked by a fusome , with its most anterior cell being attached to the niche . The percentage of germaria exhibiting at least one stem-cyst was counted . Chi-square tests were used to compare the percentages observed in the different genotypes . Acquisition of Z-stacks on fixed sample was carried out on Zeiss LSM710 or LSM780 confocal microscopes . For quantification of egg chambers with 16 or 32 cells , ovaries were analyzed with a Upright Widefield Leica Microscope . For live imaging of germarium in Fig . 4 , ovaries were dissected and mounted in oil ( 10S , Halocarbon , Sigma ) and were imaged with an inverted Confocal Spinning Disk Roper/Nikon equipped with a CCD camera CoolSnap HQ2 . Time-lapse images were then treated with Fiji . For the photo-activation experiments of Fig . 5 , ovaries were dissected and mounted in oil ( 10S , Halocarbon , Sigma ) . Photo-activation was done with a 2-photon laser at 820nm ( 3 iterations , laser power 15% , scan speed = 6; these numbers are rough approximations for the excitation power ) . Imaging was done with a confocal microscope Zeiss LSM 710 . | Abscission is the final step of cytokinesis which allows the physical separation of sister cells through the scission of a thin cytoplasmic bridge that links them at the end of mitosis . The duration of abscission varies depending on cell types , indicating that the event is developmentally regulated . Recently , we have identified two kinases , Aurora B and CycB/Cdk-1 , which regulate the timing of abscission in germ cells and in mammalian cells . However , these kinases are upstream regulators and do not perform abscission per se . Here , we show that Shrub , a potential target of Aurora B and one of the most downstream effectors of abscission , is required for complete abscission in germline stem cells . In the absence of Shrub , the mother stem cell remains linked to its daughter cells , which then share the same cytoplasm and cannot differentiate . Loss of Shrub and Aurora B have opposite effects on abscission duration suggesting that Aurora B regulates negatively Shrub . We further show that Shrub acts together with its interactor Lethal giant disc to ensure proper abscission timing . | [
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] | [] | 2015 | Abscission Is Regulated by the ESCRT-III Protein Shrub in Drosophila Germline Stem Cells |
The native-like , soluble SOSIP . 664 trimer based on the BG505 clade A env gene of HIV-1 is immunogenic in various animal species , of which the most studied are rabbits and rhesus macaques . The trimer induces autologous neutralizing antibodies ( NAbs ) consistently but at a wide range of titers and with incompletely determined specificities . A precise delineation of immunogenic neutralization epitopes on native-like trimers could help strategies to extend the NAb response to heterologous HIV-1 strains . One autologous NAb epitope on the BG505 Env trimer is known to involve residues lining a hole in the glycan shield that is blocked by adding a glycan at either residue 241 or 289 . This glycan-hole epitope accounts for the NAb response of most trimer-immunized rabbits but not for that of a substantial subset . Here , we have used a large panel of mutant BG505 Env-pseudotyped viruses to define additional sites . A frequently immunogenic epitope in rabbits is blocked by adding a glycan at residue 465 near the junction of the gp120 V5 loop and β24 strand and is influenced by amino-acid changes in the structurally nearby C3 region . We name this new site the “C3/465 epitope” . Of note is that the C3 region was under selection pressure in the infected infant from whom the BG505 virus was isolated . A third NAb epitope is located in the V1 region of gp120 , although it is rarely immunogenic . In macaques , NAb responses induced by BG505 SOSIP trimers are more often directed at the C3/465 epitope than the 241/289-glycan hole .
The induction of neutralizing-antibody responses against human immunodeficiency virus type 1 ( HIV-1 ) is the objective of vaccine programs based on various soluble envelope glycoprotein ( Env ) trimers ( reviewed in [1–12] ) . The prototype native-like recombinant Env trimer is the BG505 SOSIP . 664 construct , which is based on a clade A env gene [13–16] . This trimer , like many subsequent ones of similar design from multiple genotypes , mimics the native structure of the Env spikes on the surface of HIV-1 virions that are targeted by neutralizing antibodies , NAbs [15 , 17–20] . Accordingly , native-like trimers such as BG505 SOSIP . 664 are used in vaccine development programs aimed at eliciting NAbs , particularly those with broad activity against diverse HIV-1 strains ( i . e . , bNAbs ) . Although the BG505 SOSIP . 664 and other native-like trimers express the epitopes for multiple bNAbs , they do not elicit such antibodies in rabbits or macaques [21–25] . It is well known that antigenicity does not equal immunogenicity: the presence of a bNAb epitope on an Env trimer does not ensure that NAbs will be raised against it [3 , 4 , 26–28] . It is difficult to test and compare many early generation immunogens in humans , because of the high costs and complex , time-consuming procedures required for producing clinical-grade proteins [29 , 30] . To determine the immunogenicity of a trimer , antibody responses induced in animals are quantified and the targeted epitopes are mapped . To date , BG505 SOSIP trimers have most often been studied in rabbits and macaques . And , although macaques are genetically closer to humans , rabbits are less expensive and more readily available . In both species , the trimers induce NAbs against the autologous , neutralization-resistant ( Tier-2 ) BG505 . T332N virus , but generally not against heterologous Tier-2 viruses [21 , 23–25 , 31–34] . BG505 virus mutants have been used to map the autologous NAb epitopes in sera from trimer-immunized rabbits and , on a smaller scale , macaques [23–25] . Thus , we reported that a hole in the glycan shield of the BG505 virus , centered on residues S241 and N289 , is a frequent target for autologous NAbs induced in rabbits , but we also inferred that a substantial minority of the immunized animals raised NAbs against additional , unknown epitopes [23] . Rabbit monoclonal antibodies ( MAbs ) against that 241/289-glycan-hole site have been characterized [35] . But little is known about the epitopes for autologous NAbs induced in trimer-immunized macaques . Some evidence suggests that the 241/289-glycan hole is targeted in a subset of macaques , although less often than in rabbits [24] . Here , we designed and used a much larger panel of BG505-env pseudo-viral mutants to delineate these known and unknown rabbit and macaque NAb epitopes . We first selected a panel of 15 rabbit sera in which the autologous NAbs are known to target , or not , the 241/289-glycan-hole site [23] . The serum panel and the new env mutants enabled us to identify a second epitope cluster on BG505 Env trimers that is frequently targeted by rabbit NAbs . This site involves a stretch of the gp120 C3-region that is known to have been under selection pressure in the HIV-1-infected infant from whom the BG505 virus was isolated [13 , 16] . The site is also blocked by knocking-in a glycan at residue 465 , near the junction of the V5 loop with the β24-strand . Furthermore , two sequence changes in the gp120 V1-region affected neutralization by two of the 15 rabbit sera in the test panel , and probably identify a third NAb epitope . Several other sequence changes directly or indirectly affected how potently the rabbit sera neutralized the BG505 pseudo-virus . We then found that NAbs in sera from 15 BG505 SOSIP trimer-immunized macaques were predominantly directed at the C3/465 epitope cluster . Overall , the autologous NAb response to the BG505 SOSIP trimer is complex . As noted previously , it is not restricted to a single hole in the glycan shield at positions 241/289 [23] . Our refined knowledge of the targets for BG505 SOSIP trimer-induced NAbs may inform the design of new immunogens that are better able to elicit bNAbs .
The sera used in the present analysis were derived from a published experiment exploring the immunogenicity of BG505 SOSIP . 664 trimers in rabbits [23] . There , we inferred that , while around half of the immunized rabbits produced NAbs targeting the 241/289-glycan hole on the BG505 . T332N virus , the NAb response in the remainder recognized one or more unknown sites [23] . For more precise mapping , we therefore selected a panel of 15 high-titer sera that represent the spectrum of recognition of the 241/289-glycan hole ( Fig 1A ) . Specifically , the 4 sera ( r5726 , r5747 , r5749 , r5725 ) in Group-1 represent the dominant subset in which neutralization is eliminated by the single and double N241/N289-glycan-knock-in ( KI ) changes , the 6 sera ( r5739 , r5743 , r5744 , r5723 , r5727 , r5738 ) in Group-2 have reduced titers against those 241/289-glycan-KI mutants , and the 5 sera ( r5724 , r5742 , r5741 , r5740 , r5751 ) in Group-3 have intact titers against them ( i . e . , the NAbs target a different site ) . Note the sera in these three groups were chosen in order to identify unknown epitopes: the number of sera in each group ( 4 vs . 6 vs . 5 ) does not reflect the relative frequency of their neutralization profiles in a larger set of sera from trimer-immunized rabbits ( see Discussion ) [23] ) . In Fig 1A , the sera are ranked ( top to bottom ) by their sensitivity to the N241-KI/N289-KI mutant , as reported by the ratio of the mutant over the parental ID50 values ( i . e . , the relative ID50 , RID50 , see Methods ) . We found no strict relationship between immunization history and the serum neutralization titers against the N241-KI/N289-KI mutants ( BG505 only vs . BG505 and B41 immunizations , RID50 for N241-KI , p = 0 . 79; N289-KI , p = 0 . 16; N241-KI/N289-KI , p = 0 . 42 ) but we detected marked correlations between these titers and the absolute titers against the parental BG505 . T332N pseudo-virus ( N241-KI , r = 0 . 63 , p = 0 . 014; N289-KI , r = 0 . 60 , p = 0 . 020; N241-KI/N289-KI , r = 0 . 63 , p = 0 . 015 ( Fig 1A ) . Hence , although the 241/289-glycan hole is the dominant target for NAbs in many rabbit sera , NAbs against the yet uncharacterized subdominant epitopes are more potent or present at higher concentrations . We tested the 15 selected sera against the parental and 141 BG505 . T332N mutant viruses ( plus two clones and one mutant derived from the maternal MG505 virus , S1 Table ) and then analyzed the clustering among the ranked sera of effects on neutralization . The relative neutralization titers of 50 glycan-knock-out ( KO ) or knock-in ( KI ) ( S1 Fig ) and 55 non-glycan ( S2 Fig ) mutants are shown in the SI . The resulting 1575 serum-virus combinations yielded sporadic examples of increased or decreased neutralization titers . The generally null outcomes of this large body of tests strengthen the significance of what was seen with the selected virus mutants that are discussed below . In Fig 1 and subsequent figures with rabbit data we also show the effect of the mutations on neutralization by two MAbs , 11A and 11B , which were previously isolated from BG505 trimer-immunized rabbits and target the 241/289-glycan hole [35] . These results are described separately below . First , we investigated whether adding mutations of residues nearby the N241-KI or N289-KI changes ( P240T , F288L and T290E ) created viruses that were more strongly resistant to the Group-2 or resistant at all to Group-3 sera ( Fig 1B ) . Additional reductions in neutralization titers were rare , and the multiply mutated viruses were still neutralized potently by 4 out of 5 Group-3 sera . We infer that some NAbs in Group-2 sera and most in Group-3 are directed at epitopes elsewhere on the trimer . We next identified mutants with neutralization profiles resembling those of the N241-KI and N289-KI mutants ( Fig 2A and 2B , compare with Fig 1A ) . Two of these were the N230-KI mutant and a double mutant , K229N/K232T , which involves the two adjacent residues but without adding a glycan site ( Fig 2A ) . Combining the K229N/K232T changes with the P240T and N241-KI mutations , either with or without the N230-KI mutations , had little additional effect: in particular , the potencies of the Group-3 sera against these combination-mutant viruses were unchanged for 4 out of 5 rabbits ( Fig 2A ) . Two glycan-KO mutants , N88-KO and N625-KO , and 4 non-glycan point mutants , E268A , N279A , N280A and V518A , were usually strongly resistant to Group-1 sera but sensitive to at least 4 out of 5 Group-3 sera ( Fig 2B , again compare with Fig 1A ) . In addition , the two mutations at adjacent residues , N279A and N280A , increased the neutralization potency of multiple Group-3 sera . The distinctive profiles of specific mutants again suggest that NAb specificities differ among the three serum sub-groups . Structural modeling showed that the glycan added by the N230-KI mutation could project into the 241/289-glycan hole epitope and potentially restrict antibody access to it ( Fig 2C ) . ( Fig 2C ) . The model also indicated that residue E268 is located in the center of the 241/289-glycan hole , which accounts for the impact of its mutation ( Fig 2C ) . Residue V518 , in the gp41 fusion peptide ( FP ) , is further away , but a substitution here could indirectly affect the bottom of the glycan-hole epitope ( Fig 2C ) . Alternatively , some FP residues might directly contribute to an extended epitope centered on the 241/289-glycan hole . The predicted orientations of the glycans knocked-in at positions 230 , 241 and 289 are shown in Fig 2D . A set of BG505 . T332N mutants were generally resistant to the Group-3 but sensitive to the Group-1 sera , i . e . , sensitive to NAbs targeting the 241/289-glycan hole ( Fig 3A ) . The N465-KI mutant ( derived from MG505 cl . H3 ) , which has a glycan knocked-in at residue 465 at the junction between the V5 loop and the β24 strand , was strongly discriminatory . Other mutations at residues nearby in the primary structure had sporadic positive and negative effects on neutralization but lacked this discriminatory neutralization profile ( N461-KI , N462-KO , see S1 Fig ) . For the full panel of 15 sera , the relative titers against the N241-KI/N289-KI mutant correlated inversely but strongly with those against the N465-KI mutant ( r = -0 . 78 , p = 0 . 0010 ) . This inverse correlation supports what is apparent from a visual comparison of Figs 1A and 3A; the comparison also indicates that residue T465 is involved in the NAb-epitope cluster recognized by Group-3 sera , which is distinct from the 241/289-glycan hole target for Group-1 ( Figs 1A , 2A , 3A and 3B ) . The C3 region of gp120 is under selection pressure during human infection with the BG505 virus [13 , 16] , and we had found that this region influences neutralization by sera from BG505 trimer-immunized rabbits [25] . Accordingly , we designed a set of C3-mutant viruses . Several of them , including G354E , N356-KI , I358A , R360I and N356-KI/R360I , had neutralization profiles similar to that of the N465-KI mutant , suggesting a linkage among them ( Fig 3A ) . Structural modeling showed that these C3 residues and residue T465 are clustered , and that an N465-KI mutation could plausibly occlude access to an epitope ( Fig 3B and 3C ) . Thus , we describe a new BG505 NAb site that we term “the C3/465 epitope . ” A key role for residues I358 and R360 in the C3/465 epitope was further emphasized by the neutralization profile of the K241S mutant of the maternal MG505 cl . A2 virus , which closely resembled the profiles of the C3/465 mutants ( RID50 values for both the clone and mutant in relation to the comparator BG505 . T332N virus are given in Fig 3A ) . The cl . A2 virus was generally resistant to the panel of 15 sera , but its K241S mutant was fully sensitive to all 4 Group-1 sera , to 4 of the 6 Group-2 sera and to one Group-3 serum ( Fig 3A ) . Thus , the loss of the bulky lysine chain at position 241 permits NAb binding to the epitope in the 241/289-glycan hole , but does not confer sensitivity to the C3/465-directed NAbs . Furthermore , we noted that the only differences between the MG505 cl . A2 and BG505 . T332N viruses among the residues listed in Fig 3A are at positions 358 and 360 . Specifically , the N356-KI ( I358T ) and R360I mutations introduce the cl . A2 residues into the BG505 . T332N virus . The resulting single and double mutants were generally resistant to Group-3 sera ( Fig 3A ) . We consider it relevant that these two neutralization resistance-associated sequence differences arose naturally between the maternal and infant viruses [13 , 16] . Two further C3-region mutants , G354E and N356-KI , behaved similarly to the others that define the C3/465 site . Based on the neutralization and structural analyses , we propose that the new NAb epitope cluster is centered on residues I358 and R360 and includes a small glycan hole lined by residue T465 , which is adjacent to the N462 glycan ( Fig 3B ) . The I396N substitution also preferentially reduced the titers of Group-3 sera , although only partially ( Fig 3A ) . The spatial proximity of residue I396 in V4 to residue I358 in C3 explains its impact , while the weaker effect of the G354E mutation suggests that this residue is located at the periphery of the epitope ( Fig 3B ) . Neutralization titers of Group-2 sera were reduced by the mutations affecting either epitope cluster ( Figs 1A , 2A and 3A ) ; one serum in Group 3 , r5751 , although potent against the N241KI/289KI mutants , resembled Group 2 in other aspects ( Figs 1B , 2A , 2B and 3 ) . These sera may contain NAbs against both parts of an extended 230/241/289-glycan-hole epitope cluster and the newly identified C3/465 epitope . Alternatively , individual NAbs in these sera recognize an epitope cluster that is affected by mutations at either of these two sites , although it is not obvious from the structural models where it could be located . Two V1-region mutants and the corresponding double mutant of BG505 . T332N were largely resistant to the Group-2 sera r5743 and r5744 ( Fig 4A ) . The 133aN and 136aA mutations ( derived from MG505 cl . H3 ) insert single residues in V1; 133aN moves the N133- glycan site one position C-terminally ( S1 Table ) . The local V1 sequence in the parental BG505 . T332N virus is TNVTNN and in the 133aN/136aA double mutant it is TNNVTNAN ( the two inserted residues are highlighted in bold and underlined ) . The same two sera were also the only ones able to neutralize MG505 cl . A2 ( the RID50 values relative to BG505 T332N are given in Fig 4A ) . The MG505 cl . H3 virus , which was not neutralized by any of the 15 sera , differs from cl . A2 in having the 133aN and 136aA insertions ( Fig 4A ) . And when these cl . H3-derived 133aN and 136aA insertions were introduced into the cl . A2 V1 region , the resulting mutants resembled cl . H3 in being fully resistant to sera r5743 and r5744 ( Fig 4A ) . Likewise , when introduced into BG505 T332N comparator , they conferred resistance only to these two sera . Taken together , these data provide evidence for a NAb epitope somehow involving V1 residues N133 and N136 . We also note that neutralization of the BG505 . T332N virus by the r5743 and r5744 sera was little affected by the N465-KI and related C3 mutations , reinforcing the argument that these two sera are targeting an atypical epitope in addition to the 241/289-glycan hole ( Fig 3 ) . The V1 neutralization epitope , however , appears to be inconsistently immunogenic , as only these two Group-2 sera among the 15 tested were affected by the 133aN and 136aA mutations . The structural locations of the V1 residues are shown in Fig 4B . The above evidence is consistent with the existence of three autologous NAb epitopes on BG505 Env trimers . To strengthen the argument , we designed virus mutants on which the epitopes were simultaneously mutated . Some of the resulting combination mutants , particularly those including the N289-KI mutation , were poorly infectious and were not studied further , but we identified five that could be tested against the panel of 15 sera . Specifically , combining the N241-KI mutation with N465-KI or with the N356-KI or R360I changes in C3 or with I396N in V4 created viruses that were generally and strongly resistant to all three sub-groups of rabbit sera ( Fig 5A ) . Of note is that the two Group-2 sera with specific sensitivity to V1 changes , r5743 and r5744 , had moderately reduced titers against the above combination mutant viruses , but they did not neutralize the N241-KI/N465-KI double mutant when the 133aN and 136aA V1 insertions were added ( Fig 5A ) . Again , this finding supports the existence of a NAb epitope that includes or is influenced by the stretch of V1 residues around positions N133 and T136 . The locations of the three autologous NAb epitopes on the BG505 SOSIP . 664 trimers are depicted in Fig 5B . As positive controls for sensitivity to 241/289-KI mutations , and as tools for determining the polyclonal NAb specificities in the sera , we used two rabbit MAbs , 11A and 11B , which have been reported to target the 241/289-glycan hole [35] . The neutralization activity of both MAbs was eliminated by the N241-KI and N289-KI mutations and by almost all the other changes that predominantly affected the Group-1 sera ( Figs 1 and 2 ) . The potency of MAb 11B was , however , also somewhat reduced by the N465-KI mutation that predominantly affected neutralization by Group-3 sera ( Fig 3A ) . In contrast , the C3 mutations that reduced the titers of the Group-3 sera did not reduce the neutralization potency by either MAb; the N356-KI and I358A mutations increased their potencies . Unlike the Group-1 and most group-2 sera , MAbs had markedly reduced potency against the cl . A2 K241S mutant . The V1 mutation 133aN reduced neutralization by MAb 11B , whereas the V1 mutants sporadically enhanced the activity of Group-1 sera ( Fig 4A ) . Finally , neither MAb neutralized the viruses with the pan-resistance mutations ( Fig 5A ) . The MAb epitope mapping study yields several insights . First , the reductions in serum neutralizing titers caused by multiple , widely dispersed mutations cannot necessarily be attributed to antibody poly-specificity . For the MAbs also had complex neutralization profiles that could only be explained by a combination of direct and indirect effects of some mutations on their epitopes . Second , since the epitopes of these MAbs and their angles of binding have been determined by electron microscopy [35] , their neutralization profile helps identify the epitopes targeted by the polyclonal sera . The MAbs generally resembled the Group-1 sera in their mutant recognition patterns . But MAb 11B differed in that it was moderately sensitive to the N465-KI mutation , although not to the C3 changes that also define the C3/465 epitope ( Fig 3A ) . Since the glycan knocked-in at residue-465 is quite distant from the 241/289-glycan-hole core epitope for these MAbs , the moderate effect of the N465-KI mutation is plausibly indirect ( see Discussion ) . We purified IgG from 15 sera derived from four different exploratory studies of the immunogenicity of BG505 SOSIP trimers in macaques ( see Methods ) . The IgGs were first tested against three key BG505 . T332N mutants identified by the rabbit serum analyses outlined above . The N241-KI mutation did not reduce neutralization by any of the 15 IgG preparations , while the N289-KI mutation conferred moderate resistance in only two cases . In contrast , the N465-glycan-KI change reduced the extent of neutralization for all 15 IgG preparations , albeit only moderately in five cases ( Fig 6A ) . Sufficient IgG was available from 10 monkeys for a more detailed analysis ( Fig 6B ) . The N241-KI/N289-KI double mutant behaved similarly to the two single mutants in that it was moderately resistant to two of the 10 samples , which further indicates that the 241/289-glycan hole is not strongly immunogenic in macaques ( Fig 6B ) . In contrast , the C3 mutations N356-KI and R360I and the V4 change I396N reduced neutralization by all or most of the macaque IgGs; these mutants generally tracked the N465-KI just as they did with the rabbit sera ( Fig 6B , compare with Fig 3 ) . For 4 of the 10 IgG preparations , the N241-KI/N465-KI mutation had somewhat less impact than the single N465-KI change ( Fig 6B ) . Furthermore , the N156-KO mutation , which did not reduce neutralization by any of the rabbit sera , did reduce it by 4 of the macaque IgGs ( Fig 6B , compare with S1 Fig ) . The immuno-dominance of the C3/465 epitope over the 241/289-glycan hole was confirmed by the RAUC method , which , however , registered ~10–20% fewer neutralization-reducing effects of C3/465 mutations ( S3 Fig ) . Finally , the various mutations other than N241-KI and N289-KI that reduced neutralization by rabbit Group-1 sera , and the V1 mutations that affected two Group-2 sera , did not markedly reduce neutralization by the macaque IgG preparations ( Fig 6B , compare with Figs 2B and 4 ) .
Here we have epitope-mapped the NAb responses to BG505 SOSIP trimers in rabbits and rhesus macaques . We previously reported that the 241/289-glycan hole accounted for the NAb response in over half of the BG505 SOSIP . 664 trimer-immunized rabbits [23] . That rabbit MAbs elicited by this trimer bind at this site confirms that this epitope is immunogenic in the rabbit [35] . We can now expand this epitope cluster to the region around residue D230 , because knocking in a glycan at this position has nearly the same effect as the N241-KI and N289-KI mutations . Of note is that all rabbits immunized with the clade B trimer B41 SOSIP . 664 raised NAbs that were blocked by the N289-KI mutation [23] . By analogy to the BG505-epitope mapping , whether NAbs induced by the B41 trimer are also affected by mutations other than the N289-KI change should now be investigated . We previously noted that the 241/289-glycan hole was not the entire story: a substantial proportion of the trimer-immunized rabbits raised NAbs that targeted one or more additional epitopes [23] . We now show that one such NAb epitope involves a stretch of the C3 region ( around the β14 strand ) , and that a glycan added at residue T465 strongly shields this epitope . Residue T465 is located at the junction of V5 and the β24 strand [36] . One caveat about the 465-KI mutation is that it can have a modest effect on the 241/289-glycan hole epitope , as judged by data on MAb 11B ( Fig 3A ) . As the C3/465 and 241/289-glycan hole epitopes do not abut ( Fig 5B ) , an indirect impact of the knocked-in glycan on the accessibility or structure of the latter epitope is probably responsible . Such an effect should be borne in mind in the future use of this particular mutant . The mutations in C3 , however , lacked these apparent distant effects , and therefore the C3 mutants more definitively characterize the epitope . The contribution of C3 residues to the C3/465 epitope is consistent with the observation that the C3 region was under immune selection pressure in the human infant from whom the BG505 virus was isolated [13 , 16] , and with our earlier , more limited epitope mapping based on an Env protein with C3-sequence changes ( the 7C3-mutant ) as a competitor in NAb assays [25] . The C3 region is also the target of early , narrow specificity NAb responses in people infected with clade C HIV-1 strains [37 , 38] . Indeed , despite its designation , the C3 region is not strictly conserved in all clades . The original classification of this Env segment as conserved was based on sequence comparisons within clade B , but C3 is more variable in viruses from other clades and may be widely targeted by NAbs during HIV-1 infection [39–42] . The V1 region near residues N133 and N136 was involved in neutralization by two of the 15 rabbit sera tested . This site is probably included in an additional , infrequently immunogenic NAb epitope on the BG505 SOSIP trimer . Its spatial relationship to the other two autologous NAb epitopes is shown in Fig 5B . As noted earlier , we selected the rabbit sera in Groups-1 , -2 and -3 solely to define new epitopes . Therefore , the group sizes do not reflect the proportions of sera with the same properties across a non-selected group . We previously described sera from 30 BG505 SOSIP . 664-trimer-immunized rabbits [23] . Applying the current titer-based analysis to these sera suggests that the 241/289-glycan hole is the dominant target in ~50% of the animals and the C3/465 epitope in ~25%; the other 25% of the sera with intermediate profiles may contain NAbs against both epitopes . We found no evidence that NAbs in any of the rabbits are directed solely to V1 epitopes; no matter how they act , the V1 sequence changes affect the overall neutralization capacity in only ~10% of the animals . We detected marked correlations between the relative titers against the N241-KI or N289-KI mutants and the absolute titers against the parental BG505 . T332N pseudovirus . The 241/289-glycan hole-directed NAbs have a severely limited breadth of neutralization against heterologous Tier-2 and -3 viruses because glycans are frequent at these positions [23] . The higher neutralization titers associated with responses to the C3/465 epitope are therefore noteworthy , as conserved elements of this site may represent a more negotiable route to neutralization breadth . We observed many examples , particularly glycan-KO mutatants , of increased neutralization sensitivity . It is possible that the removal of the glycans , or other sequence changes , permits NAb access to nearby but otherwise cryptic immunogenic epitopes . Or these neutralization-sensitizing mutations may allosterically render the virus more sensitive to NAbs against the 241/289-glycan hole or C3/465 epitopes . Another explanation , however , is that they act by increasing the accessibility of V3 or other epitopes for otherwise non-neutralizing antibodies . But a change in the Tier status of the BG505 . T332N virus from Tier-2 to Tier-1 would presumably enhance neutralization by the vast majority of these rabbit sera . Additional studies would be required for a more definitive account . Our analyses of BG505 SOSIP trimer-immunized macaques reveal that the 241/289-glycan hole is not the major NAb epitope in this species , as it was targeted only in a minority of animals . In an analysis of a different set of sera from various BG505 SOSIP trimer-immunized macaques , N241-KI and N241-KI/N289-KI mutants were moderately resistant in , respectively , one and six out of nine cases ( and the N332T mutant in one of nine cases ) ; no other NAb epitope was identified [24] . Differences in immunizations and analyses probably account for the modest differences in the frequency and extent to which the 241/289-glycan hole was apparently targeted in the two studies ( see also SI section ) . Here , we show that the dominant epitope in the macaque is the C3/465 site . The macaque differs , therefore , from the rabbit , not in the identity of the BG505 Env epitopes to which it mounts NAb responses but in the relative frequency with which it does so against the different epitopes . We do not think that such a difference precludes the use of rabbits in preclinical studies of BG505 trimer variants , although , all other things being equal ( which , from a practical and financial perspective , they are not ) , the macaque would be our preferred model . Whether the detailed immunogenicity profiles of trimers derived from other HIV-1 genotypes vary between species remains to be determined; but that they might vary should be borne in mind when animal immunization studies are designed and interpreted . Finally , on the reasonable assumption that , immunologically , humans resemble macaques more than they do rabbits , we propose that the dominant autologous NAb response in BG505 SOSIP . 664 trimer-immunized humans will be against the C3/465 epitope . This hypothesis may eventually be testable [29] . We sought improved knowledge of the autologous NAb responses to BG505 SOSIP trimers to facilitate the design of immunogens yielding greater neutralization breadth . During HIV-1 infection , broader responses sometimes evolve over a multi-year period after the initial narrowly specific autologous NAbs that appear in the first few weeks to months . A single immunogen , such as a BG505 SOSIP trimer , may be able to mimic the first stimuli of this complex process but is unlikely to suffice for the induction of more broadly active NAbs . The challenge might then be to mold that initial response towards breadth . Structural knowledge of the different epitopes for trimer-induced autologous NAbs may help in overcoming sequence variation nearby . Alternatively , if an autologous response is not amenable to broadening , it may be fruitful to block the epitope and direct the initial response to epitopes with a greater potential for cross-reactivity . The new information we have obtained on BG505 NAb epitopes may help strategies to accomplish these goals .
Female New Zealand White rabbits were immunized intramuscularly with the BG505 SOSIP . 664 trimer formulated with 75 Units of Iscomatrix , essentially as described previously [21 , 23 , 25] . Iscomatrix is a saponin-based adjuvant obtained from CSL Ltd . ( Parkville , Victoria , Australia ) via the International AIDS Vaccine Initiative [23 , 25 , 43] . The rationale for the selection of 15 sera for epitope mapping is outlined in Results . The protocols used to obtain these sera varied as outlined below . Rabbits r5723-r5727 [23] were immunized with 30 μg of trimer at weeks 0 , 4 , and 20 and sera were obtained at week 22 . Sera from rabbits r5738-r5742 were obtained at week 62 after immunizations with 30 μg of BG505 SOSIP . 664 trimers at weeks 0 , 4 , 48 and 60 ( with intercalated B41 SOSIP . 664 trimer at weeks 20 , 24 and 36 ) [23] . The serum from rabbit r5747 was obtained at week 22 , after immunizations with 15 μg of each of the BG505 SOSIP . 664 and B41 SOSIP . 664 trimers at weeks 0 , 4 , and 20 , and from rabbit r5744 at week 26 after such immunizations at weeks 0 , 4 , 20 , and 22 [23] . The latter schedule with BG505 SOSIP . 664 and B41 SOSIP . 664 trimer doses of 45 μg was used before obtaining week 22 sera from rabbits r5749 and r5751 [23] . Monoclonal antibodies ( MAbs ) 11A and 11B , isolated from BG505 SOSIP . 664 trimer-immunized rabbits , have been described previously [25 , 35] . The immunization protocols are summarized briefly as follows . Macaques DF47 , DFGE , DFGN and DFIG received 300 μg of BG505 SOSIP . 664 trimer in Iscomatrix ( 75 units ) adjuvant intramuscularly at weeks 0 , 4 and 20 ( DF47 and DFGE had been primed with an adenovirus vector Ad 26 expressing BG505 SOSIP . 664 Env at 30 and then 18 weeks prior to week-0 ) . The test sera were obtained at week 22; i . e . , 2 weeks after the third trimer immunization . The study was carried out at Alphagenesis Inc . , Yemassee , SC . Macaques RUo15 , RYb15 and RZI15 received 100 μg of BG505 SOSIP . 664 trimers subcutaneously in the right leg close to the popliteal lymph nodes , in Iscomatrix ( 75 units ) adjuvant at weeks 0 , 6 , 12 and 24 . The test sera from RUo15 , RYb15 and RZI15 were obtained at weeks 36 , 32 and 26 , respectively; i . e . , 12 , 8 and 2 weeks after the 4th immunization . The study was carried out at the Yerkes National Primate Research Center ( NPRC ) at Emory University , Atlanta , GA . Macaques rh1987 and rh2011 received 100 μg of BG505 SOSIP . 664 trimers in Iscomatrix adjuvant intramuscularly at weeks 0 , 4 , 12 and 24 . The test sera were obtained at weeks 26 and 28 , respectively , i . e . , 2 or 4 weeks after the fourth immunization . The study was performed at the Wisconsin NPRC , Madison , WI [25] . Macaques 99–12 , RDL15 , RJk15 , RJm15 , RKk15 and ROp15 received two 100 μg doses of BG505 SOSIP . v5 . 2 trimers , delivered by subcutaneous immunization in the thigh of each leg , at weeks 0 , 6 , 12 and 18 . The adjuvant for RJk15 was Iscomatrix , for the other macaques it was PLGA ( MPL+R848 ) . The test sera were obtained at week 20 for RDL15 and RKk15 and at week 21 for 99–21 , RJk15 , RJm15 and ROp15; i . e . , 2 or 3 weeks after the fourth immunization . The study was carried out at the Yerkes NPRC [22] . The rabbit immunization experiment from which the serum samples were derived has been described previously [23] . The study was approved and carried out in accordance with protocols provided to the Institutional Animal Care and Use Committee ( IACUC ) at Covance Research Products ( CRP ) Inc . ( Denver , PA ) , study number C0014-15 . The macaque immunizations were also carried out according to the NIH guidelines in compliance with IACUC regulations . Approvals were obtained from the Center for Virology and Vaccine Research , Beth Israel Deaconess Medical Center and Emory Vaccine Center for the experiments carried out at Alphagenesis Inc , the Yerkes NPRC and the Wisconsin NPRC respectively ( see above ) . The rabbits and macaques were housed , immunized and bled at the various institutions listed above , in compliance with the Animal Welfare Act and other federal statutes and regulations relating to animals , and in adherence to the Guide for the Care and Use of Laboratory Animals , National Research Council , 1996 . Mutant BG505 env genes containing point substitutions were made as previously described [15 , 25 , 44] . The BG505 . T332N virus with a full-length cytoplasmic tail was used as the parental for mutant design , as it contains a knocked-in N332 glycan to match its sequence with the corresponding SOSIP trimer immunogens [15 , 23 , 25] . Some mutants were based on various clones of the MG505 virus , which was isolated from the mother of the BG505 HIV-1-infected infant [13 , 16] . The infectivities of the various mutant viruses for Tzm-bl cells were determined by titration ( S1 Table ) . Only viruses yielding a luminescence signal of 1 x 105 ( relative light units , RLU ) at a dilution of 1/20 or higher were used . These mutants ranged in relative infectivity ( RLU/ ( relative viral dose in parts per volume ) , compared with the parental virus , from 0 . 1–6 . 8 . In preliminary neutralization assays , we found that macaque sera interfered non-specifically , enhancing the infectivity of the murine leukemia virus and most of the HIV-1 pseudoviruses . We therefore purified IgG from macaque sera or plasma to eliminate the interfering factors . This procedure was not necessary with rabbit sera . Briefly , serum or plasma diluted 25-fold in PBS was passed through an equally mixed Protein A ( 17-5138-01 , GE Healthcare ) + Protein G Sepharose column ( P3296 , Sigma-Aldrich ) , the bound IgG was eluted with glycine , pH 3 and immediately equilibrated with Tris , pH 8 . The eluate was diluted 2 . 5-fold with PBS and spun in Vivaspin 6 ( 10 kDa cutoff , GE Healthcare ) columns thrice . The recovered IgG was reconstituted to the original volume . IgG recovery was measured by ELISA ( RSIGGKT-717 , Molecular Innovations ) . Neutralization of Env-pseudoviruses by sera or purified IgG was quantified in the TZM-bl-cell assay as described previously [15 , 25 , 44] . Neutralization was defined as the reduction ( % ) of the infectivity obtained in the absence of serum or IgG . Rabbit sera were titrated in two-fold steps . The dilution factors reducing infectivity by 50% ( half-maximal inhibitory dilution factor , ID50 ) were calculated from nonlinear regression fits of a sigmoid function ( with maximum constrained to <100% and minimum unconstrained ) to the normalized inhibition data in Prism ( Graphpad ) . The ratios of the titers for each mutant virus over the parental BG505 . T332N virus ( Relative Inhibitory Dilution at 50% neutralization = RID50 ) are reported in the Results section . The ID50 values for the rabbit sera against the parental virus were in the range 300–4000 . The macaque IgG preparations generally had lower neutralizing capacity than the rabbit sera against the BG505 . T332N parental virus , which in most cases precluded analyses of titer changes against the mutants . We therefore recorded the ratio of the extent of neutralization of a mutant virus , compared with the parental virus , at a macaque IgG concentration corresponding to a 1/50 dilution of serum or plasma . These ratios , i . e . , the relative extents of neutralization , REN , are recorded in Results . In addition , because of limiting sample availability , some of the IgG preparations could only be tested against a subset of mutants . All neutralization measurements are the medians derived from ≥3 experiments . In order to ascertain the accuracy of the results , we compared three methods for quantifying the effects of mutations on neutralization sensitivity ( see SI section ) . They are based on neutralization titer ( RID50 ) , neutralization extent ( REN ) at the lowest serum dilution , and the area under the neutralization curve ( RAUC ) ( S1 Fig ) . Moderate resistance is less frequently detected as REN or RAUC than as RID50 ( S1–S3 Figs ) although meaningful RID50 determinations require ID50 values > 300 and were thus not applicable to most of the macaque samples . A theoretical account of how the different resistance measurements might relate to the affinity and stoichiometry of binding is presented in the Supplementary results section ( S1 Text , pages 1–2 ) . We note that we have previously described a strong correlation between the potency of neutralization of the BG505 . T332N virus ( as measured by ID50 ) and of binding to the BG505 SOSIP . 664 trimer in ELISA ( as measured by EC50 ) [15 , 23] . By extrapolation , the relative neutralization and binding titers for the virus and trimer mutants should also correlate , but this remains to be verified experimentally . The three-dimensional model of the BG505 SOSIP . 664 trimer was based on the PDB-5V8M structure [45] . The gp120 glycans were modeled as Man5 while gp41 glycans were either derived from PDB-5FUU or modeled as Man5 [46] . UCSF Chimera was used for model visualization [47] . To investigate whether different mutations affected the same or disparate epitopes , we performed Spearman rank correlations of absolute and relative neutralization titers of rabbit sera against selected mutants ( two-tailed significance tests ) . RID50 values for subsets of rabbit sera were compared by two-tailed Mann-Whitney U tests ( all analyses were performed in Prism , Graphpad ) . | A protective vaccine would constitute a breakthrough in efforts to curb the global spread of HIV . Such a vaccine should induce antibodies inhibiting infection by most strains of the virus that circulate worldwide . Engineered SOSIP trimer mimics of the envelope glycoprotein on the surface of HIV particles , which mediates viral entry into cells , can elicit such neutralizing antibodies in rabbits and rhesus monkeys . These antibodies , however , have a narrow specificity , neutralizing mainly the same virus from which the SOSIP trimer protein was derived . Here , we have mapped the sites on the SOSIP trimer to which these antibodies bind , thereby delineating both an already identified binding site and a previously unknown one . The rabbits produced neutralizing antibodies that recognize both binding sites , but the rhesus monkeys responded predominantly to the newly identified one . As immune responses in monkeys are the more likely to resemble those in humans , the findings described here might aid strategies to steer human antibody responses to sites that are cross-reactive among HIV strains . That outcome would be a major step towards an effective vaccine . | [
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] | 2018 | Epitopes for neutralizing antibodies induced by HIV-1 envelope glycoprotein BG505 SOSIP trimers in rabbits and macaques |
Human neurotransmitter transporters are found in the nervous system terminating synaptic signals by rapid removal of neurotransmitter molecules from the synaptic cleft . The homologous transporter LeuT , found in Aquifex aeolicus , was crystallized in different conformations . Here , we investigated the inward-open state of LeuT . We compared LeuT in membranes and micelles using molecular dynamics simulations and lanthanide-based resonance energy transfer ( LRET ) . Simulations of micelle-solubilized LeuT revealed a stable and widely open inward-facing conformation . However , this conformation was unstable in a membrane environment . The helix dipole and the charged amino acid of the first transmembrane helix ( TM1A ) partitioned out of the hydrophobic membrane core . Free energy calculations showed that movement of TM1A by 0 . 30 nm was driven by a free energy difference of ~15 kJ/mol . Distance measurements by LRET showed TM1A movements , consistent with the simulations , confirming a substantially different inward-open conformation in lipid bilayer from that inferred from the crystal structure .
Stringent regulation of neurotransmission is essential for brain function . Secondary active transporters from the solute carrier family 6 ( SLC6 ) terminate signal propagation by clearing released neurotransmitters from the synaptic cleft . This is achieved by coupling substrate transport to the electrochemical sodium gradient . Members of the SLC6 family include the transporters for dopamine ( DAT ) , norepinephrine ( NET ) , serotonin ( SERT ) and γ-aminobutyric acid ( GAT ) . Several neurological and psychiatric disorders are associated with SLC6 dysfunction [1] . In addition , these transporters are clinically relevant targets of a number of marketed drugs but also of illicit drugs of abuse . The crystal structures of the bacterial homolog neutral amino acid transporter ( LeuT ) from Aquifex aeolicus in three different conformations [2–4] have greatly enhanced our structural but also functional understanding of the SLC6 family . More recently , the crystal structures of the Drosophila melanogaster DAT [5–7] confirmed fold conservation . Importantly , many insights gained from the LeuT structures can be extrapolated to eukaryotic SLC6 members . Overall , SLC6 transporters consist of twelve transmembrane helices ( TM ) , which are assembled into two domains . The structures imply that the scaffold domain anchors the transporter into the membrane , while the bundle domain changes its conformation to afford substrate transport [8 , 9] . Substrate and two sodium ions bind to the substrate binding site ( S1 ) located in the center of the membrane [3] . The structural dynamics of LeuT have been directly measured by fluorescence resonance energy transfer microscopy ( FRET ) [10–13] , electron paramagnetic resonance ( EPR ) [14–17] , and investigated by molecular dynamics ( MD ) simulations [12 , 17–37] . These studies revealed that substrate transport by LeuT involves multiple conformations and that the structure of LeuT is highly dynamic . However , it still remains elusive , if the first part of TM1 ( TM1A ) can detach from the bundle domain to allow for substrate release [2 , 8 , 21 , 22] . The inward-open LeuT crystal structure reveals a 45° rotation of TM1A , thereby opening a large access path to the S1 site from the cytosol [2] . The structure was stabilized by an antibody and four mutations were introduced . Importantly , if this motion occurred , TM1A would partition into the hydrophobic core of the membrane and , as a consequence , hydrophilic and charged residues would be transferred into the membrane , which is an energetically unfavorable process . In the current study we investigated the conformation of the inward-open state in a detergent micelle and in a membrane bilayer to assess the impact of the environment on the shape of the inner vestibule . MD simulations revealed that the conformation adopted by LeuT in the crystal structure is stable in a micellar environment . In contrast , the polar and charged residues leave the hydrophobic core of the lipid bilayer and partition in the hydrophilic environment of the lipid head groups and bulk water . We confirmed our in silico results by experimental measurements using lanthanide resonance energy transfer ( LRET ) [38 , 39] . We observed changes in distances between the micelle and the POPC membrane environment that were consistent with the results from MD simulations . We deduced from our data that the conformation of TM1A in the inward-open state depends highly on its immediate environment and inferred that the freedom of movement is considerably smaller in a cell membrane than suggested from crystal structures obtained in micellar systems .
We investigated the influence of the environment on the conformation of the inward-open LeuT structure by MD simulations . We inserted the inward-open structure of wild type LeuT into ( i ) n-octyl-beta-D-glucoside ( BOG ) to mimic the micellar environment used during the crystallization process and into ( ii ) 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine ( POPC ) to resemble the cell membrane phospholipid bilayer environment . In addition , the outward-occluded conformation was simulated in a POPC membrane and used as reference . All MD simulations were carried out in complex with sodium ions and the substrate leucine . The outward-occluded LeuT conformation showed a high overall stability in the membrane environment in repeated MD simulations of 200 ns length . Root mean square deviations ( RMSD ) from the starting structure were below 0 . 20 nm ( S1 Fig ) . Atomic β-factors reflect the uncertainty in the determination of atomic positions; in crystallography , these are often interpreted as mobility and related to dynamic properties of the corresponding residue . A comparison of the β-factors calculated from root mean square fluctuations in our MD simulations with the β-factors obtained from the outward-occluded crystal structure ( PDB ID: 2A65; resolution: 1 . 65 Å ) [3] revealed comparable profiles as observed in previous studies [18] , ( Fig 1A ) . Also , MD simulations of the membrane inserted inward-open LeuT showed a similar β-factor profile ( Fig 1B and 1C ) , though the amplitudes of the motions were larger ( Fig 1A and 1D ) . The crystal structure of the inward-open conformation ( PDB ID: 3TT3; resolution: 3 . 22 Å ) [2] had a much lower resolution , β-factors are therefore higher ( Fig 1B and 1C ) . The crystal structures of LeuT were solved in the presence of BOG or BSG ( n-octyl-beta-D-thioglucoside ) , but the detergent molecules were largely unresolved . Hence , we developed a detergent solubilized LeuT system by applying a self-assembly procedure . We tested three detergent:transporter ratios: 120:1 , 140:1 and 160:1 , as the exact detergent:transporter ratio is unknown . The 120:1 ratio was likely too low , because the membrane exposed hydrophobic surface of LeuT was not completely covered with BOG molecules . The hydrophobic surface was fully covered at a 140:1 detergent:transporter ratio . At a 160:1 detergent-transporter ratio we observed detergent-only micelle formation suggesting that this ratio might be too high . We therefore selected the 140:1 detergent:transporter ratio for all subsequent simulations . A recent study found that a similar number of n-dodecyl-β-D-maltopyranoside ( DDM ) detergent molecules was needed for solubilization of LeuT [34] . Structural stability in MD simulations of the micelle inserted LeuT was higher than in the membrane environment ( Fig 1C ) , but the β-factors showed the same pattern at lower amplitudes ( Fig 1F ) . The crystal structure of LeuT in the outward-occluded conformation has been solved starting from residue 5 ( PDB ID: 2A65 ) . Notably , the first 10 residues were missing in the inward-facing crystal structure ( PDB ID: 3TT3 ) , suggesting that their positional uncertainty was too high . The β-factors of TM1A did not differ from the other TM helices in the outward-occluded crystal structures ( Fig 1E ) , while in the inward-facing structure , the β-factors of TM1A were significantly higher ( Fig 1G ) . This suggests higher mobility or the existence of multiple conformational states of TM1A . MD simulations showed similar results: the mobility of TM1A was low in the outward-occluded conformation ( Fig 1D ) and comparable to that of the other TM helices . In contrast , in the inward-open conformation , the β-factors of TM1A were also much higher than those of the other TM helices , in particular in the membrane environment ( Fig 1E and 1F ) . Furthermore , residues preceding TM1A showed essentially unconstrained movement . The mobility determined in MD simulations was therefore consistent with the β-factors measured in the crystal structures . Importantly , this analysis showed that , in the inward-open conformation , the state of TM1A differed substantially from that seen in the outward-occluded conformation . TM1A was deeply buried in the hydrophobic core of the membrane bilayer in the starting structure of the MD simulations of the inward-open conformation . We observed a directional movement of TM1A during MD simulations , whereby polar and charged moieties of TM1A ( consisting of the side chain of R11 and the backbone amide groups on the first helical turn of TM1A ( residue 10 to 13 ) ) partitioned out of the hydrophobic core of the membrane ( Fig 2 ) . This transition was accompanied by a change in size of the inner vestibule , which decreased in width over time . We determined the distance between the Cα atoms of residues M18 ( TM1A ) and residue Y265 ( TM6; Fig 2B ) across the inner vestibule as a parameter to estimate its width . The distance decreased from 1 . 7 nm to 1 . 2–1 . 4 nm in two independent MD simulations . The third MD simulation showed a drop in distance to 0 . 9 nm . Despite the large movement , the inner vestibule did not completely close ( Fig 2E and S2 Fig ) . MD simulations of the micelle-inserted inward-open LeuT showed a strikingly different motion , when compared to the membrane embedded state: movements of TM1A were non-directional and β-factors showed larger positional fluctuations . The final conformations of three MD simulations overlapped with each other and with the crystal structure ( Fig 2C ) . The inner vestibule diameter did not decrease over time and accordingly the access path to the S1 site did not narrow significantly ( Figs 2D , 2F and S2 ) . These observations imply that the mobility of TM1A is high , presumably because it is less constrained by interactions with the other TM helices than in the outward occluded state . A fundamental difference between the outward- and the inward-facing conformations of LeuT lies in the access path to the central binding site . To clarify these changes , we derived water density plots from our MD simulation on the inward-open and outward-open states . In the case of the outward-open state , water penetrates from the extracellular space into the substrate-binding site S1 ( Fig 3 and 3A ) . In simulations of the outward-occluded state , we observed that the S1 site is sealed off from the extracellular space by a thin gate . This gate is formed by a salt bridge between residues R30 and D404 ( colored magenta in Fig 3 ) and the hydrophobic lid comprised of the residues , Y108 and F253 . In the inward-open conformation , we observed that water reaches the S1 binding site from the cytosol ( Fig 3B ) . This difference reflects the main conformational change in the transport cycle . The thin outer gate is strengthened by movements of the bundle domain which leads to a broadening of the water-free region in the outer vestibule [2 , 3] . Fig 3B shows that the charged side chain of R11 ( colored pink in Fig 3 ) is located within the hydrophobic membrane core in the starting conformation . Residue R11 increased interactions with the hydrophilic environment over time , mainly with the negatively charged PO4- group of the membrane lipids and with water ( S3 Fig ) . Concomitantly , the first turn of helix TM1A partitioned into the polar environment of the lipid head group region . The first turn of any helix establishes a strong helical dipole due to the alignment of the four consecutive backbone amide protons ( residue 10 to 13 ) . Increasing interactions with the polar environment correlated with the movement of TM1A . BOG detergent molecules cover the hydrophobic transmembrane region of LeuT and formed a thin donut-shaped structure around the hydrophobic surface of LeuT in the micelle system ( Fig 3C ) . The spherical shape and the small width of the BOG micelle structure allow for hydration of R11 and the backbone amide groups of TM1A . LeuT does not show a precisely match with the hydrophobic core of the membrane [31] . The hydrophobic mismatch is not evenly distributed over the membrane-protein interface . This is in accordance with our finding that insertion of TM1A into the membrane core further distorts the membrane and affected membrane thickness ( S4 Fig ) . Membrane deformation relaxed towards the end of the MD simulation , particularly after re-partitioning of TM1A . Substrate and two sodium ions are stably bound to the S1 site in the outward-occluded state . Their mobility was very low: the RMSD remained below 0 . 1 nm . The situation was different in the inward-open conformation ( Fig 4 ) : MD simulations of the membrane inserted inward-open LeuT suggested that this state represented a conformation , in which substrate and the two sodium ions were prone to release into the cytosol . The sodium in the Na2 site became hydrated and dissociated into the bulk solvent through the open inner vestibule within the first nanoseconds ( S5 Fig ) similar to recent reports [36] . This was expected , because the Na2 site is disrupted in the inward-open crystal structure due to the movement of the bundle domain and mutations at the Na2 binding site [2] . Ion binding to and the selectivity of the Na2 site is very sensitive to the local environment , which consists of residues from TM1 and TM8 [19 , 26] . The extent of Na1 and substrate hydration was higher in all MD simulations of the inward-open conformation as compared to the level of hydration in the outward-occluded conformation . Importantly , substrate and Na1 were mobile in all inward-open simulations ( Fig 4 ) . Yet , neither Na1 nor the substrate left the vestibule in 200 ns simulation runs . The most likely reason is a too short simulation . Nonetheless , we interpret our simulations as showing the initial events of substrate release into the cytosol . The computational analysis predicted that the conformation of TM1A of the inward-open LeuT differed between the detergent solubilized and the lipid bilayer environment . We employed lanthanide-based resonance energy transfer ( LRET ) to verify the predictions by measuring intramolecular distances . LRET offers the advantage over conventional fluorescent energy transfer ( FRET ) measurements that emission is isotropic . This renders energy transfer much less sensitive to the orientation of the label [38] . We introduced a lanthanide binding tag ( LBT ) and used the Tb3+ ion as donor . The LBT tag chelates Tb3+ and protects it from relaxation by direct water contacts . Lanthanides have a low extinction coefficient and per se , cannot be efficiently excited . However , the LBT carries a tryptophan residue , which serves as sensitizer antenna and transfers the initial excitation energy to the chelated Tb3+ ion . The LBT tag was inserted at the C-terminal end of LeuT . We synthesized the fluorophore BODIPY-C3-M ( Fig 5 , see Materials and methods for the synthesis details ) , which gives rise to reduced positional uncertainty in LRET , because of ( i ) the symmetric attachment and ( ii ) the very short linker ( 0 . 3 nm ) between the BODIPY dye and the thiol reactive maleimide function . The BODIPY-based acceptor fluorophore was covalently linked to a cysteine introduced at position 9 ( instead of alanine ) of the otherwise cysteine-free LeuT . This position was selected because it is juxtaposed to the N-cap of TM1A and lies on the opposite side of the C-terminus across the vestibule . The resulting double-tagged construct is referred to as LeuT-LBT-A9C in the subsequent description . Insertion of the donor and acceptor probes did neither alter substrate affinity of nor maximum velocity of transport by LeuT-LBT-A9C ( S6 Fig ) compared to WT . The LRET experiment is schematically depicted in Fig 5A . The LBT chelated Tb3+ donor is shown in red , the acceptor fluorophore bound to A9C is shown in magenta . Movements of TM1A can be detected by a change in the donor-acceptor distance . The LeuT-LBT-A9C construct was solubilized in n-dodecyl-β-D-maltoside ( DDM ) detergent micelles or reconstituted into POPC to generate proteoliposomes . Fig 5B shows recordings of LRET signals emitted from the Tb3+ donor after excitation by a brief laser pulse of 30 ns length . Traces of label free LeuT-LBT-A9C ( orange and green ) show donor emission in the absence of the BODIPY-C3-M acceptor . Recordings in the presence of BODIPY-C3-M were measured in the absence ( purple ) or presence of 200 mM Na+ ( black ) . The donor decay was faster in the presence of the acceptor because of quenching by energy transfer ( S1 Table ) . The measured decay constant was converted to the corresponding donor-acceptor distance by the Förster equation . The grey traces represent the background recorded with wild type LeuT lacking the LBT tag . The ionic composition did not affect donor emission , because the decay rates were similar in the presence and absence of Na+ ( replaced by K+ ) . We measured slower decay rates in the absence of Na+ than in its presence . Thus donor and acceptor were in closer proximity in the presence of Na+ . This is consistent with the results from previous studies [10–12 , 15] , which applied single molecule FRET to detergent solubilized LeuT . In the micelle environment , the distances were 6 . 26 ± 0 . 21 nm and 5 . 16 ± 0 . 22 nm in the absence and presence of 200 mM Na+ , respectively . In contrast , the distance decreased from 5 . 34 ± 0 . 15 nm in the absence of Na+ to 4 . 80 ± 0 . 14 nm in its presence , if the recordings were done with membrane embedded LeuT-LBT-A9C . Thus , the conformational change induced by Na+ reduced the distance by only 0 . 54 ± 0 . 21 nm in the membrane environment of proteoliposomes but by 1 . 11 ± 0 . 30 nm in the detergent-solubilized transporter . The simulations showed that TM1A partitioned out of the hydrophobic core of the membrane ( Fig 2 ) and this was confirmed by distance measurements ( Fig 5 ) . We performed potential of mean force ( PMF ) calculations to quantify the free energy profile underlying this movement . We extracted equally spaced ( 0 . 02 nm ) conformations from the three inward-open membrane-inserted simulations and performed 25 ns long umbrella sampling calculations for each window . We excluded the first 5 ns as equilibration and construct the PMF using the weighted histogram analysis method ( WHAM ) ( Fig 6 ) using the remaining 20 ns . Statistical errors were estimated using the bootstrap method . The profiles showed that re-partitioning of TM1A is an energetically favorable process . The initial conformation was less stable by approximately 15 kJ/mol than the lowest energy conformation . The final rise of the PMF profile could indicate that TM1A reached an equilibrium position . The profile of run 1 remained approximately flat , in line with the minimum TM1A movement in the equilibrium simulation and the largest membrane deformation ( S4 Fig ) . The intrinsically slow membrane dynamics therefore did not allow for reaching full convergence within the 200 ns of the equilibrium MD simulations . The free energy profiles show a clear trend towards an energetically more stable conformation in which the charged and polar moieties of TM1A have partitioned into the polar environment of the head group region of the membrane . We infer from the equilibrium simulations and from the PMF free energy profile that the extent of TM1A movement in the inward-open state is much smaller in the membrane environment than that suggested by the crystal structures [2 , 3] . However , this conformation provides an open access path to the S1 binding site .
The neutral amino acid transporter LeuT translocates substrates by an alternating access mechanism , in which the central binding site is only accessible from one side of the membrane at any given time [2–4 , 8 , 21 , 40 , 41] . The outward-open [4] and inward-open [2] structures are thought to represent endpoints of the transport cycle . TM1A showed high β-factors in the inward-open conformation , while the electron density of the 10 N-terminal residues could not be resolved . The inward-open conformation of TM1A observed by crystallographically has remained controversial , because of its questionable compatibility with the physico- chemical constraints imposed by the membrane bilayer . The mutations that needed to be introduced to obtain the inward-facing conformation added to the controversy , because of the disruption of the Na2 sodium binding site . Our results show that the crystallographically observed conformation of TM1A can be accommodated by a micelle environment , but it does not occur in a membrane . This conclusion is based on the following observations: ( i ) we found a stable conformation and detected a large mobility of TM1A in BOG micelle simulations , which is in line with the β-factors reported in the crystal structure . The structure was stable because detergent molecules covered the entire membrane exposed surface of LeuT . A similar behavior was observed with the detergent DDM [34] . Importantly , the micelle structure allowed for hydration of the charged side chain of R11 and of the dipole created by the first turn of the helix backbone . ( ii ) In detergent , TM1A showed high mobility , because it was not constrained by any large interaction surface . ( iii ) Our simulations revealed that the conformation of TM1A was not compatible with a membrane environment . In fact , the hydrophobic effect exerted by the lipids and the electrostatic interactions of TM1A destabilized the starting conformation and induced conformational rearrangements . ( iv ) We confirmed earlier findings [31] that the proposed inward-open conformation of LeuT caused membrane deformation . The movement of TM1A , which we observed , reduced this hydrophobic mismatch . We verified our conclusion using LRET-based distance measurements: for the inward-open conformation of LeuT , the MD simulations of the micelle-covered LeuT predicted a distance between the Cα atoms of the N-terminal residue 9 and Cα of residue 508 at the C-terminus of TM12 of 4 . 81 ± 0 . 25 nm . Complete partitioning of TM1A was observed in two simulations of membrane-embedded LeuT and reduced the distance to 4 . 51 ± 0 . 18 nm . The corresponding changes in distance measured by LRET between outward- and inward-facing LeuT were 1 . 11 ± 0 . 30 nm and 0 . 54 ± 0 . 21 nm for the micelle and membrane environment , respectively . Thus , upon switching from the outward-facing sodium-bound state of LeuT , TM1A was displaced to a lesser extent , if the protein resided in the membrane . The measured difference in movement between micelle-covered and membrane-embedded LeuT ( 0 . 56 ± 0 . 37 nm ) is in excellent agreement with the predictions from the MD simulations ( 0 . 30 ± 0 . 30 nm ) . The fact the LRET-measurements indicate a more extensive repositioning of TM1A can be rationalized by considering the applied rulers , i . e . the Cα atoms of the protein backbone ( in the MD-simulations ) and the fluorescent probes , which were–by necessity–further apart . We are aware that our simulations did not explicitly include the position of the LBT and the mobility of the acceptor BODIPY-C3-M ( resulting from the short flexible linker ) . However , the direct comparison between experiments and MD simulations is justified under the following assumptions: ( i ) the vector connecting donor and acceptor in the LRET experiment and the vector connecting the Cα atoms of residue 9 and 508 in the MD simulations are essentially parallel and/or their relative angle does not change substantially between inward and outward-facing states . ( ii ) The conformational ensembles of the LBD tag and of the BODIPY-C3-M acceptor dye remain unchanged during the switch from outward to inward-facing state . These conditions ought to be met in our system . First , the LBT tag is attached to the scaffolding domain , which does not undergo any motion during the conformational switch . Second , the acceptor is attached to residue 9 , thus both the Cα of this residue and the attached fluorescent tag move in concert . We can therefore infer from our MD simulations and our experiments that the movement of TM1A is much smaller in the membrane environment than that suggested by the crystal structures . Importantly , the exit path from the S1 site to the cytosol remained open , indicating that the large amplitude of the TM1A motion is not a requirement for substrate release . We used PMF calculations to quantify the free energy profile of TM1A movement starting from conformations extracted from equilibrium MD simulations , in which the system was allowed to explore the available phase space in an unbiased fashion and to move down naturally existing energy gradients . We found that the crystal structure was in a high-energy conformation within the membrane environment and found that partitioning of TM1A released ~15 kJ/mol . The conformation of TM1A has been investigated in two recent simulation reports . TM1A was shown to have a high probability to partially close the inner vestibule in a 1-palmitoyl-2-oleyl-phosphatidylethanolamine ( POPE ) membrane [42] . The opposing result was reported earlier , as TM1A was found to be very stable when residing in the hydrophobic core of a POPC membrane ( stabilized by ~20 kJ/mol ) [36] . However , in spite of this net stabilization energy calculated from the PMF profile , that study nevertheless suggested that TM1A could deviate from the crystallized conformation [36] . The orientation of TM1A has also been studied by single molecule FRET [11] and EPR in the micellar environments [14] using a label attached to residue 7 . Both studies reported that LeuT only populated the outward-facing state in the presence of sodium or sodium and substrate , while in the absence of sodium and substrate two conformations were found , which are consistent with inward and outward-facing LeuT . In contrast , only one distance was detected when the polar EPR label was directly attached to TM1A to the membrane exposed residue 12 [14] . Here we report experimental distance measurements in micelles and we extend the experimental investigation to a physiologically more relevant POPC membrane environment . To emphasize the importance of the environment , we observed substantial environmental effects: ( i ) we find in the micelle environment that TM1A maintains a conformation consistent with the crystal conformation . ( ii ) In contrast , in the lipid environment TM1A moves closer to the C-terminus , thereby reducing the opening of the inner vestibule . Thus , both the experimental results and the data from simulations indicate that TM1A does not fully enter the hydrophobic core of the membrane , but differs from the conformation in the outward-facing state . Movements of helix TM1A disrupt the geometry of the Na2 binding site , because it is formed by TM1 and TM8 , which move relative to each other [2 , 3 , 8 , 13 , 22] . The implication of our observations is that once TM1A moves , the Na2 binding site is disrupted , which leads to rapid dissociation of Na2 [13] . We observed repeated spontaneous movement events of Na1 and substrate after dissociation of Na2 , implying that the affinity for sodium and substrate is low in the inward-open state . LeuT has served as a template for the SLC6 transporter family since its first crystallization . It was repeatedly demonstrated that many insights gained from LeuT were also relevant to understanding the transport cycle of the human neurotransmitter transporters . It is hence very likely that our findings can also be generalized , because the biophysical properties of the environment impose similar constraints on all transporters: the detergent micelles can adjust to any shape of the solubilized membrane protein , but the two dimensional layer of the lipid bilayer environment opposes motion against the pressure profile [43–45] and precludes vertical movements of helices , i . e . in a direction perpendicular to the plane of the membrane . It can therefore be safely assumed that movements of TM1A in the human SLC6 transporter family will be restrained in amplitude by the membrane environment .
Simulations of the inward-facing structure of LeuT ( PDB ID: 3TT3 ) [2] were carried out in palmitoyl-oleoyl-phosphatidyl-choline ( POPC ) containing membranes and in n-octyl-β-D-glucopyranoside ( BOG ) micelles . The missing residues of the inward facing LeuT structure were built using MODELLER , version 9 . 12 [46] applying the automodel procedure , selecting the best models according to the DOPE score [47] . Mutations present in the structure were reverted to wild type . The missing residues of the N-terminus were copied from the outward-occluded LeuT structure ( PDB ID: 2A65 ) [3] after superpositioning of helix TM1A , while the sodium ions and the substrate leucine were copied after superpositioning of the scaffold domain . Residues E112 , E287 and E419 are protonated as suggested by crystal structures and pKa calculations [8] . The side chain of residue K288 in the center of the membrane was neutralized . The LeuT structure with the PDB ID: 2A65 was used as starting structure for the simulations of the outward-occluded structure . The missing 3 residues of the extracellular loop 2 were modeled using MODELLER . The transporter structures were inserted into a pre-equilibrated membrane consisting of 174 POPC lipid molecules using the membed method as described recently [48] . Each system contained ~12850 SPC water molecules , was neutralized and a salt concentration of 150 mM NaCl was added by randomly replacing water molecules . The system dimensions are 8 . 37 , 8 . 37 and 9 . 70 nm . The semi-isotropic pressure coupling scheme was applied . Each system was equilibrated for a total of 30 ns while slowly releasing the transporter by reducing the position restraints on the heavy atoms of LeuT in three steps: 1000 , 100 and 10 kJ/mol/nm2 . Representative structures are shown in S7 Fig . The micelle structure was created using a self-assembly procedure . We randomly placed BOG detergent molecules into a truncated octehedron box that contained one LeuT using the same starting conformation as in the membrane simulations and filled the system with ~48000 SPC water molecules . The systems were electroneutralized and an ionic concentration of 150 mM NaCl was added by randomly replacing water molecules . Electrostatic interactions were treated using the particle mesh Ewald summation method with a cutoff of 1 . 0 nm . The heavy atoms of LeuT were restrained with 1000 kJ/mol/nm2 . These assembled systems were further equilibrated for 10 ns while maintaining secondary structure using distance restraints . The BOG detergent molecules were allowed to equilibrate for 100 ns . We built independently three systems by incrementally adding BOG detergent molecules . The protein:BOG ratios were 1:120 , 1:140 and 1:160 . The 120 BOG detergent molecules were not sufficient to fully cover the hydrophobic region of LeuT . Addition of 20 randomly placed BOG molecules to the equilibrated first systems ( ratio 1:140 ) followed by 100 ns equilibration allowed for a good coverage of the hydrophobic surface . Addition of further 20 detergent molecules ( ratio of 1:160 ) resulted in the formation of small detergent micelles suggesting that the lipid:protein ratio was too high . Representative structures of the 1:140 system are shown in S7 Fig . Production runs were carried out for 200 ns . Simulations were carried out with the Gromacs simulations package , version 4 . 5 . 4 [49] . Berger lipids [50] were used for describing the POPC membrane . The OPLS force field [51] was used for the protein and detergent . The topology for the BOG detergent molecule was developed using the mktop procedure applying the standard OPLS partial charge scheme . Temperature was maintained at 310 K using the v-rescale ( τ = 0 . 1 ps ) thermostat [52] , while separately coupling protein , membrane and solvent . Pressure was maintained at 1 bar using the Berendsen barostat [53] . The pressure coupling constant was set to 1 . 0 ps , the compressibility to 4 . 5×10−5 bar-1 . Long range electrostatic interactions were described using the smooth particle mesh Ewald method [54] applying a cutoff of 1 . 0 nm . The van der Waals interactions were described using the Lennard Jones potential applying a cutoff of 1 . 0 nm . Long range correction for energy and pressure were applied . The bonds and angles of the water molecules were constrained using the SETTLE algorithm [55] , while all other bonds were constrained by LINCS [56] . We used potential of mean force ( PMF ) calculations [57] to quantify the energetic profile for the movement helix TM1A . Structures were extracted from the equilibrium simulations in 0 . 02 nm increments . Each structure was used as starting conformation for umbrella simulation , the conformations was restrained by a harmonic potential of 5000 kJ mol−1 nm−1 applied between the center of mass of two equally size groups . Group 1 consisted of the Cα atoms of residue 11 to 20 on helix TM1A , group 2 included the Cα atoms of residues 78 to 81 ( intracellular loop 1 ) , 363 to 366 ( TM8 ) and 503 and 504 ( TM12 ) . Each window was simulated for 25 ns . The first 5 ns were discarded as equilibration , the remaining 20 ns were considered for determination of the PMF using the weighted histogram analysis method ( WHAM ) [58] . Statistical errors were estimated using the bootstrap method . The LBT tag has the amino acid sequence YWDTNNDGWYEGDELLA . The LBT encoded at the DNA level , was introduced just after the C-terminus to the LeuT gene within thrombin cleavage site ( LVPAGS ) right before the HIS-tag using two consecutive PCRs . The plasmid for LeuT was a kind gift by E . Gouaux . First PCR reaction was carried out to make the megaprimers using primers ( R519-LBT-G520 primers ) , and purified using agarose gel . These cleaned megaprimers were then used to introduce the LBT encoding peptide at the C-terminus of the LeuT gene via conventional PCR yielding the LeuT-LBT construct . The A9C mutation was introduced via site directed mutagenesis into the LeuT-LBT construct using respective primers . All mutations were confirmed via DNA sequencing . Below , the sequence of the LBT tag is highlighted in bold . Protein sequence of LeuT-LBT: MEVKREHWATRLGLILAMAGNAVGLGNFLRFPVQAAENGGGAFMIPYIIAFLLVGIPLMWIEWAMGRYGGAQGHGTTPAIFYLLWRNRFAKILGVFGLWIPLVVAIYYVYIESWTLGFAIKFLVGLVPEPPPNATDPDSILRPFKEFLYSYIGVPKGDEPILKPSLFAYIVFLITMFINVSILIRGISKGIERFAKIAMPTLFILAVFLVIRVFLLETPNGTAADGLNFLWTPDFEKLKDPGVWIAAVGQIFFTLSLGFGAIITYASYVRKDQDIVLSGLTAATLNEKAEVILGGSISIPAAVAFFGVANAVAIAKAGAFNLGFITLPAIFSQTAGGTFLGFLWFFLLFFAGLTSSIAIMQPMIAFLEDELKLSRKHAVLWTAAIVFFSAHLVMFLNKSLDEMDFWAGTIGVVFFGLTELIIFFWIFGADKAWEEINRGGIIKVPRIYYYVMRYITPAFLAVLLVVWAREYIPKIMEETHWTVWITRFYIIGLFLFLTFLVFLAERRRNHESAGTLVPRYWDTNNDGWYEGDELLAGSGHHHHHHHH Protein sequence of LeuT-LBT-A9C: MEVKREHWCTRLGLILAMAGNAVGLGNFLRFPVQAAENGGGAFMIPYIIAFLLVGIPLMWIEWAMGRYGGAQGHGTTPAIFYLLWRNRFAKILGVFGLWIPLVVAIYYVYIESWTLGFAIKFLVGLVPEPPPNATDPDSILRPFKEFLYSYIGVPKGDEPILKPSLFAYIVFLITMFINVSILIRGISKGIERFAKIAMPTLFILAVFLVIRVFLLETPNGTAADGLNFLWTPDFEKLKDPGVWIAAVGQIFFTLSLGFGAIITYASYVRKDQDIVLSGLTAATLNEKAEVILGGSISIPAAVAFFGVANAVAIAKAGAFNLGFITLPAIFSQTAGGTFLGFLWFFLLFFAGLTSSIAIMQPMIAFLEDELKLSRKHAVLWTAAIVFFSAHLVMFLNKSLDEMDFWAGTIGVVFFGLTELIIFFWIFGADKAWEEINRGGIIKVPRIYYYVMRYITPAFLAVLLVVWAREYIPKIMEETHWTVWITRFYIIGLFLFLTFLVFLAERRRNHESAGTLVPRYWDTNNDGWYEGDELLAGSGHHHHHHHH Primers for LBT coding Megaprimers LeuT-LBT forward primer: AGAGTGCTGGTACCCTGGTGCCGCGCTATTGGATACCAACAACG LeuT-LBT forward primer: TGGTGATGATGACCGCTGCCCGCCAGCAGTTCATCGCC A9C mutant forward primer: GAAGTTAAAAGGGAACACTGGTGCACGCGACTCGGTTTAATCCTC A9C mutant reverse primer: GAGGATTAAACCGAGTCGCGTGCACCAGTGTTCCCTTTTAACTTC LeuT was expressed and purified as previously reported [4] . Briefly , fresh bacterial transformants of chemically competent cells C41 ( DE3 ) from Lucigen were used for each batch of protein purification . Cells were induced with 0 . 2 mM IPTG when inoculum reached an OD600 of 0 . 6 . Induced cells were grown for 20 hours at 20°C . Harvested cells were lysed two times on Avestin Emulsiflex applying a pressure of 15000 psi in lysis buffer ( 50 mM HEPES , pH 7 . 5 , 200 mM NaCl , 1 mM EDTA , 5 mM MgCl2 , 20 μg/ml DNAse-1 , 1 mM PMSF and 0 . 4 mg/ml Lysozyme ) . Cell debris were removed by centrifugation at 5000g . Supernatant was centrifuged at 120000g for two hours to pellet the crude membrane fraction . Subsequently , crude membranes were solubilized for 90 min on a rotatory carousel at 4°C in membrane solubilization buffer ( 20 mM HEPES , pH 7 . 5 , 200 mM NaCl and 1% DDM supplemented with 1 mM PMSF ) . Unsolubilized membranes were removed by centrifugation at 120000g for 20 min at 4°C . Solubilized material was incubated with pre-equilibrated NiNTA beads from Qiagen overnight at 4°C . Leucine bound to LeuT was removed by extensive washing with buffer devoid of Na+ ( 20 mM HEPES , pH 7 . 5 , 200 mM KCl ) supplemented with concentration gradient of imidazole . Bound LeuT was then eluted from the NiNTA resin with elution buffer ( 20 mM HEPES , pH 7 . 5 , 200 mM KCl , 250 mM imidazole ) . Imidazole was then removed using PD10 columns and ion exchange between Na+ and K+ was performed as needed . Cysteine specific protein labeling with the fluorescence dye BODIPY-C3-M was carried out using a protein to BODIPY-C3-M mole ratio of 1:3 , incubated for 3 hours at 4°C by gentle agitation before LeuT was eluted from the NiNTA resin . Excessive dye was removed by washing the LeuT loaded Ni-NTA beads on a column . LRET based distance measurements were then carried out using freshly purified samples . POPC proteoliposomes were prepared as reported [59] from detergent solubilized and BODIPY-C3-M labeled LeuT using a protein:lipid ( w:w ) ratio of 1:100 . In brief POPC lipid ( Avanti Polar lipids Inc . ) was dried under a gentle stream of nitrogen to remove the organic solvent chloroform , remaining chloroform traces were removed overnight in a rotavapor . The lipid film was dissolved in 200 mM KCl or NaCl buffer and 20 mM HEPES at pH 7 . 5 to a final concentration of 20 mg/ml . The lipid suspension was then sonicated for 45 minutes ( using three 15-min cycles ) , flash frozen and slowly thawed to room temperature . Liposomes were extruded 11 times with a mini extruder ( Avanti lipids ) over a filter of pore size of 400 nm . Liposomes were destabilized with Triton X-100 and detergent solubilized LeuT added at a 1:100 protein:lipid ratio and incubated at room temperature for 30 min . Detergent was removed using biobeads ( Biorad ) followed by ultracentrifugation at 120000g for 90 min . The proteoliposomes were re-suspended to a final concentration of 100 mg/ml and stored at -80°C until use . First LRET measurements performed with a commercially available BODIPY-based acceptor fluorophore did not meet with any success . This was thought to be due to the extended length of the spacer of this probe joining the BODIPY dye with the thiol reactive maleimide subunit as well as to the nonsymmetrical attachment of the linker to the fluorescent moiety , both counteracting a well-defined spatial orientation of the probe in the protein . To overcome this problem the BODIPY probe 1 ( BODIPY-C3-M , Fig 7 ) has been developed in which a short three carbon chain symmetrically originates from the BODIPY dye and links it with the maleimide moiety . As starting material for the synthesis of BODIPY-C3-maleimide probe 1 , a BODIPY derivative analogous to 2 but equipped with a 3-bromopropyl residue in 10-position should be used . But when following a standard procedure [60] common for the preparation of 10-substituted BODIPY derivatives starting from 2 , 4-dimethylpyrrole and 4-bromobutyryl chloride , instead of the desired BODIPY derivative displaying a 3-bromopropyl residue , the BODIPY derivative 2 was obtained . As even upon extensive variation of the reaction conditions only 2 could be isolated , the formation of which was later on also published by others in the literature [61] , this compound , 2 , was used as starting material for the preparation of the target BODIPY 1 . To this end , compound 2 was subjected to an alkaline hydrolysis of the ester function to yield alcohol 3 which was subsequently transformed in the O-tosylated derivative 4 upon treatment with tosyl chloride in the presence of NEt3 and DMAP . Reaction of 4 with the potassium salt of phthalimide gave BODIPY derivative 5 . Subsequent treatment of 5 with hydrazine to liberate the primary amino function contained in 5 and with N-methoxycarbonylmaleimide without prior isolation of the amino derivative finally provided BODIPY probe 1 . The D535-30 bandpass filter ( Chroma ) was used for the measurements of the donor-emission ( viz . Tb3+ emission ) . The transmission range of this filter is centered on the second emission peak of Tb3+ at the wavelength of 540 nm . BODIPY-C3-M ( acceptor ) emission was recorded in the dark region between the first and the second Tb3+ peak by utilizing a filter specified for this wavelength range: D520/25m ( Chroma ) . However , we found poor signal to noise ratios in our recordings of the acceptor emission . We surmise that this was likely caused by quenching of the acceptor fluorophore emission by the environment . However , quenching of the acceptor emission has no repercussion on the Förster-distance . Accordingly , all analyses presented here are based on the parameters estimated from the fits to the donor decays in the absence and presence of the acceptor . We gated the photomultiplier tube at 300 μs after triggering of the laser pulse and fitted the donor emission by a sum of two exponentials . The faster component of around 400 μs was present in all conditions ( also in the fluorophore free condition ) indicating that this component is a non-specific component and independent of fluorophore absorption and emission ( S1 Table ) . Samples containing 1 μM detergent micelle solubilized LeuT in HEPES buffer , NaCL or KCL 200 mM , and 2 μM TbCL3 at pH 7 . 5 were placed onto the fine quartz coverslip . Liposome reconstituted LeuT samples were prepared containing 5 μM protein . HEPES buffer , NaCl or KCl 200 mM at pH 7 . 5 were the same outside and inside the liposomes . 10 μM TbCl3 was added to the outside of the liposomes . LBT-tag bound Tb3+ was excited by the UV laser pulse with a wavelength of 266 nm , fluorescence decay traces were recorded . Decay traces were fitted as shown in supplementary table and distances between LBT-tag bound Tb3+ and acceptor fluorophore were calculated from the decay constants τDA using the Förster relationship [62] . R is the calculated donor-acceptor distance , R0 is the reference distance , τD is the intrinsic donor decay , τDA is the sensitized donor decay constant due to excitation energy transfer from the donor to the acceptor . [3H]-Ala uptake was carried out at 30°C as reported previously [63] . Proteoliposomes were prepared as described above . The internal solution of proteoliposomes contained 200 mM KCl , 20 mM HEPES at pH 7 . 5 . Background binding was determined using gradient free proteoliposomes containing 200 mM NaCl instead of KCl . The uptake was initialized by diluting the proteoliposomes into external buffer ( 200 mM NaCl , 20 mM HEPES at pH 7 . 5 , at indicated concentrations of [3H]-Ala ) at 30°C . The reaction was stopped after two minutes by 10 folds dilution into ice cold stopping buffer ( 200 mMKCl , 20 mM HEPES at pH 7 . 5 ) . Proteoliposomes were then collected over nitrocellulose filters of 0 . 22 μm pore size . The filters were washed three times with 4 mL of ice-cold stopping buffer . The dried filters were immersed into 3 ml of scintillation cocktail . Radioactivity was measured in a liquid scintillation counter after mixing on a shaker for 2 hours . | Crystal structures of the bacterial small amino acid transporter LeuT provided structural evidence for the alternating access model . Thereby , these structures shaped our understanding of the mechanisms underlying substrate translocation by neurotransmitter transporters . However , it has been questioned , if the crystallized inward-open conformation of LeuT can exist in the membrane environment . Here we show that , while stable in detergent micelles , the inward-open conformation of LeuT is of high energy and undergoes structural readjustments . We use a multi-faceted approach including molecular dynamics simulations , scintillation proximity assays , free energy calculations and apply for the first time lanthanide resonance energy transfer measurements to verify the in silico predictions . In silico and in vitro approaches using the same conditions allowed us to combine the macroscopic experimental data with microscopic all atom results from simulations to identify the underlying driving forces: partitioning of charged and polar groups from the hydrophobic membrane interior to the hydrophilic environment . We propose that the inward-facing state shows a much smaller movement of TM1A , but large enough to create an access path to the S1 substrate binding site from the vestibule . | [
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] | 2016 | The Environment Shapes the Inner Vestibule of LeuT |
The processes underlying the evolution of regulatory networks are unclear . To address this question , we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms . Specifically , we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria . We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members , such as FNR , FixK , and DNR . While FNR , FixK , and DNR are each proposed to regulate different aspects of anaerobic metabolism , they are predicted to recognize very similar DNA target sequences , and they occur in various combinations among individual α-proteobacterial species . In this study , the composition of the respective FNR , FixK , or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes . The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon ( a FNR-type regulator ) in the α-proteobacterium Rhodobacter sphaeroides . Our results show that this approach correctly predicted many regulon members , provided new insights into the biological functions of the respective regulons for these regulators , and suggested models for the evolution of the corresponding transcriptional networks . Our findings also predict that , at least for the FNR-type regulators , there is a core set of target genes conserved across many species . In addition , the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species , possibly reflecting species-specific adaptation to environmental and other factors . The comparative genomics approach we developed is readily applicable to other regulatory networks .
Organisms rely on regulatory networks to integrate and process signals from various sources and to orchestrate the transcription of genes controlling a range of cellular processes . Importantly , changes in the architecture of these regulatory networks play a significant role in survival or adaptation of organisms to changing environments [1] . However , the processes underlying regulatory network evolution across related organisms are unclear . To address this problem we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict the architecture and infer the evolutionary history of regulatory pathways controlling the biological response to O2 . Fundamental to the function of transcriptional regulatory networks are DNA-binding proteins that recognize specific DNA target sequences to modulate gene expression . Accordingly , identifying the set of target genes for each transcription factor is a crucial step toward understanding the functions of their target genes , elucidating the architecture of regulatory networks , and inferring how these networks have evolved . Yet , the set of target genes recognized by a given transcription factor is rarely available for a regulator within or across species . Because related organisms often rely on orthologous regulators for similar functions , comparative genomics approaches offer the possibility to characterize regulons that are widely conserved across organisms , as well as to identify important exceptions . In this study , we used computational and high-throughput experimental methods to predict the members of transcriptional regulatory networks that are conserved across a large number of diverse bacteria . Our analysis focused on transcriptional regulatory networks that are known or predicted to function under low O2 or anaerobic conditions . These transcriptional regulatory networks are often conserved across species because the availability of O2 has major consequences for many critical metabolic activities . For example , in bacteria , O2 availability controls the type of energetic pathway used for growth ( fermentation , respiration , photosynthesis in anaerobic phototrophic bacteria , etc . ) and acquisition of nutrients ( nitrogen or carbon dioxide fixation , or metal uptake , etc . ) , which are critical to the survival of cells , communities , and entire ecosystems [2] . While the physiological effects of O2 on these processes are fairly well established , the transcription factors , target genes , or regulatory networks controlling these functions are not as well understood . Consequently , information on the properties of these regulatory networks is necessary in order to identify conserved functions that are controlled by O2 availability across related organisms . FNR , FixK , and DNR are related , and relatively well-studied members of the CRP/FNR super-family of transcription factors that control anaerobic processes in many proteobacteria [3] . FNR is a global regulator of anaerobic gene expression in Escherichia coli and its activity is directly inhibited by O2 via destruction of a labile iron-sulfur cluster [2] , [4] . FNR orthologs are widely distributed across bacteria [3] , but , to date , their function has been mostly studied in E . coli and other γ-proteobacteria [5]–[7] . FixK is another member of the CRP/FNR super-family that controls gene expression in an O2-dependent manner [8] . For example , in the α-proteobacterium Bradyrhizobium japonicum FixK2 plays a role in establishing the legume root-nodule symbiosis that occurs at low O2 tensions [8] . However , unlike FNR , the activity of FixK2 is not directly controlled by O2 . Instead , fixK2 expression is controlled by the O2-responsive two-component signal transduction system FixLJ [9] . Finally , DNR , another member of the CRP/FNR super-family , controls the expression of genes needed for anaerobic denitrification in Pseudomonas aeruginosa [10] . DNR activity responds to nitric oxide ( NO ) , an intermediate of denitrification [11] . While the functions of FNR , FixK , and DNR have been established in several model organisms , it is not clear whether these roles are conserved across other species . Homologs of FNR , FixK , and DNR are known or predicted to exist in a large number of diverse bacteria [3] , but the target genes for these regulators have not been extensively studied . In addition , the fact that FNR , FixK , and DNR have significant amino acid sequence similarity in their DNA-binding domains and recognize very similar DNA target sequences [3] makes it challenging to predict their respective target genes . It also raises the question of how these functions can be selectively controlled in organisms that contain different numbers of one or all three of these proteins . Furthermore , because it is not possible to rely solely on the presence of a predicted upstream DNA target sequence as a means to link a target gene to the regulon of one of these transcription factors , it is difficult to predict the regulatory network or biological functions controlled by FNR , FixK , or DNR orthologs within or across different organisms using current approaches . These challenging properties illustrate why an approach integrating additional information is necessary to predict the regulatory networks of related proteins across organisms . In this report , we describe a computational method that takes advantage of the large number of available bacterial genome sequences to predict the conserved portions of the respective regulons of related transcription factors . After clustering members of the CRP/FNR super-family into sets of orthologs , we predicted genes that are controlled by FNR , FixK , or DNR proteins by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes . We chose to focus on α-proteobacteria since these species are metabolically diverse , have several unique anaerobic lifestyles ( photosynthesis , symbiosis , nitrogen fixation , denitrification ) when compared to organisms analyzed previously , and often contain multiple protein members of one or more of the CRP/FNR sub-families . To provide experimental support for the computational predictions , we defined genes in the Rhodobacter sphaeroides FnrL ( a FNR-type regulator ) regulon using a combination of chromatin immuno-precipitation on a chip ( ChIP-chip ) assays [12] and publically available transcription profiling data [13]–[16] . The results reported here refined predictions for the DNA target sequences of members of the CRP/FNR super-family and predicted conserved members of the FNR , FixK , and DNR regulons across α-proteobacteria . The patterns of regulon conservation observed across the α-proteobacteria phylogeny led us to propose that the regulon of each conserved regulator is composed of a core set of genes conserved across species . We also propose that this core regulon is expanded in each species by incorporating genes whose functions are selected by the conditions found in their ecological niches .
Our approach to determining the members of the FNR , FixK , and DNR regulons across the α-proteobacteria was to first identify all the sub-families of the CRP/FNR super-family in α-proteobacteria and then predict their DNA target sequences . Phylogenetic analysis of the CRP/FNR super-family from bacteria in 2002 [3] , revealed 21 distinct protein sub-families , which included FNR , FixK , and DNR . Because a larger number of α-proteobacterial genomes were available in 2009 , we performed a similar analysis to determine the representation and distribution of these sub-families within the α-proteobacteria . In addition , a second goal was to determine whether any new sub-families share a similar predicted DNA target sequence to FNR , FixK , and DNR that would confound our analysis . After searching all sequenced α-proteobacterial genomes in the Integrated Microbial Genomes database ( img . jgi . doe . gov ) in January 2009 ( ∼150 genome sequences ) for proteins of the CRP/FNR super-family , we first found that α-proteobacteria from the genera Rickettsia , Ehrlichia , Wolbachia , and Bartonella do not possess proteins in the CRP/FNR super-family . Accordingly , these genera were not studied further . Among the remaining genera , we selected 87 representative α-proteobacterial species that altogether contained 697 proteins in the CRP/FNR super-family ( Table S1 ) . To assemble these 697 proteins into functionally related sets , we took a clustering approach derived from the ORTHOMCL algorithm [17] , which identifies connected sets of proteins in networks constructed from protein sequence similarities . When we applied this clustering approach multiple times with increasing stringency , we uncovered a hierarchical relationship between proteins of the different families ( Figure 1 ) . Ultimately , 607 of the 697 proteins were clustered into 7 major sub-families that could not be further sub-divided solely by more stringent clustering , suggesting that the proteins within each of these 7 major sub-families are very closely related . The 7 α-proteobacterial protein families and their relationships are also consistent with the phylogenic tree obtained by neighbor joining of the 2002 dataset [3] , supporting the conclusion that both approaches are capturing the same functional groups . However , this approach failed to differentiate between FNR- and FixK-type proteins because it only considered global amino acid sequence similarities . Therefore , we subsequently divided the mixed FNR-FixK group into FNR or FixK groups based on the known properties of E . coli FNR . Specifically , E . coli FNR and presumably its orthologs have 4 conserved cysteine residues that are essential to coordinate an O2-labile [4Fe-4S] cluster [18] , . Proteins within the mixed FNR-FixK group that lack any of the cysteine ligands for the [4Fe-4S] cluster are not expected to sense O2 directly and thus , were assigned to the FixK group . After sub-dividing the FNR-FixK group into a FNR group , members of which possess all 4 of the conserved cysteine residues , and a FixK group , which includes proteins that lack one or more of these 4 cysteines , 8 major protein sub-families of the CRP/FNR super-family were defined . The resulting 8 major protein sub-families include members of the FNR , FixK , DNR , NnrR , A , B , C , and G groups of the CRP/FNR super-family using the nomenclature described by Korner et al . [3] ( Figure 1; locus IDs for each sub-family are provided in Table S1 ) . Our analysis indicates that only the 8 sub-families of the 21 sub-families of the CRP/FNR super-family identified across all species available in 2002 [3] are significantly conserved across the α-proteobacteria considered in our study , and no new conserved sub-families in addition to the 21 were identified . Proteins in the 11 remaining sub-families of the CRP/FNR super-family , such as CRP or CooA , were found in some of the 87 α-proteobacteria , but these other sub-families had a very limited distribution across species and clustered into minor groups ( Figure 1 ) . The FNR sub-family is composed of 75 members distributed in 66 species and is the most widely distributed of the 8 sub-families of CRP/FNR super-family . The FixK sub-family comprises 76 proteins distributed in the genomes of 44 species . While members of the FixK sub-family are not predicted to sense O2 directly , the activity of some family members is indirectly regulated by O2 through the FixLJ two-component system [20] . However , we were unable to predict whether all the FixK orthologs were regulated by FixLJ since it is difficult to predict which species have FixLJ orthologs because functionally distinct two-component regulators have very similar amino acid sequences [21] . Nevertheless , FNR orthologs and some FixK orthologs are expected to regulate genes that have functions relevant to adapting to changes in O2 levels . The nitric oxide-responsive DNR and NnrR groups of regulators contain 58 proteins in 37 genomes and 52 proteins in 40 genomes , respectively . In contrast , the largest sub-family of proteins in α-proteobacteria is group A , which is composed of 152 uncharacterized proteins that are distributed in the genomes of 59 of the 87 species examined . The next largest sub-family , group C , contains 116 uncharacterized proteins that are distributed within the genomes of 33 species . Most of the species of α-proteobacteria , which possess a protein in group C , belong to the Rhizobiales order , suggesting that the proteins in this group are associated with a biological function that is conserved in these α-proteobacteria . The other two major groups , B ( 34 proteins in 28 genomes ) and G ( 44 proteins in 35 genomes ) , are also composed of uncharacterized proteins . In summary , we predict that α-proteobacterial species possess different combinations of CRP/FNR-type regulators , including the FNR , FixK , and DNR families . Previous reports indicated that representative members of the FNR , FixK , and DNR families recognize similar DNA target sites [3] , [8] , [22] , [23] . To determine , ( i ) if all proteins within and across each of the FNR , FixK , or DNR families share a conserved DNA target sequence and ( ii ) if any of the other 5 major sub-families of the CRP/FNR super-families also recognize similar sites , we analyzed amino acid sequences in the helix-turn-helix ( HTH ) DNA-binding domain within each sub-family . This information was then used to predict the corresponding DNA target sequences ( Figure 2 ) . For this analysis , we first aligned the amino acid sequences of the C-terminal domains that contain the predicted HTH motif of the above set of 697 proteins . The multiple sequence alignment was then divided into the 8 respective sub-families . We also mapped onto the alignments the three corresponding residues of the E . coli CRP protein that make direct contact with DNA in the X-ray structure of the binary complex [24] . These CRP residues were used as a reference to assess conservation of the residues that would be predicted to determine DNA target sequence specificity between and within sub-families . This mapping revealed that two of the three corresponding residues in the FNR , FixK , and DNR sub-families are conserved across all members of these groups ( glutamate and arginine at positions 17 and 21 , respectively in Figure 2A ) . In addition , neighboring residues , which may directly or indirectly affect DNA target specificity , are also well conserved across these three protein families ( positions 12 , 13 , 20 and 26 in Figure 2A ) . Furthermore , Glu 209 ( position 17 ) , Ser 212 ( position 20 ) , and Arg 213 ( position 21 ) have all been implicated in specific DNA binding by E . coli FNR [25] , [26] . The HTH domains of the remaining protein groups in the CRP/FNR super-family differ significantly from the ones of FNR , FixK , and DNR and from each other suggesting specialization of DNA binding ( Figure 2A ) . In summary , even though the specific contribution of each residue to DNA target specificity is not totally understood for members of the FNR , FixK , and DNR families , the extensive conservation of amino acid residues in their HTH domains supports the hypothesis that proteins from these three sub-families , but not from the other 5 sub-families , recognize similar DNA target sequences . To predict the corresponding DNA target sequences for proteins in the 8 CRP/FNR sub-families and to assess the predictions made from the HTH domain sequence analysis , we took advantage of the fact that transcription of genes encoding the proteins in the CRP/FNR super-family is often auto-regulated . Thus , we searched for conserved DNA sequences in the regions upstream of the structural genes in each group . The one exception to this approach was the FixK sub-family because transcription of fixK in Bradyrhizobium japonicum , and presumably orthologs in other species , are regulated by the response regulator FixJ . Indeed , a promoter sequence analysis revealed that only 20 of the 76 FixK orthologs may be auto-regulated . Thus , we derived the FixK binding motif from the promoter sequences of previously predicted targets genes in B . japonicum [8] and their orthologs in α-proteobacterial genomes containing orthologs of FixK . The results of this analysis showed that the predicted DNA target sequences for members of the FNR , DNR and FixK groups are virtually identical ( Figure 2B ) . In contrast , analysis of upstream DNA sequences for the other 5 major groups of α-proteobacterial members of the CRP/FNR super-family indicated that these proteins bind related but non-identical target sites . For example , genes encoding proteins in the NnrR group are preceded by a DNA sequence that contains only 6 of the 10 conserved positions of the FNR , FixK , or DNR motifs ( Figure 2B ) . This was not surprising since proteins in the NnrR group share less conserved residues with the FNR and FixK HTH domain ( notably , residues at position 17 are different in Figure 2A ) . In conclusion , these findings reinforce the proposition that proteins in the FNR , FixK , and DNR groups recognize very similar , if not identical , DNA target sequences in the 87 selected α-proteobacteria . Knowing the DNA target sequence for a transcription factor often provides sufficient information to predict computationally its target genes within and across genomes . However , using the deduced DNA binding sites to predict the respective FNR , FixK , and DNR regulons presented a particular challenge because the three regulators recognize very similar DNA target sequences ( Figure 2B ) and because the selected 87 α-proteobacterial species often possess different numbers or combinations of the FNR , FixK , and DNR proteins ( Table S1 ) . For example , Rhodopseudomonas palustris TIE-1 possesses three proteins representing each of the FNR , FixK , and DNR groups , while Hoeflea phototrophica DFL-43 has three proteins in the FNR group and none in the FixK , or DNR groups . Therefore , without additional information it was not possible to determine the respective regulons of FNR , FixK , and DNR by testing solely for the presence of a DNA target sequence that is common to these three regulators . However , if we assumed that the composition of regulons co-evolved with the function of their respective regulators , then we would expect that phylogenetic occurrence profiles across related species should contain information about the functional relationships between target genes and regulators . This information can then be used to assign target genes to their historical regulator even in situations where multiple regulators might have overlapping regulons . To characterize the evolutionary relationship between FNR , FixK , or DNR , and putative target genes , we improved upon a computational method that was used previously to predict regulon members of alternative sigma factors [12] by integrating it with an approach first introduced by Pellegrini et al . , who compared phylogenetic profiles of sets of orthologous genes across multiple species to infer functional links between genes [27] ( Figure 3 ) . Because the DNA target sequence of a particular regulator represents the functional link between the regulator and its target genes , we expected that the presence of the binding sequences in the promoter regions of the target genes to co-evolve also with the regulator function . Therefore , taking into account the correlation between the phylogenetic profiles of target genes and regulators should allow us to assign target genes to their historical regulators and define their respective core regulons even if the transcription factors have indistinguishable DNA-binding sequences . Note , we used the term “core regulon” to refer to a historical consensus that emerged from the comparison of the 87 bacteria considered in this study . To assign predicted target genes to FNR , FixK , or DNR and thus , reconstruct their core regulons , we identified all occurrences of the shared DNA target sequence in the promoter regions of genes in each of the 87 genomes ( with an estimated false-discovery rate of ∼15% and p-value≤0 . 001 ) ( Figure 3 , Step A ) . Because bacterial genes are often organized in transcription units , where multiple genes share a common promoter , each identified DNA target sequence from step A was then linked to all the genes within the nearest predicted transcription unit ( see Materials and Methods for how we predicted transcription units ) . Next , we assembled sets of orthologous genes by clustering all genes across the 87 genomes using the same approach that we used to identify the CRP/FNR super-family functional groups . This approach predicted ∼25 , 000 distinct sets of orthologous genes distributed in the genomes of the 87 α-proteobacterial species we analyzed . Then , we constructed phylogenetic profiles of target genes based on the occurrence of the common DNA-binding sites within each set of orthologous genes ( Figure 3 , Step B ) . Finally , to predict the respective regulons of FNR , FixK , and DNR , for every set of orthologs , we calculated the similarity between the phylogenetic profiles of ( i ) target DNA-binding sites and ( ii ) FNR , FixK , or DNR ( Figure 3 , Step C ) . This approach allowed us to assign sets of target genes to the regulator with which they shared the most similar phylogenetic profile ( Figure 3 , Step D , Figure 4 , and Table 1 ) . To restrict our predictions to the most conserved members of the respective regulons , we set a cut-off to include target genes that had a phylogenetic profile that was at least 20% similar to one of the three regulators . Considering one example of regulon predictions , the predicted target genes ( in yellow in Figure 4 ) of Loktanella vestfoldensis were assigned mostly to the FNR regulon ( Figure 4 ) , consistent with the fact that L . vestfoldensis possesses a FNR-type regulator but no FixK- or DNR-type regulators . In addition , orthologs of L . vestfoldensis target genes were also predicted to be FNR target genes in many other α-proteobacterial species . On the other hand , our predictions probably did not reveal the entire FNR regulon of L . vestfoldensis since this method only captured target genes that are conserved in at least 20% of the species that possess FNR . From this comparative analysis , we were able to predict , using genomic sequence information only , conserved members of the FNR , FixK , and DNR regulons , even though each of these proteins recognizes a very similar DNA target sequence . Several patterns emerged from the distribution of the predicted regulons ( Figure 4 ) . First , the predicted FNR regulon appeared to be more conserved than those for FixK , or DNR across the 87 α-proteobacterial species . The most conserved part of the predicted FNR regulon contained 6 sets of orthologous genes ( including genes encoding FNR itself ) in about 60% of the genomes . In addition , a predicted FNR regulon of 20 sets of orthologs was present in 27 species of the Rhodobacterales order ( Figure S1 ) . Conversely , the composition of the predicted FNR regulon split the Rhizobiales order into two groups . The first group of Rhizobiales ( 18 species containing Rhizobium , Mezorhizobium , Sinorhizobium , Agrobacterium and others ) had a fairly well conserved FNR regulon of ∼13 sets of orthologs . In contrast , in the second group of Rhizobiales ( 19 species , containing Bradyrhizobium , Nitrobacter , Rhodopseudomonas , Methylobacterium and others ) , the predicted FNR regulon was significantly reduced or missing . On the other hand , this second group of Rhizobiales is predicted to possess a well-conserved FixK regulon ( 18 sets of orthologs ) , possibly indicating a greater role of FixK in the anaerobic or low-oxygen lifestyle of these bacteria . Finally , the 11 sets of orthologs in the predicted DNR regulon were not well conserved or consistent within the species phylogeny , suggesting that DNR plays a more limited or a specialized role in gene expression among α-proteobacteria than either FNR or FixK . In summary , for each of the three global transcription factors , our analysis predicted regulon members that are conserved across α-proteobacteria as well as target genes that were found only in a subset of organisms . To evaluate our predictions , we directly identified members of the R . sphaeroides FnrL regulon using chromatin immuno-precipitation on a chip ( ChIP-chip ) assays , DNA target sequence analysis , and expression profile clustering . FnrL is a member of the FNR sub-family and contains an O2-labile [4Fe-4S] cluster ( T . Patschkowski and PJ . Kiley , unpublished data ) , like its homolog FNR in E . coli [4] . To probe genome-wide interactions of FnrL with DNA in vivo , we used antibodies to FnrL for ChIP-chip assays [12] . FnrL activity is high in the absence of O2 [28] , so we analyzed these interactions in wild-type R . sphaeroides growing under anaerobic conditions in the presence of light ( photosynthetic growth conditions ) . By identifying regions of the genome that were significantly enriched by immuno-precipitation with antibodies against FnrL ( p-value ≤0 . 01 ) in three biological replicates , we found 27 sites bound by FnrL ( Table 2 , Figure 5 ) . Of these 27 sites , 6 were in the promoter regions of genes previously shown to require FnrL for increased activity in the absence of O2 [28]–[32] , illustrating that this assay identifies bona fide FnrL binding sites . To test which FnrL ChIP-chip sites affect gene transcription , we also used ChIP-chip assays to score binding by the major sigma factor , σ70 , and the β′ subunit of RNA polymerase in the same cultures . This analysis showed that of the 27 regions bound by FnrL , 22 were also bound by σ70 ( p-value ≤0 . 01 ) ( Table 2 ) and the β′ subunit of RNA polymerase , which also extended as expected across the entire length of transcription units , indicating that these genes were actively transcribed under these conditions . The lack of σ70 binding in the other 5 of the 27 genomic regions may indicate that FnrL has a negative effect on transcription , possibly by occluding occupancy by σ70-containing RNA polymerase . However , it is also possible that a different σ subunit recognizes these promoters , or that no active promoters are located near these regions under our growth conditions . Overall , our analysis shows that FnrL binds DNA under anaerobic conditions in vivo and suggests that by this criterion , the FnrL regulon contains at least 27 operons . To test if the genomic regions bound by FnrL in vivo contained the canonical DNA target sequence predicted to be recognized by this protein , TTGAT-N4-ATCAA [28]–[31] , we used the MAST software to search the corresponding genomic regions [33] for sequences matching the α-proteobacterial FNR DNA target position-weighted matrix we derived ( Figure 2B ) . Of the 27 regions bound by FnrL , 25 contain a close match to the canonical FNR target sequence ( log-likelihood score ≥1613 . 5 ) ( Table 2 ) . The other two sites contain sequences with less similarity to the canonical sequence and may represent lower-affinity FnrL binding sites or ones where FnrL binding is possibly facilitated by another factor . This analysis supports the prediction that R . sphaeroides FnrL recognizes a canonical sequence that is very similar to both the one we predicted for the FNR sub-family in α-proteobacteria ( Figure 2B ) and the motif recognized by E . coli FNR [34] . To identify additional potential binding sites that may have been missed in the ChIP-chip experiment , we also searched the entire genome for matches to the FNR DNA target sequence . Using a log-likelihood score ≥1613 . 5 in order to keep the false-discovery rate ≤10% , we found only 10 additional matches to the target sequence ( Table 2 ) . Of these 10 matches , 7 are located within protein coding sequences and three others fall within intergenic regions . To identify FnrL regulated transcription units , genes within 500 bp on either side of the 37 potential FnrL target sites ( 27 sites identified by ChIP-chip and the 10 putative FnrL binding sites identified by sequence analysis ) were collected and analyzed for O2-dependent changes in transcript abundance using publically available global gene expression data from R . sphaeroides [14]–[16] , [35] . When the transcript abundance profiles were clustered by similarity ( Pearson correlation coefficient ) , the RNA transcript levels of 68 putative FnrL target genes showed O2-dependent expression patterns ( Figure 6 ) . One large cluster of co-expressed genes ( cluster A in Figure 6 ) contained 51 protein-coding sequences organized in 20 predicted transcription units . The transcript levels from these 51 genes negatively correlate with culture O2 levels , consistent with the hypothesis that FnrL activated their expression . This conclusion is also supported by the co-occupancy of FnrL , σ70 and core RNA polymerase at these sites under anaerobic conditions using the ChIP-chip assay . Another cluster of co-expressed genes ( cluster B; 10 open reading frames in 4 predicted transcription units ) also showed O2-dependent changes in RNA abundance . However , cluster B , unlike cluster A , showed less accumulated RNA under anaerobic conditions in the light ( the conditions we used to monitor FnrL binding in ChIP-chip assays ) than in cells grown anaerobically in the dark . Because FnrL is expected to have the same activity in anaerobic conditions whether light is present or not ( as shown by cluster A expression profile in Figure 6 ) , we propose that the transcription of genes in cluster B is affected by an additional , possibly light-responsive factor . Indeed , PpsR/AppA is such a candidate factor since it is known to also control expression of one operon in cluster B ( RSP0696-3 ) in a light- and O2-dependent manner [13] , . Finally , transcript levels from a third cluster of co-expressed genes ( cluster C; 7 open reading frames in three putative transcription units ) that were bound by FnrL under anaerobic conditions in the light decreased as culture O2 tensions were lowered , so we propose that FnrL directly repressed transcription of these genes . Overall , our results predict that the 27 transcription units found in gene expression clusters A , B , and C ( containing a total of 68 genes ) are under direct positive or negative control by FnrL . Twenty-four of these 27 transcription units contained promoter regions bound by FnrL in the ChIP-chip assays ( a total of 21 FnrL-bound regions since some of these binding sites were between divergently transcribed operons ) ( Table 2 ) . The remaining 3 transcription units ( RSP0692-89 , RSP3341 , and RSP3640-3 ) were associated with a FnrL DNA target sequence ( 3 of the 10 putative sites detected by sequence analysis ) but FnrL-binding was not detected under growth conditions used for ChIP-chip assays . Nevertheless , we propose that these 3 transcription units are FnrL-regulated because of the evidence provided by the gene expression profiling experiments ( Table 2 ) . Finally , 6 regions bound by FnrL in the ChIP-chip assays were not associated with any known O2 regulated transcription units . These FnrL-occupied sites could represent genomic regions in which FnrL binding did not influence the transcription of neighboring promoters in an O2-dependent manner under the conditions explored , ones in which activity of a co-activator is required that is not functional under our growth conditions , or ones in which FnrL controlled expression of transcripts that were not annotated , such as small RNAs . The predicted function of members within this proposed FnrL regulon is consistent with prior knowledge about the anaerobic lifestyle of R . sphaeroides . Functions encoded by members of the FnrL regulon include many components of the electron transport chain . For example , transcription of operons that encode subunits of low-affinity cytochrome c oxidase ( RSP1826-29 and RSP1876-77 ) was apparently repressed by FnrL . In contrast , expression of genes encoding the high-affinity cytochrome cbb3 oxidase ( RSP0693-96 ) , which supports respiration in microaerobic conditions , enzymes for ubiquinone synthesis ( RSP0467-8 ) , and the membrane-bound NADH oxidase ( RSP0100-12 ) are proposed to be directly activated by FnrL . Other FnrL-activated functions are involved with the anaerobic lifestyle of R . sphaeroides , such as tetrapyrrole ( RSP0317 , RSP0699 , and RSP2984 ) , bacteriochlorophyll biosynthesis ( RSP0276-81 ) , or transport of ferrous iron ( RSP1817-19 ) , which is predominant in the absence of O2 . Our data also predicts that expression of dksA ( RSP0166 ) , which encodes a homolog of a global regulator of stable RNA synthesis and several other cellular functions [38]–[41] , is a newly identified target for activation by FnrL under anaerobic conditions in R . sphaeroides . A comparison of the computational predictions from the comparative genomics analysis and the experimentally determined R . sphaeroides FnrL regulon showed that of the 20 sets of orthologs composing the FNR regulon proposed to be conserved across α-proteobacteria ( Figure 4 ) , 17 are part of the R . sphaeroides FnrL regulon ( Figure 6 , Table 2 ) . The remaining three sets of orthologs computationally predicted to be in the conserved FNR regulon ( #1083 , #2905 , and #555 in Figure 4 ) contained two R . sphaeroides genes ( RSP2905 and RSP1825 ) that were not part of the FnrL regulon because their transcript levels were not regulated in an O2-dependent manner and no FnrL binding was detected in the ChIP-chip experiment . Nevertheless , it cannot be excluded that FnrL regulates these two genes under growth conditions different from those examined in this study . On the other hand , two experimentally confirmed R . sphaeroides FnrL target genes ( RSP0465 and RSP0466 ) were assigned to the DNR regulon by our computational analysis ( Figure 4 , Table 1 ) . Since R . sphaeroides does not possess a DNR ortholog , these two genes may have been acquired through horizontal gene transfer and placed under the control of FnrL . Overall , the agreement between the R . sphaeroides FnrL regulon based on experimental and comparative genomic analyses illustrates the utility of the computational methods in correctly predicting target genes for transcription factors . Nevertheless , the size of the experimentally determined R . sphaeroides FnrL regulon ( 68 genes ) is larger than the one proposed to be conserved across α-proteobacteria ( 20 sets of orthologs ) ; leaving us without information about the regulation of ∼50 predicted FnrL target genes in other α-proteobacteria . Our comparative genomics analysis selected only target genes that were conserved in at least in 20% of the species possessing FNR orthologs . Therefore , to examine to what extent the additional ∼50 genes of the R . sphaeroides FnrL regulon were conserved within the 87 α-proteobacteria , we identified the sets of orthologous genes among these bacteria that corresponded to the FnrL target genes and determined which of their promoters contained a predicted FNR DNA target sequence . The results of this analysis indicated that very few of the other α-proteobacteria have FNR target genes in common with R . sphaeroides beyond the 20 conserved sets of orthologs ( Figure 7 , Table S2 ) . As expected , the predicted FNR regulon of another R . sphaeroides strain ( ATCC 17025 ) overlaps significantly with the FnrL regulon of R . sphaeroides 2 . 4 . 1 . In addition , only the FNR regulons of the R . palustris strains TIE-1 and HaA2 , which are photosynthetic bacteria , were predicted to have a significant number of orthologous genes with the extended R . sphaeroides FnrL regulon . Interestingly , the predicted overlap of the FnrL regulons between R . sphaeroides strain 2 . 4 . 1 and R . palustris strains TIE-1 and HaA2 is larger than the overlap between R . sphaeroides and more closely related species of the Rhodobacterales order . In summary , 17 of the 68 experimentally determined members of the R . sphaeroides FnrL regulon were also predicted to be members of a conserved or core FNR regulon across α-proteobacteria . Our data also indicated that R . sphaeroides FnrL controls expression of additional genes in a so-called extended regulon that is not always shared with either other purple non-sulfur α-proteobacteria or other closely related species . Overall , our analysis of FNR target genes across the α-proteobacteria indicated that the regulon of orthologous regulators can vary dramatically over a relatively short evolutionary time .
By determining the similarity between the phylogenetic profiles of each regulator and potential target genes across genomes , we were able to assign target genes to one of the three regulators . In many cases , these assignments were supported by either prior knowledge or experimental data provided in this study . For example , 17 of the 19 predicted members of the core FNR regulon were shown to be direct FnrL targets under the conditions tested . For the B . japonicum FixK regulon , expression of blr6070 , blr6071 , blr4637 , blr0497 and blr6074 ( ID 3100 , 2589 , 1551 , 5478 and 2256 ) was shown to depend on FixK2 ( a FixK-type regulator ) [8] , [42] , as we predicted . We also correctly predicted that expression of RPA4249 , RSP4237 , RPA4238 , RPA4236 , RPA1673 , RPA4235 , RPA1672 and RPA4239 ( ID 114 , 321 , 329 , 1387 , 2238 , 2551 , 2810 and 3532 ) would be dependent on FixK in R . palustris [43] . The roles of FixK or FNR in controlling expression of other members of the predicted regulons remain to be tested , but based on our data we expect that many of these candidates will be direct target genes of these transcription factors in α-proteobacteria . Unfortunately , no experimental analysis of the DNR regulon is available in any α-proteobacterium . However , the annotation of the putative target genes of DNR , which is a known nitric oxide sensor , indicates that the predicted role of several members of this regulon is in denitrification , which produces nitric oxide as an intermediate ( ID 1696 , 2903 , 3120 , 4023 and 4488 ) . Because our approach assigned target genes to regulators based on correlations rather than absolute concordance of their respective phylogenetic occurrence profiles , it captured the general patterns emerging from the evolutionary histories of the regulons instead of the exact composition of each regulon in every species . Consequently , regulons were occasionally predicted to exist in species that did not possess the corresponding regulator . For example , we predicted a Caulobacter FNR regulon even though these bacteria lack a gene encoding a FNR-type regulator . To explain this observation , we propose that Caulobacter species once contained a FNR-type regulator that was displaced by a FixK-type regulator , which now controls expression of these target genes in an O2-regulated manner . Indeed , some of these Caulobacter crescentus genes are known to require FixK and the O2-sensing two-component histidine kinase and regulator , FixLJ for their expression [44] . On the other hand , we also predict that some species possess regulators but lack members of the corresponding core regulon . To explain this observation , we propose that the functions of these orphan regulators have diverged sufficiently to regulate completely different sets of target genes and may actually respond to signals different from those that control activity of FNR , FixK , or DNR . Therefore , these orphan regulators may not actually be orthologs of FNR , FixK , or DNR . Additional experiments are needed to test these hypotheses . Because FNR , FixK , and DNR recognize very similar target DNA sequences , cells containing multiple regulators may have target genes that belong to more than one regulon . For example , FNR and FixK are likely to have overlapping regulons because both FNR and FixK activity is regulated by O2 [2] . Indeed , 5 members of the known B . japonicum FixK regulon ( ID 1331 , 1264 , 1230 , 1774 and 129 in Table 1 ) and 9 genes from the characterized R . palustris FixK regulon ( ID 74 , 129 , 301 , 1230 , 1264 , 1289 , 1331 , 1348 and 1987 in Table 1 ) [8] , [43] are part of our core FNR regulon . These results indicate that , at least in these two species , significant overlap between the FNR and FixK regulons is tolerated . They also illustrate that our computational approach was able to capture the potential overlap between regulators and target genes . In contrast , there might be less overlap between members of the DNR and either the FNR or FixK , regulons . Indeed , in Paracoccus denitrificans , which possesses both a FNR- and a DNR-type regulator ( named FnrP and NNR respectively ) [45] , each protein regulates discrete sets of target genes even though the respective DNA target sequences for these two proteins are very similar . To explain the absence of regulon overlap between FnrP and NNR , Van Spanning et al . proposed that other proteins or subtle differences in the DNA binding site play a role in target gene discrimination [45] . Even though the underlying mechanisms for discrimination are unknown , we did not predict significant overlap between the core DNR regulon and those for FNR or FixK . Thus , the phylogenetic relationship between regulators and target genes was able to compensate for missing information about differences between the target sequences of related transcription factors . Together , these results demonstrate that phylogenetic profiles of regulators and potential target genes can be used successfully to predict the members , function and potential overlap of transcriptional regulatory networks . One benefit of our approach is its ability to decipher relationships between regulators and target genes despite possible overlap in regulon structure which may occur because of similarities in DNA binding sites . Consequently , our assignments provide testable hypotheses about the architecture and role of FNR , FixK , and DNR across α-proteobacteria . Our analysis predicts that FNR is the most widely distributed of these three transcription factors we analyzed , since it is found in the genome of 87 α-proteobacteria ( Figure 1 ) . For the most part , the genes found in a predicted core α-proteobacterial FNR regulon encode enzymes for micro-aerobic or anaerobic respiratory growth , including synthesis of heme ( ID 1230 and 74 ) and the high-affinity cytochrome cbb3-type oxidase ( ID 1289 , 1331 , 1348 , 1915 and 2282 ) ( Table 2 ) . Other genes in the core α-proteobacterial FNR regulon were predicted to encode metal cation transporters ( ID 28 and 1758 ) that are required for activity of cytochrome cbb3-type oxidase in B . japonicum and R . sphaeroides [46] , [47] . Since the cytochrome cbb3-type oxidase contains a copper cluster , it was proposed that these putative transporters maintain cellular copper homeostasis [48] . The ompW gene was also predicted to be part of the core α-proteobacterial FNR regulon and its expression was decreased under aerobic conditions in R . sphaeroides . In Salmonella enterica , OmpW mediates transport of methyl viologen ( paraquat ) [49] , a compound which can generate reactive oxygen species under aerobic conditions [50] . Thus , it is possible that reducing OmpW protein levels in α-proteobacteria in response to increases in O2 tension also helps reduce damage from reactive oxygen species , possibly by preventing the uptake of redox mediators . Another member of the predicted core α-proteobacterial FNR regulon is uspA , a universal stress family protein , which is involved in stress resistance [51] and required for survival during energy starvation under anaerobic conditions in Pseudomonas aeruginosa [52] . In contrast to the wide distribution of FNR homologs , another CRP/FNR family member , FixK , is generally restricted to α-proteobacteria in the Rhizobiales order . The predicted core FixK regulon was best defined in the Bradyrhizobiaceae family ( Nitrobacter , Bradyrhizobium , and Rhodopseudomonas ) , where it includes genes encoding sensing components of the O2-responsive signal transduction cascade , FixLJ ( ID 332 and 114 ) [8] , [42] . Moreover , species in the Bradyrhizobiaceae family that have a well-defined FixK regulon , also have only 7 genes predicted to be part of the core conserved FNR regulon . Another characteristic of the FixK family correlating with this observation is provided by the recent finding that B . japonicum FixK2 activity can be regulated by modification of a cysteine residue in response to oxidative stress [53] . Indeed , a protein sequence alignment of all the FixK orthologs analyzed in this study revealed that this particular cysteine residue is conserved only in Nitrobacter , Bradyrhizobium , and Rhodopseudomonas species , indicating that FixK may have a specialized role in these species when compared to the FixK family members in the rest of the α-proteobacteria . Taken together , we propose that an extended FixK regulon , a reduced FNR regulon , and the presence of a conserved reactive cysteine residue in some FixK proteins is part of an evolutionary transition in which FixK acquired some FNR target genes and other functions to integrate them into the lifestyle of Bradyrhizobiaceae species . Indeed , it appears that FixK-type regulators diverged from the FNR-type group only very recently [3] , probably as an adaptation to a specific ecological niche or signal encountered in their environments . On the other hand , this model suggests that the FixK orthologs present in α-proteobacterial species other than Nitrobacter , Bradyrhizobium , or Rhodopseudomonas , do not share a common set of target genes and consequently have unknown roles in the transcriptional regulatory networks of these bacteria . The results of our analysis also predicted that members of the DNR regulon include genes known to be involved in nitrate respiration , the first step in denitrification ( ID 1696 , 2903 , 3120 , 4023 and 4488 ) . Previous work indicated that NnrR , another member of the CRP/FNR super-family that is involved in NO-dependent regulation [54] , is responsible for controlling denitrification in α-proteobacteria [55] . Thus , the small size of the predicted DNR regulon members may indicate a more limited role of this regulatory network in α-proteobacteria in favor of NnrR . This is an interesting hypothesis because members of the NnrR family have a predicted DNA target sequence less similar than DNR does to FNR and FixK ( Figure 2 ) . Therefore , NnrR orthologs provide an alternative to DNR to regulate functions in response to nitric oxide and resolve potential cross talk among the different regulatory networks . Our results provide support the hypothesis that bacterial transcriptional networks are often composed of a core set of genes that is widely conserved across related species , and a larger variable gene set that is specific to a smaller number of species [12] , [55]–[59] . For example , we predicted that the core FNR regulon ( about 20 genes , Table 2 ) contains genes involved in the response to O2 deprivation , which is a conserved function for this protein across many bacteria [3] . In contrast , the predicted extended R . sphaeroides FnrL regulon ( another 48 genes , Table 1 ) mostly encodes functions involved in photosynthetic metabolism , a specialized anaerobic lifestyle for this organism . Moreover , we predicted that species closely related to R . sphaeroides and that are proposed to have a photosynthetic lifestyle , such as Jannaschia CCS1 or Dinoroseobacter shibae , do not share more than one third of the FnrL regulon with R . sphaeroides ( Figure 7 ) . Such observations suggest that , over a relatively short evolutionary time scale , the composition of the FnrL regulon changed significantly . We propose that the placement of O2-dependent and photosynthetic functions within the R . sphaeroides FnrL regulon was a result of adaptation to correlated changes in light and O2 availability that this organism encounters in nature . Support for the relationship between environmental factors and the composition of regulons is also found in the role of FixK , which controls both the symbiotic relationship between B . japonicum with soybean [8] , and functions involved in O2 utilization [20] . For this plant symbiont , it appears that O2 limitation is associated with establishment of root nodules on its host plant . Another example of adaptation to correlated changes in the environment was seen in E . coli , which has coupled its transcriptional responses to temperature and O2 fluctuations to mirror the co-variation of these two factors when the bacterium travels from the open environment to the gastrointestinal tract [61] . Furthermore , this regulatory connection was rapidly lost when E . coli was exposed to an environment where temperature and O2 varied independently [61] . Such associative learning may be a widespread mechanism that provides a selective advantage during adaptation to new environmental niches . Presented with a new set of conditions , cell survival depends on the appropriate response to environmental changes . Therefore , if any new environmental signals correlate with other signals that can already be sensed by the cell , genetic changes that link appropriate target genes to an existing regulator would give the cell a competitive advantage . Such rewiring or expansion of regulatory networks may occur more frequently than independent evolution of a sensor , regulator and promoter elements , because of the high-rate of bacterial gene transfer and recombination . The promoter elements necessary for the expansion of transcriptional networks ( i . e . binding sequences ) can be found in the conserved core regulon , which defines a compact functional unit . Indeed , the conserved core regulon often contains the sensor/regulator itself and proteins directly relevant to the primary signal sensed . Moreover , genes of the core regulon are often physically co-located on the genomes . For example , in many species of α-proteobacteria , the structural gene for FNR is found in the immediate genomic neighborhood of its target genes that encodes for the cytochrome c oxidase cbb3-type and accessory proteins . This model for the evolution of bacterial transcription regulatory networks is consistent with previous analyses [62] , [63] . Babu et al . concluded that the structure of transcriptional regulatory networks evolves faster than target genes and metabolic networks and that inhabitants of similar ecological niches are more likely to share conserved regulatory networks even if they span wide phylogenetic distances . [64] . These observations support the view that large portions of a so-called extended regulon can be determined by environmental conditions . It remains to be determined if the composition of the core and extended regulons evolve on different time scales . In summary , this work demonstrates the utility of combining computational and high-throughput experimental approaches to define the composition , function and evolution of regulatory networks . Our approach predictions the target gene composition of these networks even in cells that possess multiple DNA-binding proteins that recognize very similar DNA target sequences . Thus , we expect our approach will be useful to similar analyses of other transcriptional regulatory networks if the DNA binding sites of regulators are known or can be predicted . By studying transcriptional regulators that are critical to a low O2 or anaerobic lifestyle , we were also able to identify new physiological functions associated with these regulators . Finally , our results support a model for the evolution of transcriptional regulatory networks . In this hypothesis , the core conserved elements , comprising the transcription factor , target genes and promoter elements represent a ‘start-up kit’ containing elements available to expand the regulon according to factors encountered that are correlated in nature .
R . sphaeroides 2 . 4 . 1 strain was grown in Sistrom's succinate-based minimal medium A [65] at 30°C in 500 ml cultures . To maintain anaerobic photosynthetic conditions the cultures were bubbled with a gas mixture containing 95% N2 and 5% CO2 and illuminated at a light intensity of 10W/m2 . R . sphaeroides cells were harvested at mid-exponential growth phase ( ∼2×108 colony-forming units/ml ) to prepare samples for a ChIP-chip assay [12] . FnrL , the β′ and σ70 subunits of RNA polymerase were separately immuno-precipitated with anti-R . sphaeroides FnrL rabbit serum , anti-E . coli β′ rabbit serum , or 2G10 anti-σ70 monoclonal antibodies , respectively . Labeled DNA was hybridized on a custom-made tiling microarray , synthesized by NimbleGen ( Roche NimbleGen Inc , Madison , WI ) , covering R . sphaeroides 2 . 4 . 1 [12] . Before data analysis , dye intensity bias and array-to-array absolute intensity variations were corrected using quantile normalization across replicates ( limma package in the R environment ) [66] . The log2 of the ratio of experimental ( Cy3 ) to control signals ( Cy5 ) was calculated . The data from the biological replicates were averaged for visualization in SignalMap 1 . 9 software ( Roche NimbleGen Inc , Madison WI ) . Regions of the genome enriched for occupancy by FnrL were identified using TAMALPAIS at p≤0 . 01 for a threshold set at the 95th percentile of the log2 ratio for each chip [67] . Only regions that were significantly enriched in all three replicates were considered . The ChIP-chip data have been deposited in NCBI's Gene Expression Omnibus [68] and are accessible through GEO Series accession number GSE22027 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE22027 ) . To identify genes that show expression patterns correlated with environmental O2 levels . R . sphaeroides transcription profiling experiment datasets were collected from the Gene Expression Omnibus database ( http://www . ncbi . nlm . nih . gov/geo/ , platform number: GPL162 ) . The datasets contain gene expression levels from 44 Genechip Custom Express microarrays ( Affymetrix , Santa Clara , CA ) obtained from the wild-type 2 . 4 . 1 strain grown in a succinate-based minimal medium ( GSM1620 , GSM1671 , GSM8108 , GSM2410 , GSM2421 , GSM2422 , GSM2423 , GSM3030 , GSM3031 , GSM3032 , GSM38777 , GSM38778 , GSM38779 , GSM26242 , GSM26243 , GSM26244 , GSM25295 , GSM25296 , GSM25297 , GSM1672 , GSM1673 , GSM2425 , GSM2426 , GSM38780 , GSM38781 , GSM27348 , GSM27349 , GSM27350 , GSM2418 , GSM2419 , GSM8109 , GSM2429 , GSM2430 , 2416 , GSM2417 , GSM8107 , GSM3258 , GSM3260 , GSM3262 , GSM38774 , GSM38775 , GSM38776 , GSM3272 , GSM3273 , GSM3274 ) [14]–[16] . Expression microarray data were normalized using the RMAexpress v1 . 0 software ( http://rmaexpress . bmbolstad . com/ ) with background adjustment and quantile normalization [66] . The clustering analysis was done in the R statistical software environment ( http://www . r-project . org/ ) using the Pearson correlation coefficient as a distance between expression patterns and ‘complete’ linkage to construct the cluster hierarchy . The method adopted to determine sets of putative orthologous proteins was adapted from Li et al . [17] with some modifications . First , similarities between all translated protein coding sequences across all tested genomes were discovered using BLASTP algorithm with a cutoff at E-value ≤1e-5 [69] . Each similarity score was normalized by dividing the bit score between two sequences by the maximum of the bit score of each sequence when scored against itself ( norm_score ( x , y ) = bit_sore ( x , y ) /max ( bit_score ( x , x ) , bit_score ( y , y ) ) ) . Then , to correct for the fact that the normalized score distributions are dependent on the phylogenetic distance between organisms , all normalized similarity scores between protein sequences of two organisms were divided by the value at the 98th percentile of the distribution of these scores . Sets of related and putatively orthologous proteins were obtained using the MCL 06-058-2 algorithm with settings other than ‘inflation’ set to default [70] ( http://www . micans . org/mcl/ ) . Several values for the ‘inflation’ parameter were used to explore the hierarchy of the relationship between sets of proteins . Ultimately , the ‘inflation’ parameter was set to 3 . 0 to obtain protein sets used in the remaining analysis . The species maximum likelihood phylogeny was constructed using the aLRT-PhyML algorithm [71] , [72] ( http://atgc . lirmm . fr/phyml/ ) with default parameters and E . coli genome sequences as an out-group . The protein sequence alignment used to reconstruct the phylogeny was derived from 42 sets of orthologs that have only one member in each species . Each protein set was aligned with MUSCLE 3 . 7 [73] ( http://www . drive5 . com/muscle/ ) independently and then all the alignments were concatenated . The global alignment was filtered using GBlocks 0 . 91b [74] ( http://molevol . cmima . csic . es/castresana/Gblocks . html ) to remove divergent and poorly aligned positions . The resulting alignment consisted of 5921 positions . The common binding site model used to carry out the phylogenetic transcription factor binding-site analysis was constructed by aligning the conserved palindromic sequence found in the promoter regions of the genes coding for the FNR , FixK , and DNR orthologs across all genomes considered in this study using MEME [75] . A hidden-Markov model of the binding site motif was constructed with HMMER 2 . 3 . 2 [76] ( http://hmmer . janelia . org/ ) . The promoter regions , represented by the 300 base pair sequence upstream of the transcriptional start site , of all protein-coding sequences were scored against the model . The distribution of scores for each organism was normalized to a standard distribution to eliminate the influence of varying base composition of the background sequences across organisms . Each protein coding sequence is associated with a motif score , which is represented by its standard deviation from the mean of the score distribution . Scores ≥3 . 0 were labeled as significant . Because bacterial genes can be organized in polycistronic operons , the promoter scores of the first genes of putative operons were propagated to the rest of the genes in the operons . The score of a predicted downstream gene in the operon was calculated by taking the maximum between its own score and the score of the previous gene multiplied by the probability of the two genes being co-transcribed . The operon predictions were obtained from the VIMSS database ( http://www . microbesonline . org/operons/ ) [77] . After grouping gene products in their respective orthologous sets , the presence of significant DNA target sequences associated with each gene forms a Boolean vector across species . The similarity between the occurrence of a particular transcription factor ( A ) and the occurrence of a binding motif ( B ) was calculated using the Jaccard coefficient ( J ( A , B ) = |A∩B|/|A∪B| ) . Target genes were assigned to the transcription factor to which they shared the most similar phylogenetic profile . Target genes which profiles were not at least 20% similar to one of the three regulators were ignored . | An important property of living systems is the use of regulatory networks to appropriately program gene expression . Central to the function of regulatory networks are transcription factors that regulate gene expression by binding to specific DNA sequences . Despite the central role of these regulatory networks , the processes driving their organization and evolution across organisms are poorly understood . This paper describes the use of comparative genomics and high-throughput approaches to predict the organization and evolution of transcriptional regulatory networks across a large group of species . We focused on regulatory networks controlling cellular responses to changes in O2 levels because this signal has major consequences on many biological systems . Our analysis predicts that related regulatory networks share a core set of target genes across diverse species while other target genes vary according to the organism's specific lifestyle . Our approach of defining transcriptional regulatory networks across a wide range of organisms should be of general utility to studying similar questions in other systems . | [
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] | 2010 | Reconstruction of the Core and Extended Regulons of Global Transcription Factors |
The RNA helicase LGP2 ( Laboratory of Genetics and Physiology 2 ) is a non-signaling member of the retinoic acid-inducible gene-I ( RIG-I ) -like receptors ( RLRs ) , whose pivotal role on innate immune responses against RNA viruses is being increasingly uncovered . LGP2 is known to work in synergy with melanoma differentiation-associated gene 5 ( MDA5 ) to promote the antiviral response induced by picornavirus infection . Here , we describe the activity of the foot-and-mouth disease virus ( FMDV ) Leader protease ( Lpro ) targeting LGP2 for cleavage . When LGP2 and Lpro were co-expressed , cleavage products were observed in an Lpro dose-dependent manner while co-expression with a catalytically inactive Lpro mutant had no effect on LGP2 levels or pattern . We further show that Lpro localizes and immunoprecipitates with LGP2 in transfected cells supporting their interaction within the cytoplasm . Evidence of LGP2 proteolysis was also detected during FMDV infection . Moreover , the inhibitory effect of LGP2 overexpression on FMDV growth observed was reverted when Lpro was co-expressed , concomitant with lower levels of IFN-β mRNA and antiviral activity in those cells . The Lpro target site in LGP2 was identified as an RGRAR sequence in a conserved helicase motif whose replacement to EGEAE abrogated LGP2 cleavage by Lpro . Taken together , these data suggest that LGP2 cleavage by the Leader protease of aphthoviruses may represent a novel antagonistic mechanism for immune evasion .
Antiviral response against RNA viruses greatly relies on detection of infection by cytoplasmic sensors . Among the different pattern-recognition receptors ( PRRs ) involved in antiviral immunity , the retinoic acid-inducible gene-I ( RIG-I ) -like receptors ( RLRs ) , recognize non-self RNA species derived from viral infection triggering the downstream signaling cascade leading to type-I interferon ( IFN ) secretion and host antiviral response [1 , 2] . RLRs are ubiquitous cytosolic RNA helicases including RIG-I , melanoma differentiation-associated gene 5 ( MDA5 ) and LGP2 ( Laboratory of Genetics and Physiology 2 ) . All three RLRs share a DExD/H box RNA helicase domain and a C-terminal domain ( CTD ) . The helicase domain and the CTD bind to viral RNA , CTD being essential for the specific recognition of RNA substrate features . The helicase domain generally functions to coordinate RNA binding , ATP hydrolysis , and conformational rearrangements upon RNA recognition [2 , 3] . The RLRs share the ability to detect molecular signatures of virus infection , but differ in both their RNA recognition specificity and signaling properties . RIG-I senses primarily 5´-triphosphate blunt-end dsRNA , while MDA5 is activated by long dsRNA , consequently responding to different but overlapping sets of viruses [4 , 5] . LGP2 has the highest RNA binding affinity of the RLRs , and has the ability to recognize diverse dsRNAs , regardless of the presence of 5´-triphosphate or RNA length [6] . RIG-I and MDA5 contain N-terminal tandem caspase activation and recruitment domains ( CARDs ) which upon recognition of viral RNA , interact with the CARD of the mitochondrial activator of virus signaling ( MAVS ) protein , the essential adaptor molecule for RLR signaling . LGP2 lacks the N-terminal CARDs and then independent signaling activity . However , LGP2 is known to be widely involved in viral RNA recognition and regulation during innate immune responses , remaining the most enigmatic member of the RLR family [7] . Both negative and positive regulatory roles have been reported for LGP2 in antiviral immunity . An enhancing effect on MDA5-mediated signaling was found when LGP2 was present at low cellular concentrations . According to a model based on a concentration dependent biphasic switch , at early stages of infection low levels of LGP2 would enhance MDA5-mediated antiviral signaling , but as infection progresses and LGP2 production is induced by IFN , LGP2 would act as a negative feedback regulator inhibiting MDA5 signaling [7–9] . Single molecule RNA binding experiments and biochemical analysis revealed that ATP hydrolysis activity is required to enable LGP2 to efficiently engage diverse dsRNA species , and for enhancement of MDA5 signaling [8] . An RNA- and virus-independent inhibitory role for LGP2 in antiviral signaling has also been reported , likely involving CARD-independent interaction with MAVS by competition with an essential kinase for binding and interfering with downstream signaling [10] . Foot-and-mouth disease virus ( FMDV ) is the etiologic agent of a highly infectious vesicular disease affecting swine , cattle and other domestic and wild cloven-hoofed animals worldwide [11 , 12] . FMDV is included in the Aphthovirus genus of the Picornaviridae family . Picornaviruses are small non-enveloped viruses and their capsids enclose a single-stranded RNA genome coding for a polyprotein which is subsequently cleaved by viral proteases to yield the different viral proteins . MDA5 is involved in recognizing the dsRNA synthesized during picornavirus replication [13] and experimental evidence using lentivirus-driven RNA interference supports that FMDV is sensed by MDA5 in porcine epithelial cells [14] . During co-evolution with their hosts viruses have acquired strategies to actively counteract host antiviral responses [15–17] and the balance between innate response and viral antagonism may determine the outcome of disease and pathogenesis . A repertoire of mechanisms aimed at confronting the host IFN response has been described for FMDV , most of them involving the proteolytic activity of the two virally encoded Leader and 3C proteases [18 , 19] . The FMDV Leader protease ( Lpro ) is the first protein encoded in the ORF , a papain-like cysteine protease which is present as two different forms , Lab and Lb , generated by translation initiation at two in-frame AUG codons separated 84 nt on the viral RNA [20] and subsequent intramolecular self-processing . Both forms of Lpro are active but Lbpro is more efficiently translated and abundant in infected cells [21] . FMDV Lpro impairs cap-dependent translation through cleavage of initiation factor eIF4G , leading to a translational host shut-off [22 , 23] and plays an important role in viral pathogenesis . Several cellular proteins have been identified as Lpro targets [24] and Lpro activity is known to disrupt signaling pathways involved in host defenses , like degradation of the p65 subunit of NF-κB and suppression of IFN-β and inflammatory chemokines by reduction of IRF-3/7 expression [25 , 26] . The deubiquitinase activity of Lpro is also known to cleave ubiquitin moieties from critical signaling proteins of the type-I IFN signaling pathway , such as RIG-I , TBK1 , TRAF3 , and TRAF6 [27] . A few reports have identified LGP2 as a potential target for viral antagonism . The paramyxovirus V protein binds to the helicase domains of both MDA5 and LGP2 disrupting their enzymatic activity [28] . A recent work describes the interaction between the Nonstructural Protein 3 ( NS3 ) encoded by the hepatitis C virus ( HCV ) and the helicase domain of LGP2 by quantitative micro-spectroscopic imaging ( Q-MSI ) [29] . Overexpression of LGP2 has been shown to reduce FMDV growth and interaction of LGP2 with non-structural protein 2B has been detected by immunoprecipitation experiments [30] . Here , we show that FMDV Lpro targets LGP2 helicase for cleavage , resulting in lower levels of IFN-β and antiviral activity in co-transfected cells . No evidence of proteolysis could be detected with a catalytically inactive version of Lpro . The Lpro target sequence in LGP2 was identified as an RGRAR motif which is part of the conserved helicase motif VI of LGP2 . Direct interaction between both proteins was evidenced by immunoprecipitation and co-localization assays . LGP2 processing was also detected during FMDV infection , suggesting that LGP2 cleavage by the Leader protease may be a mechanism developed by aphthoviruses to counteract the host immune response . This is the first report of LGP2 proteolytic cleavage exerted by a viral protease and unveils a novel role for the FMDV leader protease on immune evasion .
The FMDV-encoded Leader protease is an important virulence factor involved in IFN antagonism . Given that LGP2 is an innate immunity effector with synergistic effect on MDA5-induced antiviral response , we sought to determine whether FMDV is targeting LGP2 by a mechanism involving the activity of Lpro . First , we studied the effect of the co-expression on HEK293 cells of ( Myc-DDK-tagged ) -human LGP2 together with either the wildtype catalytically active form of Lbpro ( LbWT ) or LbC51A , an inactive form of the protease carrying a mutation in the active site [31 , 32] . The levels and integrity of LGP2 were analyzed 24 h later by immunoblot using antibodies against the N- or C-terminal regions of human LGP2 , and compared to those observed after co-transfecting with the empty vector ( EV ) ( Fig 1A ) . Expression of LbWT induced a drastic decrease in the full-length LGP2 levels . Interestingly , two LGP2-derived products of approximately 49 KDa and 27 KDa were specifically detected with the antibodies against the N- and C-terminal regions of LGP2 , respectively . In contrast , when LGP2 and LbC51A were expressed together , no decrease in the helicase levels or additional bands were observed , suggesting that the LGP2 fragments detected may result from specific proteolytic cleavage by Lbpro . Cleavage of eIF4G , a known cellular target protein for Lbpro was analyzed in HEK293 cells expressing the protease as a control of its catalytic activity in the experimental conditions used ( Fig 1B ) . The 110 KDa cleavage fragment of eIF4G [33] was readily detected in cells expressing LbWT , like in cells infected with FMDV , in contrast to those expressing LbC51A ( Fig 1B ) . The impact on the cap-dependent expression of a control DDK-tagged protein during co-expression with Lbpro due to eIF4G cleavage is shown for comparison ( Fig 1C ) . In sum , these results suggest that LGP2 is a target for the proteolytic activity of the Leader protease . Next , we further characterized the Lbpro-LGP2 interaction . When lysates from cells co-expressing LGP2 and Lbpro were analyzed at different times after transfection , a progressive degradation of full-length LGP2 , concomitant with detection of the N- and C-terminal products , could be observed ( Fig 2A ) . The 27 KDa C-terminal fragment was also clearly detected with the anti-DDK antibody , consistent with the C-terminal location of the DDK tag in the LGP2 fusion protein transiently expressed . A dose-dependent effect of Lbpro on LGP2 was also observed , with accumulation of the N- and C-terminal products as higher concentrations of the protease were co-expressed with a fixed amount of the helicase ( Fig 2B ) . With the highest amount of Lbpro assayed , the level of detection of all LGP2-derived bands 24 h after transfection decreased drastically , likely due to the extensive processing of the protein by Lb and subsequent degradation of the resulting products . The integrity of eIF4G in the lysates corresponding to the time course and Lbpro dose experiments was also analyzed to monitor the activityof Lbpro in each case ( S1A and S1B Fig ) . To address whether the caspase or the proteasome pathways were involved in LGP2 cleavage , the caspase inhibitor zVAD-FMK or the proteasome inhibitor MG132 was added to the transfection medium during LGP2 expression assays . As shown in Fig 2C , induction of apoptosis or proteasome did not result in LGP2 cleavage . In contrast , eIF4G analysis revealed the presence of the expected caspase-dependent fragments [34] ( S1C Fig ) . Additionally , the 49 KDa N-terminal and 27 KDa C-terminal fragments were generated when LGP2 and Lbpro were co-expressed in the presence of the inhibitors . These results suggest that LGP2 cleavage was specifically attributable to the protease activity of the Lb protein and not a result of activation of cellular apoptosis and proteasome . Given that pigs are among the most relevant natural host species for FMDV , we next assessed the ability of Lbpro to process porcine LGP2 . For this purpose , we expressed the porcine helicase fused to an N-terminal DDK tag , as we failed in our attempts to detect the endogenous LGP2 . Amino acid sequence alignment showed an 82% identity between human and porcine LGP2 proteins . Similarly to human LGP2 , we found evidence of porcine LGP2 cleavage when it was co-expressed with the catalytically active form of Lbpro ( Fig 2D and 2E ) . At 24 h after transfection , the full length porcine LGP2 was hardly detectable and no effect could be observed co-expressing the inactive form of the protease LbC51A ( Fig 2D ) . Consistently , an N-terminal fragment of similar size to that generated from the human protein was readily detected with the antibody against the N-terminal region of LGP2 or the anti-tag antibody . The N-terminal LGP2 cleavage product generated by the activity of Lbpro accumulated over time after transfection ( Fig 2E ) . The N-terminal fragment of porcine LGP2 showed a slightly slower migration than that derived from the human helicase ( 50 KDa approximately ) , consistent with the presence of the N-terminal DDK tag ( Fig 2F ) . Interestingly , no C-terminal products were found when using the specific antibody against the LGP2 C-terminal region in lysates from cells co-expressing the porcine helicase and LbWT ( Fig 2D and 2E ) . To further address that issue and rule out any interference with the cross-reactivity of the antibody , raised against the C-terminal region of the human LGP2 , we made a new construct for the expression of porcine LGP2 fused to a C-terminal Myc tag . Using an anti-Myc antibody we were unable to detect any LGP2-derived product around 27 KDa when porcine LGP2 and Lbpro were co-expressed , unlike that generated from human LGP2 , and only a very faint product of approximately 18 KDa could be detected ( Fig 2G ) . The cleavage pattern of porcine LGP2 was further confirmed in porcine SK6 cells ( Fig 2H ) . The difference in the LGP2 C-terminal patterns observed between the human and porcine helicases induced by Lbpro might be the result of a more efficient degradation of the cleavage product generated from the porcine protein . Indeed , smaller degradation products can also be observed as the N-terminal fragments from both human and porcine LGP2 accumulate in transfected cells ( Fig 2C , 2F and 2G ) . Additionally , secondary cleavage sites for Lbpro might be present in the C-terminal region of porcine LGP2 . Taken together , these results show that the FMDV Lbpro specifically cleaves human as well as porcine LGP2 when both helicase and protease are co-expressed in either human HEK293 or porcine SK6 cells . Having established that LGP2 is a target for the catalytic activity of Lbpro , we sought to determine whether Lbpro interacts with LGP2 . First , we carried out co-immunoprecipitation ( coIP ) assays in porcine SK6 cells co-expressing both proteins ( Fig 3A ) . As expected , both full-length LGP2 and its N-terminal fragment were efficiently pulled down by the anti-tag antibody . Two different concentrations were used for SDS-PAGE analysis in order to separate the approximately 49 KDa LGP2 fragment from the 50 KDa IgG heavy chain band . We found that both LbWT and the inactive LbC51A mutant co-immunoprecipitated with LGP2 , while no Lb was detected when co-expressed with the control tagged vector . According to the intensity of the LbWT and LbC51A bands in the corresponding IP fractions , it seems that both Lb forms are able to bind to full-length LGP2 . As the amount of intact LGP2 24 h after co-transfection with LbWT is scarce , the low amount of protease immunoprecipitated with LGP2 detected as a faint band ( Fig 3A ) . In contrast , LbC51A is accumulated in transfected cells and its interaction with LGP2 was readily detected . Additionally , the interaction between Lb and LGP2 might be abolished after cleavage contributing to a better detection of the LbC51A-LGP2 interaction . We also found by confocal microscopy that both LbWT as well as LbC51A co-localized with LGP2 when transiently co-expressed in BHK21 cells ( Fig 3B ) . Taken together , these results suggest that the FMDV Lpro and LGP2 physically interact in vivo . Having shown that Lbpro interacts with and cleaves LGP2 , we hypothesized that the helicase cleavage event could play a role on viral host immune evasion . First , we determined whether FMDV infection induced LGP2 cleavage . For that purpose , human or porcine LGP2 was expressed in swine SK6 cells that were then infected with FMDV and lysed at different times after infection . Viruses in the supernatants collected from transfected and infected cells were titrated at the corresponding time points ( Fig 4A and 4B ) . In these assays , two serologically and genetically divergent FMDV isolates were used: type-O O1BFS and type-C CS8 . When SK6 cells expressing human LGP2 were infected with FMDV , the N- and C-terminal LGP2 cleavage products were clearly detected at 2 or 4 h post-infection ( hpi ) for CS8 or O1BFS isolates , respectively and up to 8 hpi ( Fig 4A ) . When porcine LGP2 was expressed , FMDV infection with O1BFS or CS8 isolates generated the LGP2 N-terminal product of about 50 KDa which could be detected between 4–8 hpi using antibodies against either the N-terminal region of LGP2 or the DDK-tag ( Fig 4B ) . Similarly to assays using ectopically expressed Lbpro , no C-terminal products derived from porcine LGP2 could be detected in human or swine cells . In all cases , detection of the human or porcine LGP2 cleavage products correlated with accumulation of the FMDV-encoded Lpro which could be often detected as a doublet , including Lb and a slower migrating form corresponding to Lab ( Fig 4A and 4B ) . Also , LGP2 cleavage products detection coincided with times of higher viral titers ( Fig 4A and 4B ) . These results show that LGP2 cleavage occurs during FMDV infection and the cleavage patterns observed are equivalent to those found in the above experiments using transiently expressed Lbpro ( Fig 2 ) . The impact of FMDV infection on eIF4G as result of Lpro activity on a known cellular target was monitored over time in SK6 cells transfected with human or porcine LGP2 ( S2A and S2B Fig , respectively ) . While eIF4G cleavage was complete at 8 hpi ( S2 Fig ) , full-length LGP2 was still abundant in cells ( Fig 4A and 4B ) , likely due to a lower affinity for LGP2 together with the excess of overexpressed protein within cells at the time of infection . Next , the pattern of LGP2 was analyzed at different times after infection with another aphthovirus , equine rhinitis A virus ( ERAV ) . A drastic decrease in full-length LGP2 was observed after 24 h of infection and we were able to detect the 27 KDa C-terminal cleavage product at 48 hpi ( S3 Fig ) . In contrast , during infection with different swine viruses causing a clinical disease similar to FMDV , like swine vesicular disease virus ( SVDV ) —a picornavirus - , or vesicular stomatitis virus ( VSV ) —a member of the Rhabdoviridae family , no cleavage products were detected and the levels of full-length LGP2 were maintained with no obvious decrease associated with infection ( S4A and S4B Fig ) . Similar results were found when infection by two other distantly related picornaviruses—Aichivirus ( Aiv ) or encephalomyocarditis virus ( EMCV ) —was analyzed for LGP2 cleavage ( S4C and S4D Fig ) . Again , no decrease in full-length LGP2 levels or any cleavage products could be detected . Interestingly , with the exception of ERAV , none of the picornaviruses analyzed express an active Leader protease . Altogether , these results suggest that LGP2 cleavage is not a general event during the course of infection by picornaviruses or vesicular swine viruses , but a specific mechanism occurring during FMDV infection and likely shared among aphthoviruses . It has been shown that LGP2 overexpression negatively affects FMDV replication in cultured cells [30] . To determine whether LGP2 cleavage by Lpro is involved in IFN antagonism operating during FMDV infection , the effect of LGP2 and Lpro co-expression on the resulting viral titers , IFN-β mRNA levels and antiviral activity induced was analyzed in swine SK6 cells ( Fig 5 ) . First , the viral titers after 8 h of infection in cells co-expressing porcine LGP2 and either LbWT or inactive mutant LbC51A were compared ( Fig 5A ) . As expected , expression of LGP2 induced a significant reduction in viral titers . Interestingly , co-expression of LbWT restored the viral titers recovered from control cells and no significant differences were found between cells co-expressing LGP2 and LbWT and those transfected with the EV alone or with LbWT or LbC51A independently . However , co-expression of LGP2 and LbC51A failed to have a stimulatory effect on FMDV replication and viral titers were equivalent to those obtained when LGP2 alone was expressed . When the integrity of LGP2 was analyzed , the N-terminal cleavage fragment could be detected in cells co-transfected with EV or LbC51A ( Fig 5A ) , consistent with the cleavage pattern observed during infection ( Fig 4 ) . In contrast , no full-length LGP2 could be detected in cells co-expressing LbWT , suggesting an additive cleavage effect of overexpressed LbWT and FMDV-encoded Lpro on LGP2 , though a putative contribution of the 3Cpro activity has not been analyzed and cannot be ruled out . In all cases , complete cleavage of eIF4G was observed , as expected at 8 h after infection ( Fig 5A ) . Since the Lpro activity is able to subvert the inhibitory effect mediated by LGP2 expression , ultimately promoting viral growth , we sought to address whether the mechanism behind that effect was related to type-I IFN induction . For that , the mRNA levels of porcine IFN-β were analyzed by RT-qPCR in SK6 cells transfected and infected as above ( Fig 5B ) . Consistent with the different viral titers recovered from cells co-expressing porcine LGP2 and either LbWT or LbC51A , the IFN-β mRNA levels in cells co-transfected with LGP2 and LbWT were significantly lower than those measured in cells co-expressing LGP2 and either inactive LbC51A or an empty vector ( 100- and 128-fold lower , respectively ) ( Fig 5B ) . We also observed that lower levels of IFN-β mRNA were induced when LbC51A and LGP2 were co-expressed compared to cells co-expressing LGP2 and an EV . This could be due to interference by the inactive LbC51A , that is still able to bind LGP2 , with the antiviral response triggered by the helicase . Additionally , a residual protease activity of the LbC51A , expressed at high levels in transfected cells , might contribute to the IFN reduction observed . In any case , this difference only seemed to induce a small insignificant reduction in viral titers . Altogether , we concluded that , when LGP2 is transiently overexpressed , co-expression of catalytically active Lpro was associated with lower levels of IFN-β induction and higher levels of FMDV replication , in correlation also with complete cleavage of the helicase . Next , we aimed to determine whether the differences in IFN-β mRNA induction and FMDV titers described above correlated with different levels of antiviral activity present in the supernatants of the corresponding cells . Then , we carried out an IFN bioassay based on VSV infection inhibition in cells pre-treated with the supernatants from SK6 cells transfected and infected as above . The antiviral activity in each case reflects the protein levels of type-I IFN effectively secreted after mRNA induction and biologically active against viral infection . As shown in Fig 5C , antiviral activity was detected and measured in supernatants from cells co-transfected with LGP2 and either the EV or LbC51A but not with LbWT . This is consistent with the low levels of IFN-β mRNA measured by RT-qPCR and the higher FMDV titers recovered from those cells ( Fig 5A and 5B ) . No antiviral activity could be detected in mock-transfected/infected or non-infected control cells either . The antiviral activity found in cells expressing LGP2 alone or together with inactive LbC51A was completely neutralized by incubation of the supernatants with a monoclonal antibody against porcine IFN-α , while no inhibitory effect on VSV infection was observed in untreated cells , proving the specificity of the neutralizations observed and further confirming that the antiviral activity subverted by Lbpro was indeed type-I IFN specific . Though several cellular proteins are known targets for Lpro cleavage , only a few substrate sequences which , however , do not share a unique amino acid sequence motif , have been identified experimentally . Given that the estimated molecular weights of the N- and C-terminal fragments generated after Lbpro cleavage of human LGP2 seem to add up to the size of the full-length protein ( 77 KDa ) , suggesting a single cleavage site , and the similar size observed for the N-terminal fragment cleaved from the porcine protein ( about 50 KDa ) , the amino acid sequence around the putative cleavage region was analyzed for similarities with previously reported Lpro target sequences . A stretch of positively charged R amino acids ( RGRAR ) resembling the ( R ) ( R/K ) ( L/A ) ( R ) target motif defined for Gemin5 and Daxx ( death-domain associated protein ) proteins [35] was identified in the conserved helicase motif VI of both human and porcine LGP2 sequences ( Fig 6A ) . To determine the relevance of the arginine residues in the candidate target sequence , a triple substitution mutant to negatively charged glutamic acid ( RGRAR/EGEAE ) was generated in the human protein ( Fig 6A ) . Unlike LGP2WT , when the LGP2 triple mutant ( LGP2MT ) was co-transfected with Lbpro no cleavage products could be detected , though the expected decrease in the cap-dependent expression of the tagged-polypeptide , concomitant with Lpro expression was evident ( Fig 6B ) . These results suggest that residues 69–73 in human LGP2 ( corresponding to amino acids 72–76 in the porcine protein ) are a target motif for Lpro proteolytic activity .
In this study , we identified the innate immune sensor LGP2 as a target for the FMDV Leader protease . The IFN system is a powerful component of the antiviral response and viruses have evolved sophisticated strategies to evade the host innate immune response by interfering with the different events involved in PRR activation and signaling [15 , 16] . FMDV is no exception , and viral proteases have been found to counteract the innate responses induced in cells during the course of infection [17 , 18] . Lpro is known to prevent the host antiviral response by several mechanisms including cleavage of initiation factor eIF4G - and then prevention of the synthesis of IFN and other cytokines immediately after infection- , degradation of NF-κB , and deubiquitination of immune signaling molecules [18 , 24] . Though the contribution of LGP2 to innate immune activation is still not fully understood , recent work unveils a relevant regulatory role on RLR signaling through CARD-independent interactions . The dsRNA generated during picornavirus replication is sensed by MDA5 , and LGP2 is believed to promote the viral RNA-MDA5 interaction leading to efficient antiviral signaling [36] . Indeed , RNA derived from EMCV infection with strong MDA5-stimulatory activity was immunoprecipitated with LGP2 [37] . It is also known that either LGP2 or MDA5 deficiency results in higher susceptibility to picornavirus infections [38 , 39] . A recent report shows that , in the absence of infection or viral proteins , LGP2 functioned as a biphasic master activator of numerous innate immunity genes , sequentially induced in a cascade fashion leading to production of IFN . In turn , LGP2 was subject to negative control by cellular translation regulators [40] . Here , we first provide evidence that LGP2 is cleaved by the FMDV Lbpro resulting in a drastic decrease of full-length LGP2 and accumulation of specific cleavage products in an Lb-dose-dependent manner . Catalytically inactive mutant LbC51A had no effect on LGP2 . We found that LGP2 cleavage was specifically attributable to Lbpro catalytic activity and not a result of activation of cellular apoptosis or proteasome . When the patterns of human and porcine LGP2 after co-expression with Lbpro were compared , a similar N-terminal fragment of about 50 KDa was observed in both cases , while an additional C-terminal fragment of 27 KDa was only detected for human LGP2 . Though several cellular proteins are known targets for Lpro cleavage , only a few substrate sequences have been identified experimentally and there is no consensus for Lpro target sequence . Together with the L/VP4 junction of the viral polyprotein , cleavage sites in eIF4GI , eIF4GII , Gemin5 and Daxx have been determined . The analysis of the amino acid sequence around the putative cleavage region revealed a conserved motif in human and porcine LGP2 proteins resembling the Lpro target site ( R ) ( R/K ) ( L/A ) ( R ) reported in Gemin5 and Daxx [35] . Replacement of all three positively charged R residues by E ( RGAR/EGEAE ) in human LGP2 protein completely abolished cleavage by Lbpro , defining the RGRAR sequence in the conserved helicase motif VI as the FMDV Leader protease target site in LGP2 . This result further increases the number of host factors cleaved by this protease , opening new avenues for the identification of novel targets . Cleavage at that position would excise a 27 KDa C-terminal fragment , in agreement with our results , involving removal of part of the helicase domain and the complete CTD region . An intact CTD is required for RNA specific recognition , and LGP2 mutants in the CTD , helicase domain or both are known to be RNA binding-deficient and have poor enhancing activity towards MDA5 [7] . Thus , cleavage by Lpro would likely abolish the antiviral function of LGP2 . Additionally , we found that both active LbWT and inactive LbC51A were able to interact with LGP2 , though LbC51A co-immunoprecipitated with the helicase more efficiently than LbWT . Besides the higher levels of expression achieved with the inactive version of the protease , these results suggest that Lbpro forms a transient interaction with LGP2 that is abolished after LGP2 cleavage . This is also consistent with the low levels of full-length LGP2 and high levels of the N-terminal fragment present in the lysates when LbWT was expressed . Given that LGP2 cleavage by Lpro was found using the ectopically expressed protease , we analyzed the fate of overexpressed LGP2 during FMDV infection in order to address the biological relevance of the cleavage event . Interestingly , the human and porcine helicase patterns observed during FMDV infection with two different viral isolates overlapped with those observed under LbWT overexpression . Consistently , the corresponding N- and C-terminal LGP2 cleavage products accumulated in cells around 4 h after infection , coinciding with accumulation of viral Lpro , and thus supporting that LGP2 is processed by Lpro during FMDV infection . Evidence of LGP2 cleavage was also found during infection with the equine aphthovirus ERAV , which shares with FMDV , unlike most picornaviruses , the presence of a proteolytically active Leader protein at the N-terminus of the polyprotein [41] . In contrast , no evidence of LGP2 cleavage or noticeable decrease was observed during infection with a set of different viruses , including unrelated picornaviruses AiV and EMCV , and other RNA viruses causing swine vesicular disease similar to FMD like SVDV—picornavirus—and VSV—rhabdovirus , suggesting that no evident specific mechanisms targeting LGP2 integrity were exerted by these other viruses . In agreement with these data , Feng et al . could not find any sign of LGP2 cleavage in HeLa cells during infection with Coxsackievirus B3 , a subtype of Enterovirus B , another picornavirus [42] . Interestingly , Gemin5 cleavage by Lpro was only observed in FMDV-infected cells but not during infection with picornaviruses belonging to different genera like SVDV or EMCV [35] . A previous study showed a detrimental effect of LGP2 expression on FMDV replication , as well as a decrease in the helicase levels when different viral proteins—including Lpro , 3C and 2B - were expressed [30] . The authors concluded that 2B interaction with LGP2 was responsible for this effect and linked it to regulation of the inflammatory response in infected cells by an unknown mechanism . In this study , we showed that LGP2 cleavage by Lpro is involved in IFN antagonism operating during FMDV infection . Expression of catalytically active Lpro was able to subvert the IFN-β induction and inhibitory effect on viral growth mediated by LGP2 , circumventing the type-I IFN specific antiviral activity induced in porcine cells that had been transfected and later infected with FMDV . A potential role on LGP2 antagonism has been suggested for the binding of paramyxovirus V and HCV NS3proteins to the helicase domain of LGP2 . LGP2-V protein interaction disrupts the ATP hydrolysis activity of LGP2 [28] . The HCV NS3 protein has a protease domain at its N-terminus linked to a C-terminal helicase domain . LGP2-NS3 interaction might contribute to localize NS3 to mitochondria for MAVS cleavage [29] . To our knowledge , this is the first report of an LGP2 cleavage event involving a virally encoded protein , with implications in the resulting type-I IFN response of the host against viral infection . FMDV is highly sensitive to IFN , and IFN-based strategies have proved to be efficient biotherapeutic approaches against the virus [43–45] . Cleavage of LGP2 by the Leader protease unveils a new antagonistic mechanism evolved by FMDV , and likely other aphthoviruses , directed to suppress the host IFN response . LGP2 cleavage expands the list of cellular proteins involved in immune response targeted by the FMDV Lpro , highlighting its relevance as a crucial proteolytic virulence factor . The suppressor effect exerted by Lpro on the LGP2-dependent type-I IFN induction may be the result of blockade at several points of the pleiotropic activation of innate responses orchestrated by LGP2 , included its synergistic effect on MDA5 signaling . Our findings encourage further studies focused on the role of LGP2 on the antiviral response against FMDV and the putative involvement of MDA5 in the LGP2-Lpro interplay . A better understanding of the mechanisms employed by viruses to circumvent the host antiviral signaling will contribute to development of new therapeutic strategies to fight viral infections , including antiviral approaches and novel vaccines . This is of particular relevance for FMDV , given the rapid spread of the virus and the devastating economic consequences associated with FMD outbreaks .
HEK293 , Vero and BHK21 cells ( all three from ATTC ) and SK6 and IBRS-2 cells ( both obtained from Centro de Investigación en Sanidad Animal , CISA-INIA , Madrid , Spain ) were all cultured in Dulbecco’s modified Eagle’s medium ( DMEM; GIBCO ) supplemented with 10% fetal bovine serum at 37 oC with 5% CO2 . These cell lines were used for propagation and infection assays of the corresponding viruses . FMDV type-C CS8 and type-O O1BFS isolates were propagated in swine SK6 or IBRS-2 cells . ERAV and Aichivirus were propagated in Vero cells . SVDV was propagated in SK6 cells . VSV was propagated in IBRS-2 cells . Plasmids encoding the WT or C51A mutant Lb protease were generated by PCR amplification of the corresponding regions from an FMDV O1K full-length cDNA clone [46] and insertion into the BamHI and XbaI sites of pcDNA3 . 1 ( + ) ( Invitrogen ) . Plasmids encoding the sequence of porcine LGP2 with a C-terminal Myc tag and/or an N-terminal DDK tag were generated by gene synthesis ( NZYTech ) and cloning into the NheI and XbaI sites of pcDNA3 . 1 ( + ) ( Invitrogen ) . Plasmid encoding ( C-terminal Myc-DDK-tagged ) -human LGP2 was from Origen . Plasmid pcDNA3/Flag-METTL3 encoding human methyltransferase-like 3 was from Addgene ( # 53739 ) . For transfection , 2 μg of LGP2-encoding plasmids and 1 μg of plasmids encoding FMDV proteases were used using Lipofectamine 2000 ( Invitrogen ) following the manufacturer's recommendations . The total amount of transfected DNA was balanced to 3 μg with empty vector . In some experiments , the transfection medium was supplemented with 20 μM Puromycin ( apoptosis inducer , Sigma-Aldrich ) , 20 μM zVAD-FMK ( broad caspase inhibitor , Promega ) or 10 μM MG132 ( proteasome inhibitor , Cayman Chemical ) . Mouse monoclonal anti-LGP2 ( E-1 , raised against a peptide mapping at the C-terminus of human LGP2 ) and goat polyclonal anti-LGP2 ( N-14 , raised against a peptide mapping near the N-terminus of human LGP2 ) were purchased from Santa Cruz Biotechnology Inc . Mouse monoclonal anti-FLAG ( M2 ) was purchased from Sigma-Aldrich . Rabbit polyclonal anti-PARP and mouse monoclonal anti-cleaved PARP ( Asp214 ) ( 19F4 ) were purchased from Cell Signaling Technology . Mouse monoclonal anti-Pig IFN-Alpha ( K9 ) was purchased from PBL Assay Science . Rabbit polyclonal anti-FMDV Leader protease was raised against the Lab/Lb fusion protein expressed by pE16 plasmid [47] and kindly provided by Ewald Beck . Rabbit polyclonal anti-βII-tubulin [48] was achieved from Sobrino F Lab . Mouse monoclonal anti-G3BP ( clone 23 ) was purchased from BD Biosciences . Goat polyclonal anti-eIF4G ( D-20 ) antibody was purchased from Santa Cruz Biotechnology Inc . Goat anti-mouse , goat anti-rabbit and rabbit anti-goat IgG ( H + L ) secondary antibodies HRP conjugate were purchased from Thermo Scientific . Cells were transfected with indicated plasmids with Lipofectamine 2000 ( Invitrogen ) according to the manufacture’s protocol and 24 h later , cells were infected with the corresponding viruses . At different times after infection , supernatants were harvested , serially diluted and viral titers were determined by plaque assay on fresh monolayers . After 1 h of infection , cells were washed twice and overlaid with 0 . 5% agar . After 24 h , cells were fixed with 10% formalin and stained with crystal violet . Viral titers were expressed as plaque forming unit ( pfu ) /ml . The mean values and standard deviations were calculated from triplicate determinations . Cells were harvested after transfection or infection , and lysed with PBS containing 1% NP-40 , 1 mM DTT and protease inhibitor cocktail ( Complete , Roche ) . Whole cell lysates were incubated at room temperature for 5 min and cleared by centrifugation at 9 . 300 x g for 5 min at 4°C . Protein concentrations were determined based on the Bradford method using the Bio-Rad protein assay kit . Equal amounts of proteins ( 20–50 μg ) were separated by 6–12% SDS-PAGE and electrophoretically transferred onto a nitrocellulose membrane ( GE Healthcare ) . After blocking with 3% non-fat milk in 0 . 05% Tween20 PBS , the membranes were incubated with the primary antibodies , followed by horseradish peroxidase-conjugated goat anti-rabbit , anti-mouse or rabbit anti-goat IgG . Membrane bound antibodies were detected by enhanced chemiluminescent luminol substrate ( Western Lightning Plus Chemiluminescent Substrate kit , Perkin Elmer ) and visualized by exposure to X-ray films . 1x106 SK6 cells were co-transfected with 2 μg of DDK-poLGP2 or DDK-vector plasmids together with 1 μg of plasmids encoding LbWT or LbC51A . Cells were harvested 24 h later and lysed with 100 μl of lysis buffer ( 50 mMTris-HCl [pH , 7 . 5] , 150 mMNaCl , 0 . 5% NP-40 , and protease inhibitor cocktail ) . The supernatants were collected by centrifugation at 10 , 000 x g for 5 min at 4°C and precleared with 25 μl of protein G-Agarose ( Roche ) for 1 h at 4°C with rotation . Proteins were immunoprecipitated by addition of monoclonal anti DDK and incubation for 4 h at 4°C and then , addition of protein A agarose and incubation at 4°C for 16 h . Immunoprecipitated complexes were washed three times with 400 μl of wash buffer 1 ( 0 . 1% NP-40 , 50 mM Tris pH 7 . 5 , 150 mM NaCl ) and once with 400 μl of wash buffer 2 ( 50 mM Tris pH 7 . 5 , 150 mM NaCl ) . Then , beads were collected via centrifugation at 10 , 000 x g for 2 min at 4°C , boiled at 100°C for 3 min in SDS protein-loading buffer and analyzed via WB . BHK-21 cells were transfected with indicated plasmids with Lipofectamine 2000 ( Invitrogen ) according to the manufacture’s protocol . After 20 h , cells were washed three times with room temperature PBS , then fixed with 4% paraformaldehyde solution in PBS for 20 min , washed again with PBS three times and permeabilized with 0 . 05% Tween in PBS for 15 min . After wash three times with PBS , cells were blocked with 5% BSA in PBS for 1 h . Cells then were incubated with specific primary antibodies overnight at 4°C , followed by incubation for 1h with goat anti-mouse Alexa fluor 488 and goat anti-rabbit Alexa fluor 647 as secondary antibody . Nuclei were stained with 4' , 6-diamidino-2-phenylindole ( DAPI ) at 1 μg/ml . Images were acquired with a Zeiss LSM 880 Meta confocal microscope ( Carl Zeiss Microimaging , Thornwood , NY ) with a Plan Apochromatic ×40/1 . 4 oil objective lens . Image processing and analysis of intensity of fluorescence by histograms were carried out using Fiji/ImageJ software . Total RNA was isolated from SK6 cells using TriReagent ( Sigma ) , quantified by spectrometry and DNase-treated with Turbo DNA-free kit ( Ambion ) . 500 ng of RNA was used for RT with 20U of SuperScript III RT ( Invitrogen ) at 55 oC for 30min . Quantitative PCR was carried out using aliquots of the RT reactions ( 1/10 ) and LightCycler FastStart DNA master SYBR green I ( Roche ) . All reactions were conducted in triplicate . Data were analyzed using the ΔΔCT method . IFN-β gene expression was normalized to that of the GAPDH and was expressed as the fold increase above the level of mock-transfected cells . Primers for amplification of IFN-β and GAPDH have been previously described [49] . The antiviral activity in supernatants from transfected and/or infected SK-6 cells was determined by a VSV infection inhibition assay on IBRS-2 cells ( IFN bioassay ) as described [49] . Briefly , after transfection , SK-6 cells were incubated at 37°C and 24 h later infected with FMDV CS8 isolate at an MOI of 5 . Supernatants were collected 7 h later and infectious particles were inactivated by acidic treatment ( pH = 2–3 ) with 10M HCl for 16–20 h at 4°C and then , neutralized ( pH = 7 ) with 10 M NaOH . Dilutions of the treated supernatants ( up to 1/15 ) were added on fresh IBRS2 monolayers and incubated for 24 h at 37°C . Then , cells were washed and infected with VSV ( 50–60 pfu per 1x106 cells ) and plaques were counted 24 h after infection . Antiviral activity was defined as the reciprocal of the highest dilution resulting in a 50% reduction in the number of plaques relative to untreated cells . In order to block the antiviral activity exerted by IFN-α in SK6 cells supernatants on VSV infection , some samples were incubated for 1 h at 37°C with 1μg of a monoclonal antibody against swine IFN-α ( clone K9 ) from PBL Assay Science . The unpaired Student’s t test for independent samples was used to compare data using IBM SPSS Statistical ( v . 24 ) software; a p value of < 0 . 05 was considered statistically significant and a p value of > 0 . 05 was considered statistically non-significant . In all graphs , three asterisks indicate a p value of <0 . 001 , two asterisks indicate a p value of <0 . 01 , one asterisk indicates a p value of <0 . 05 , and ns indicates not significant ( p > 0 . 05 ) . The number of replicates used in experiments is specified in the corresponding figure legends . | Foot-and-mouth disease virus ( FMDV ) is the causative agent of a devastating disease affecting livestock worldwide . FMDV is considered an extremely successful pathogen able to replicate and spread rapidly among its hosts . The induction of type-I interferon ( IFN ) response is a crucial event in mammalian cells against infections , and viruses have evolved a variety of mechanisms to avoid it . LGP2 ( Laboratory of Genetics and Physiology 2 ) is a cellular protein involved in sensing viral RNA during infection and plays a relevant role on regulation of the signaling pathways leading to IFN induction . Here we show that LGP2 is specifically targeted for cleavage by the FMDV-encoded Leader protease ( Lpro ) and a correlation with a decrease in the IFN levels induced in infected cells . Our data unveil a new viral mechanism of immune evasion based on direct cleavage of LGP2 by the Leader proteases of aphthoviruses . To our knowledge this is the first report of the proteolytic cleavage of LGP2 by a virally-encoded protease . Our findings will contribute to a better understanding of the virus-host interplay involved in pathogenesis and to the development of more efficient strategies to combat infectious diseases . | [
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] | 2018 | Innate immune sensor LGP2 is cleaved by the Leader protease of foot-and-mouth disease virus |
Persistence of HIV DNA presents a major barrier to the complete control of HIV infection under current therapies . Most studies suggest that cells with latently integrated HIV decay very slowly under therapy . However , it is much more difficult to study the turnover and persistence of HIV DNA during active infection . We have developed an “escape clock” approach for measuring the turnover of HIV DNA in resting CD4+ T cells . This approach studies the replacement of wild-type ( WT ) SIV DNA present in early infection by CTL escape mutant ( EM ) strains during later infection . Using a strain-specific real time PCR assay , we quantified the relative amounts of WT and EM strains in plasma SIV RNA and cellular SIV DNA . Thus we can track the formation and turnover of SIV DNA in sorted resting CD4+ T cells . We studied serial plasma and PBMC samples from 20 SIV-infected Mane-A*10 positive pigtail macaques that have a signature Gag CTL escape mutation . In animals with low viral load , WT virus laid down early in infection is extremely stable , and the decay of this WT species is very slow , consistent with findings in subjects on anti-retroviral medications . However , during active , high level infection , most SIV DNA in resting cells was turning over rapidly , suggesting a large pool of short-lived DNA produced by recent infection events . Our results suggest that , in order to reduce the formation of a stable population of SIV DNA , it will be important either to intervene very early or intervene during active replication .
Treatment of HIV-1 infected individuals with highly active antiretroviral therapy ( HAART ) can suppress plasma viral RNA levels below the threshold of detection by standard diagnostic assays . However after cessation of even long-term HAART , virus replication is quickly re-established [1]–[4] . A barrier to viral eradication is the presence of viral DNA stably integrated into the chromosomes of resting CD4+ T cells and other long-lived cell populations , since the decay of this viral compartment is very slow [5]–[17] . Several studies suggest that persisting integrated viruses are laid down early in infection [18]–[20] . An indication for this is that HIV strains cultured from resting CD4+ T cells are genetically distinct to concurrent plasma virus [20] . However , it is generally difficult to study the precise kinetics of establishment and turnover of the latent reservoir in most human cohorts as the infecting isolate is usually not known and serial samples available during asymptomatic early infection ( 1–2 weeks post transmission ) are difficult to acquire . Studying macaques experimentally infected with SIV overcomes these barriers . Recent studies show the utility of SIV-infected macaque models for studying long-term integrated viruses [21]–[23] . During HIV and SIV infection one typically sees immune escape at defined cytotoxic T cell lymphocyte ( CTL ) epitopes . CTL escape mutations ( EM ) are frequently generated early after the acute infection stage and typically follow predictable patterns of outgrowing wild type ( WT ) virus . We hypothesised that evidence for the early formation and turnover of SIV DNA may be found by comparing the dynamics of immune escape in cellular viral DNA populations to the dynamics in replicating plasma virus . If replicating WT virus ( as indicated by plasma RNA ) is only present during acute infection , and is completely replaced in plasma by replicating EM virus during chronic infection , the latent reservoir will be primarily WT if laid down during acute infection , but predominantly EM if laid down ( or rapidly turned-over ) during chronic infection . In other words , if WT viral DNA is detected in resting CD4+ T cells during chronic infection and remains at similar levels when measured later , this supports low rates of turnover of viral DNA populations during active infection . We previously developed sensitive real-time PCR assays to quantify EM and WT viruses at a Mane-A*10-restricted SIV Gag CTL epitope ( termed KP9 ) in replicating plasma RNA [24] , essentially providing a “viral load” of both WT and EM quasispecies . For this study , we also developed PCR assays to assess WT and EM populations in cellular SIV DNA in FACS-sorted resting CD4+ T cells . After obtaining serial plasma and PBMC samples from Mane-A*10 positive SIV-infected pigtail macaques , we used the observed evolution of WT and EM replicating plasma SIV RNA viruses to model the turnover rate that resulted in the observed relative levels of WT and EM SIV DNA sequences . These analyses suggest that during periods of active high-level infection , the majority of SIV DNA in resting CD4+ T cells is turning over very rapidly . However , at lower levels of infection a substantial proportion of SIV DNA in resting CD4+ T cells is laid down early ( when virus is still WT at the CTL epitope ) and this WT reservoir persists at stable high levels during chronic infection .
We first studied 12 Mane-A*10+ animals in a SIV vaccine trial using an influenza virus vector , as this large study provided an extensive bank of plasma and PBMC samples ( Table 1 ) . We characterized the frequency of CTL escape mutant and wild-type variants in SIV plasma RNA ( Figure 1A ) . The evolution of EM and WT viruses in plasma was derived by a previously described SIV Gag KP9 qRT-PCR that specifically discriminates the K165R EM virus [24] . After infection with the SIVmac251 challenge stock , peak SIV viremia with predominating WT virus was observed ∼2 weeks post infection in all animals . K165R CTL immune escape predictably occurred [24] , [25] and EM virus predominated in chronic infection , being selected in preference to WT virus in the majority of animals . Several animals had plasma viremia trajectories in which there was minimal or no detectable EM virus in plasma during acute infection , and complete or near complete replacement of WT virus with EM virus in plasma during chronic infection . To assess SIV DNA within resting CD4 T cells , we sorted cells based on their being positive for CD3 and CD4 and negative for HLA-DR and CD69/CD25 ( Figure 1B ) , and then performed a nested PCR with the second round being specific for either WT or the K165R CTL EM virus ( Figure 1C ) . All animals were infected with SIVmac251 that is WT at this CTL epitope . The PCR provides relative levels of EM and WT SIV DNA in resting CD4 T cells . We performed assays on FACS-sorted resting CD4 T cells obtained from PBMC samples collected over the course of infection , and compared the ratio of WT and EM virus in plasma with that in SIV DNA in resting cells ( Figure 1D ) . These two ratios of WT/EM are the basis of the “escape clock” that we use to estimate the SIV DNA turnover rate in resting cells . The method is outlined in the in Figure 2 . Briefly , if SIV DNA turns over quickly ( or has a short half-life ) , then we expect the fraction of WT virus in SIV DNA to closely track the ratio seen in plasma virus , since most of SIV DNA would have been recently formed from plasma virus . If , on the other hand , SIV DNA is extremely stable ( or persists indefinitely ) , then we expect the fraction of WT in SIV DNA to reflect the accumulation of all latently infected cells over the whole previous course of infection . The archived viral DNA of each strain should then be proportional to the ‘area under the curve’ ( AUC ) of each virus over time . For any SIV DNA ratio in between these extremes , we could estimate the optimal half-life of SIV DNA that best fits the data using the model described in the Methods section . In the majority of these animals with active replication ( which had high viral loads ) we observed that CTL escape in the plasma SIV RNA was closely followed by CTL escape in the SIV DNA from FACS-sorted resting CD4 T cells ( first 8 animals in Figure 3 ) . The estimated half-life of SIV DNA was therefore extremely short – of the order of a few days . To confirm these results we also assessed reversion of the K165R KP9 CTL escape mutation in a Mane-A*10 negative animal infected with the SHIVmn229 challenge stock . This challenge stock had previously been passaged in a Mane-A*10+ animal and was composed largely of the K165R escape mutation [26] . In the absence of CTL pressure , we observe plasma SIV RNA rapidly reverting back to wild type , as previously reported [26] . Thus , this provides an ‘escape clock’ where EM instead of WT virus is temporarily expressed , and thus provides an excellent control for our measurements of WT∶EM ratio . Consistent with our findings with WT SIVmac251 infection , we found that the cellular SIV DNA in resting CD4 T cells also reverted back to wild type very rapidly in this animal with high levels of viral replication ( Figure 4 ) . The rapid turnover of cellular SIV DNA in resting CD4 T cells that we observed during high level SIV infection above was surprising , given the accepted stability of the latent reservoir in subjects with very low levels of replication on HAART . To investigate the effects of plasma viral turnover on the persistence of SIV DNA , we repeated the study on a cohort of 8 Mane-A*10+ animals from a peptide immunotherapy trial . These animals had undergone ART at week 3 , followed by immunotherapy and cessation of ART ( week 10 ) , leading to long-term low levels of viral replication in many animals . In these animals , escape was usually observed in the plasma following therapy interruption , leading to the rapid appearance and dominance of EM virus in chronic infection . Thus we were able to study SIV DNA dynamics in resting CD4+ T cells in chronic infection at a time of low viral loads in the absence of therapy . The results of fitting the half-life of WT DNA in animals from both trials are shown in Figure 3 , in the order of increasing estimated half-life . Analysis of the proportion of WT SIV DNA in resting cells from these animals produced a very different picture from that seen in the first cohort . In several animals , the SIV DNA in resting cells remained close to 100% WT , despite EM virus dominating the plasma for prolonged periods . When we estimated the half-life of SIV-DNA in these resting cells using the ‘escape clock’ approach , we found that in 4 animals with very low viral loads the half-life of SIV-DNA in resting cells was >20 years . In several other animals , although some turnover could be measured , the half-lives were extremely long . We then investigated whether viral load was a correlate of the rate of SIV DNA turnover in sorted resting CD4+ T cells . We observed a significant correlation between viral load and estimated SIV DNA half-life ( Figure 5 ) , suggesting that the high levels of infection and CD4+ T cell activation may play a role in determining SIV DNA turnover .
Current HAART regimes suppress plasma HIV RNA to very low levels , but cessation of HAART results in a brisk rebound of plasma virus [1]–[4] . Cellular compartments containing viral DNA provide a stable long-term reservoir for the virus [5]–[17] . However , the dynamics of establishment and turnover of this reservoir are not well understood . In particular , the majority of studies of HIV latency have focused on HIV DNA turnover under therapy , when viral replication and CD4+ T cell activation and turnover are greatly suppressed . But is HIV DNA persistence the same during active infection ? Our approach using a qRT-PCR to track the evolution of CTL escape mutants allowed us to compare EM and WT virus in plasma RNA and cellular DNA in a cohort of Mane-A*10 positive SIV-infected pigtail macaques . By analysing SIV DNA in purified resting CD4 T cells and comparing with plasma virus , we show that WT SIV DNA can persist in some animals for many months , even where there is an absence of WT viral RNA in replicating plasma virus . Thus , the WT SIV DNA species that are laid down early during infection can persist into late infection , and turnover of this viral compartment is very slow . Importantly however , this long half-life of WT DNA was only seen in animals with low viral loads . Animals with a high viral load showed a very rapid turnover of WT SIV DNA in resting CD4+ T cells . Indeed , we observed a highly significant correlation between the average viral load in chronic infection and the estimated half-life of SIV DNA . This correlation suggests that viral load is an important factor driving SIV DNA turnover in resting CD4 T cells during active infection . Our observation of the long half-life of SIV DNA associated with low levels of plasma virus is consistent with the previous studies of HIV DNA persistence under drug therapy , where viral loads are even lower than those observed here [14] . What is less clear from our study is why we see such a rapid SIV DNA turnover in resting cells during active infection . A number of mechanisms are possible . Firstly , it seems possible that CD4+ T cells simply don't get a chance to stay in the resting state long enough to maintain a stable integrated pool , since SIV DNA is continuously driven to productive infection because of host cell activation . The half-life that we are estimating here is then half-life spent in the “resting” pool , i . e . the time during which infected cells express CD3 and CD4 and are negative for HLA-DR , CD69 and CD25 . When they activate , they are no longer sorted as resting , and are lost from the pool in the same way as if they died . One limitation to our conclusions about the latent infection is that they apply only to CD69−CD25−HLA-DR− infected CD4+ T cells in blood , which may not truly represent the latent pool , but may be a heterogeneous population containing truly latently infected cells as a small subset . Thus , although the observed average turnover of HIV DNA in these resting CD4+ T cells is sometimes extremely fast , we cannot exclude that there might be minor populations of cells harbouring much longer-lived DNA , or that indeed long-lived DNA might not be harboured at some other anatomical site . Although we also found very few effector memory or dividing cells within the sorted resting CD4 T cell population , future studies could sort even more highly refined resting CD4 T cell populations or investigate other anatomical sites to evaluate this further . A second possibility is that the observed SIV DNA represents a mix of long-lived , integrated SIV DNA , and of short lived reverse transcription products that represent dead-ends for the virus . At low viral loads , the level of short-lived reverse transcription products is very low , as there is little virus present in plasma to produce new infections . Thus , the SIV DNA observed comes predominantly from the long-lived integrated pool , and we observe the slow SIV DNA turnover characteristic of this compartment . However , in animals with a high viral load , we may see a high level of recent infection and of short-lived reverse-transcripts . If viral loads are high enough , this pool of recent reverse transcripts is the dominant population we see , overwhelming the long-lived WT DNA , and leading to an apparent close tracking of the viral DNA in resting cells with the plasma DNA . This mechanism also predicts that the long-lived WT DNA pool always persists at the same level , but is numerically overwhelmed by the large number of copies of short-lived EM DNA when plasma viral load is high . In our model we did not consider a possibility that the half-life of infected resting cells depends on viral strain , because we assumed that they would not express viral epitopes and would not be recognized while resting . In addition , the fraction of WT DNA in resting cells is in most cases higher than in plasma , which is not supportive of preferential killing of resting cells with WT DNA . However , it is in principle possible that WT-infected resting cells are preferentially killed during periods of fast turnover , when the WT fraction is very low and approaches that in plasma . We note though that if preferential killing of WT infected resting CD4+ T cells were driving the rapid turnover of latency , we might expect that the turnover would be correlated with CTL number . Specifically , if this were the mechanism driving the turnover , we would expect that in animals with good CTL control ( low viral loads ) we should see faster turnover of HIV-DNA . However , we observed the opposite relationship . Moreover , when we analysed the correlation between the number of tetramer positive cells and HIV-DNA turnover , we found that both in early ( before the appearance of EM in plasma ) and in chronic infection the average number of tetramer positive cells was positively correlated with the estimated half-life of resting infected cells . This is in agreement with our interpretation that better immune control leads to less reactivation of latently infected cells . Our analyses are in agreement with early studies in humans suggesting that latent reservoirs in resting CD4+ T cells are laid down earlier in infection and are extremely long-lived [20] , [27] . There are a number of possible mechanisms by which long-lived SIV/HIV DNA may persist in cells ( illustrated in Figure 6 ) . Firstly , the individual cells bearing HIV DNA may be extremely long-lived . Secondly , these cells may turn over through homeostatic replication , with a balance of cell replication and death leading to a stable number of HIV DNA copies . Finally , it has been suggested that HIV persistence may be maintained by low levels of viral reactivation , replication , and reinfection of new cells , leading to a stable level of HIV DNA copies . This latter mechanism seems unlikely at low plasma viral loads given our results . That is , if WT DNA persistence involved reactivation , viral production into the plasma , and reinfection of new cells , then we should be able to estimate the proportion of new infections due to WT virus , by the ratio of WT∶ EM virus in the plasma . However , since in most cases we don't observe any WT virus in the plasma in chronic infection , it could at best make only a very trivial contribution to any reinfection , and could not maintain WT DNA levels at or above the AUC levels via this mechanism . There are limitations to our data that suggest further studies . Discriminating integrated from non-integrated forms of SIV DNA was not feasible in the small numbers of sorted resting CD4 T cells without further optimising the assay . Several assays have been designed to measure the more abundant non-integrated forms of HIV/SIV such as 1 LTR and 2-LTR circular forms , and these could be used in the future to determine the level of contaminating non-integrated SIV [28]–[31] . No widely accepted method exists to measure the “true” latent reservoir and our studies of resting CD4 T cells are only an approximation of this as yet undefined cell population . PCR-based assays have the disadvantage in that much of the cellular HIV-1 DNA may be from replication-deficient virus , although for viruses to contribute to the latent reservoir they must be replication-competent [20] , [32] . However , our analyses focus only on a single nucleotide change in the KP9 CTL epitope . This change ( alone ) is replication competent and it seems unlikely that additional lethal mutations would accumulate more commonly in either WT or the K165R EM species . Our results provide a method for direct quantification of HIV DNA turnover during active infection , and show for the first time that SIV DNA turnover in resting CD4+ T cells is strongly correlated with viral load during chronic infection . The rapid turnover of SIV DNA in animals with high viral load suggests the resting pool of CD4+ T cells and the pool of SIV DNA may be much more dynamic than previously thought during active infection . However , the persistence of WT SIV DNA laid down in early infection in animals with low chronic viral loads indicates the importance of the earliest stages of infection in establishing the latent pool of HIV DNA . Taken together , our study highlights the importance of early viral control in preventing the establishment of persistent HIV infection .
Experiments on pigtail macaques ( Macaca nemestrina ) were approved by CSIRO livestock industries Animal Ethics Committees ( approval number 1315 ) and cared for in accordance with Australian National Health and Medical Research Council guidelines . We studied serial PBMC and plasma samples from 20 pigtail macaques involved in several SIV infection studies [33] , [34] . Five macaques received no SIV vaccinations and were infected with SIVmac251 ( wild type at KP9 ) [35] . Two macaques received influenza viruses expressing KP9 and were infected with SIVmac251 [34] . Five macaques received influenza viruses expressing KP9 , KSA10 and KVA10 . Eight Mane-A*10 positive pigtail macaques were enrolled in a therapeutic peptide-based vaccine trial [33] . The outline of the therapeutic study was as follows: pigtail macaques were infected intravenously with SIVmac251 at week 0 and received ART ( tenofovir and emtricitibine ) from weeks 3 to 10 post infection and then withdrawn . Either no treatment ( controls ) or OPAL treatment ( overlapping 15mer Gag peptides only or peptides from all 9 SIV proteins ) was given at weeks 4 , 6 , 8 and 10 after infection . PBMC and plasma samples were collected at regular time points on all animals . The animals and their treatment are summarized in Table 1 . To quantify virus levels of WT or EM quasispecies at the KP9 epitope we employed a discriminatory real-time PCR assay as described [24] , [36] . Briefly , the assay uses a forward primer specific for either wild-type sequence or specific for the nucleotide mutation encoding the dominant K165R KP9 escape mutant . At each timepoint after infection 10 µl of plasma RNA was reverse-transcribed and then amplified by qRT-PCR using either WT or EM forward primers . A common reverse primer and FAM-labelled DNA probe were also added for quantification against the appropriate SIV Gag epitope RNA standards using an Eppendorf Realplex4 cycler . Analysis was performed using Eppendorf Realplex software . Baselines were set 2 cycles earlier than real reported fluorescence and threshold value was determined by setting threshold bar within the linear data phase . Samples amplifying after 40 cycles were regarded as negative , and corresponded to <1 . 5-Log10 SIV RNA copies/ml of plasma . Plasma viral cDNA was also subjected to Sanger-based sequencing as previously described [37] to confirm the EM quasispecies contained the K165R mutation detected in the qRT-PCR assay . We studied HLA-DR-CD69−CD25− CD4+CD3+ T lymphocytes as resting CD4 T cells as these cells are commonly studied as a model for resting CD4 T cells [32] , [38]–[41] . Frozen PBMC ( approximately 5×106 ) were thawed at 37°C in RF10 , centrifuged at 300 g and resuspended in 500 ul of PBS containing 2 mM EDTA . 0 . 5 µl live/dead ( Near Infra Red –IR ( APC-Cy7 ) viability stain/tube was added and tubes were incubated for 60 minutes on ice in the dark . Cells were washed for 5 min at 500 g , the supernatant removed and surface stained with an antibody cocktail of CD69-APC ( clone L78 ) , CD3-PE ( clone SP34-2 ) , CD4-FITC ( clone L200 ) , CD25-APC ( clone BC96 ) and HLA-DR- PerCP Cy5 . 5 ( clone L243 ) on ice in the dark for 60 minutes to avoid CD4 T cell activation . PBMC were washed in PBS containing 0 . 5% BSA and 2 mM EDTA , fixed in 0 . 1% formaldehyde and passed through filtered facs tube prior to being sorted on the FACSAria . Live resting CD4+ T cells were positive for CD3 and CD4 and negative for HLA-DR and CD69/CD25 . To validate whether HLA-DR-CD69−CD25− CD4+CD3+ T lymphocytes studied were truly resting using other markers we also studied CD28 and CD29 memory markers and the cell turnover marker Ki67 in a subset of the studied animals . The activated cells were highly enriched for CD28−95+ effector memory cells . A mean of only 0 . 91% of the resting cells were of the effector memory phenotype ( p<0 . 001 ) . The activated cells were also highly enriched for Ki67 staining ( p = 0 . 0028 ) . A mean of only 1 . 64% of the resting cells were Ki67+ . DNA from sorted cells was extracted using the Qiagen mini DNA . A nested KP9-specific qRT-PCR was performed that consisted of a first round Gag specific PCR followed by a second round discriminatory KP9 qRT-PCR . The first round PCR utilized 400 nM of the Gag forward primer ( 5′- CAAGTAGACCAACAGCACCATCTAGCGGCAG-3′ ) and reverse primer ( 5′- CTTGTTGTGGAGCTGGTTGTGGGTGCTGCAAGTC ) . Amplification was performed using 2 U Expand High Fidelity polymerase , 200 nM dNTPs and 250 mM MgCl2 per reaction . Amplification consisted of 94°C for 2 minutes followed by 22 cycles of 94°C for 15 seconds , 68°C for 30 seconds and 72°C for 45 seconds , with a final extension of 72°C for 7 minutes . The second round dKP9 qRT-PCR has previously been described for the analysis of WT and EM virus in plasma RNA , was performed [24] , [36] . The second round product was serially diluted 1/100 to 1/2000 to ensure that the second round qRT-PCR did not contain saturating amounts of DNA . Sanger based sequencing confirmed the ratios of WT∶EM virus observed in the real-time PCR reaction ( not shown ) . We start from a simple model describing WT and EM infection in resting CD4+ T cells: ( 1 ) In this model , cells infected with WT and EM ( IW and IE respectively ) are becoming resting ( RW and RE for resting cells infected with WT or EM respectively ) at a fixed rate μ and have a half-life of τR . Half-life can describe the loss of resting cells either to death or to activation . We do not have access to IW and IE from experiment , but we assume that free virus is turning over much faster than productively infected cells [42] , so that plasma virus to a good approximation reflects the corresponding productively infected cell level . This proportionality holds irrespective of the cause of viral load variation – be it because of the variation in target cell numbers , immune response or drug therapy . It allows us to replace μIW and μIE in Eq . 1 with fW and fE , where W and E are the plasma WT and EM viral loads , and f is a constant different from μ . We then use this model to estimate the half-life of viral DNA in resting infected cells using the measured WT and EM viral loads and the fraction of WT DNA in resting cells bW = RW/ ( RW+RE ) . For this purpose we rewrite the system Eq . 1 ( with W and E replacing IW and IE ) in terms of the WT fraction bW and a variable Λ representing total number of infected resting cells scaled by constant f , Λ = ( RW+RE ) /f: ( 2 ) The system Eq . 2 has only one fitting parameter , the half-life of viral DNA τR . We find the best fit of τR for each animal by solving Eq . 2 with initial conditions Λ ( t = 0 ) = 1 and bW ( t = 0 ) = 1 ( because inoculating SIVmac251 is 100% WT ) and choosing a value of δ = ln2/τR between 0 and 2 such that it minimizes the deviations from measured points of WT DNA fraction , using measured values of WT and EM viral load with exponential interpolation between time points for the variables W and E . Because the fitted values of the WT fraction bW must lie between 0 and 1 , the best-fit value of δ has to minimize the expression [43]: ( 3 ) where ti are the time points when the measurements were taken , bWexpt are the measured values of the WT fraction at this point , and bWpred are the values predicted by the model . The arcsin-square root transformation of the deviations was used to normalize the error distribution . Given the initial conditions , the solution Λ ( t ) , bW ( t ) of the system Eq . 2 for each value of τR is unique . Therefore it is sufficient to have one experimental WT fraction different from 1 or 0 to completely define the trajectory of WT fraction in time . We have such points for all animals . Even when a fraction looks like 1 or 0 , it often deviates a little from these numbers . The largest possible value of τR that could be obtained from our model is infinity ( which we report as >105 because δ = 10−5 is the lowest parameter value used that was greater than zero ) , and the lowest possible value is 0 . 35 days ( if this is the best fit , we report it as <0 . 5 days ) . The confidence intervals for each animal in Figure 5 are obtained by bootstrapping , using the errors transformed by arcsin-square root . The initial point bW ( 0 ) = 1 was not used in bootstrapping . Because the total number of measurements for each animal was small , we used the whole set of error permutations to determine the bounds of the confidence intervals . Our model assumes that the constant f is the same for cells infected with WT and EM . However , this constant may be higher or lower in one of the strains , depending on its propensity μ to generate latently infected cells , fitness cost of mutation and type of immune response . We have therefore repeated the process by simultaneously fitting the ratio fE/fW and τR and found that this did not change the range of observed half-lives or the correlation of half-lives with chronic viral load . The details of this analysis are shown in the Text S1 in the online Supplementary material . It should be noted that RW and RE , which we regarded as infected resting cells in Eq . 1 and Eq . 2 , can also be interpreted as the WT or EM DNA content in resting cells ( just as IW and IE can represent viral DNA in productively infected cells ) , In this case , the half-life of τR describes the loss of viral DNA due to cell death , degradation or resting cells becoming activated . | New treatments for HIV have proved very successful at controlling viral replication and preventing the onset of AIDS . However , these treatments must be continued for life , because if they are stopped the virus rapidly ‘rebounds’ to its original levels . The reason for this rebound is the existence of a population of viruses that lie dormant inside cells during treatment , and reactivate as soon as treatment is stopped . This ‘latent virus’ is extremely long-lived under drug therapy conditions , and therefore presents a major barrier to viral eradication . However , very little is known about the survival and reactivation of latently infected cells during ongoing infection , because virus is being formed and destroyed all the time . We have developed a novel ‘escape clock’ approach to measure how long viral DNA lasts in monkeys . We find that , in the setting of low viral load , the lifespan of infected cells is very long , whereas during active infection there is a surprisingly high turnover of viral DNA within resting CD4 T cells . We believe this is due to high level of immune activation when there is a high level of replicating virus . This result may have important implications for the optimal timing of drug treatment . | [
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] | 2012 | An “Escape Clock” for Estimating the Turnover of SIV DNA in Resting CD4+ T Cells |
Protein electrospray ionization ( ESI ) mass spectrometry ( MS ) -based techniques are widely used to provide insight into structural proteomics under the assumption that non-covalent protein complexes being transferred into the gas phase preserve basically the same intermolecular interactions as in solution . Here we investigate the applicability of this assumption by extending our previous structural prediction protocol for single proteins in ESI-MS to protein complexes . We apply our protocol to the human insulin dimer ( hIns2 ) as a test case . Our calculations reproduce the main charge and the collision cross section ( CCS ) measured in ESI-MS experiments . Molecular dynamics simulations for 0 . 075 ms show that the complex maximizes intermolecular non-bonded interactions relative to the structure in water , without affecting the cross section . The overall gas-phase structure of hIns2 does exhibit differences with the one in aqueous solution , not inferable from a comparison with calculated CCS . Hence , care should be exerted when interpreting ESI-MS proteomics data based solely on NMR and/or X-ray structural information .
Proteomics , the large-scale characterization of proteins and their interactions , is key to understand cellular processes including signaling pathways , metabolism , and gene transcription [1]–[3] . Arguably , the most powerful tool for studying functional proteomics is protein electrospray ionization ( ESI ) mass spectrometry ( MS ) [3]–[11] . ESI-MS detects rapidly and reliably proteins in complexes formed during cellular processes at physiologically relevant concentrations [12] . It provides the stoichiometry , topology , connectivity , dynamics and shape of multi-protein complexes when combined with ion mobility ( IM ) -MS experiments [2] , [13] . Using the IM-MS technique , collision cross sections ( CCS ) can be determined [2] , [3] , [13] , [14] with protein concentrations well below those required for high resolution ( X-ray and NMR ) as well as low resolution traditional structural biology techniques [3] , [6] , [15] , [16] such as electron microscopy [17] and tomography [18] . ESI-MS has also been used for structural proteomics in combination with experimental structural biology techniques ( e . g . X-ray and NMR ) and/or computational techniques ( e . g . homology modeling and protein-protein docking ) [3] , [19]–[23] . These applications are based on the assumption that the vaporization of non-covalent protein complexes from aqueous solution into the gas phase ( as occurs during ESI-MS ) in general preserves the characteristic structural determinants of the complexes in water [24]–[28] . This assuption is consistent with the avaliable CCS data for some biomolecules and with the fact that intact non-covalent protein complexes in ESI-MS are indeed transferred into the gas phase [29]–[34] . However , direct proove for this concept has not been forthcoming at the atomistic structural level , because the structural determinants of gas-phase protein complexes have remained largely unknown [28] . Thus , the preservation of these determinants on passing from solution into the gas phase is still under debate for protein complexes . Predicting the structure of protein complexes under ESI-MS conditions , and in particular assessing whether native interactions in the gas phase reflect those in the aqueous phase , is therefore important for ESI-MS based structural proteomic studies . A straightforward approach to improve the structural prediction is to run molecular dynamics ( MD ) simulations and select models that are consistent with the CCS [35] , [36] . However , these investigations have limited predictive power as no validations are provided against the main charge and the simulation is basically used as a tool to generate structural ensembles from which specific conformers can be selected [35] . More elaborate protocols have been developed for single proteins in the gas phase [24] , [37]–[47] . These approaches have predicted ensembles of structures consistent with the experimentally measured charge and CCS [38] , [39] . They have further suggested that desolvation leads to more compact overall protein structures while preserving the majority of the secondary and tertiary structures [24] , [37] , [38] , [40] . In addition , the fraction of hydrogen bonds ( relative to the theoretical maximum ) increases significantly upon passing from aqueous solution ( on average 43% ) to the gas phase ( on average 56% ) [41] . This suggests that proteins in the gas phase may be trapped in a low energy state , structurally close to the native state in water [42] . Our recent studies further indicate that the ionization state of a gas-phase protein is the result of the balance between repulsive electrostatic terms and stabilizing forces that include salt bridges , hydrogen bonds , π-charge and long-range electrostatic interactions [37] , [38] . Therefore , these simulation schemes appear instrumental to predict the structural determinants of protein complexes . Recently , we have proposed an efficient approach to sample exhaustively the proteins' protonation state space , based on a hybrid Monte Carlo ( MC ) /MD scheme [38] . Here , we extend this computational scheme , originally developed for single protein ESI-MS structural predictions , to a protein complex , the human insulin dimer ( hIns2 hereafter , supporting information ( SI ) , Figure S1 ) . hIns2 is present in vivo [48] . It is used for the treatment of diabetes and obesity [49] , [50] . Our predictions reproduce the experimental main charge state and CCS . They further show that , in the sub-ms time scale ( possible times of the ESI-MS experiments to form stable gas-phase structures , ranging from ms to s [28] ) the overall gas-phase structure of the complex rearranges already significantly . The final gas-phase structure differs distinctively from the solution structure as large amplitude reorganizations take place in order to maximize intra- and intermolecular hydrogen bond interactions , which are necessary for the formation of stable gas-phase structures . Hence , our current work provides evidence against the assumption that non-covalent complexes being transferred into the gas phase generally preserve their structural determinants in solution .
We have reported a systematic exploration of the charge and conformational space of the hIns2 non-covalent complex in the gas phase by using a hybrid MC/MD approach and sub-millisecond MD simulations . The long time required for observing structural changes such the unfolding of the helices ( ∼25 µs ) , as well as other conformational rearrangements , confirms that conformational changes in the gas phase may happen over long time scales ( from µs to ms ) [28] , [69] , [70] . Our calculations correctly reproduce the experimental main charge and the CCS measured in solution at pH = 7 . 4 [52] . Hence , molecular simulations approaches such as the one reported here may be a useful tool to ( study and ) complement the structural analysis of protein complexes via ESI-MS . We suggest that distinct protein complexes differ from one another when their structural properties are determined in gas phase or in solution . This is due to a substantial structural reorganization as a consequence of the maximization of intra- and intermolecular hydrogen bond interactions , which are necessary for the formation of stable vacuum structures . Therefore , care should be exerted when interpreting ESI/IM-MS data that are solely based on NMR and/or X-ray structural information . Consistent with this , recent experimental work also illustrates that the comparison between measured and calculated CCS based on X-ray structures can only provide a semi-quantitative estimate [71]–[74] . This may be attributed to the considerable uncertainties ( from 0 to ∼40% ) involved in the experimental measurements of CCS related to drag enhancement of protein ions in the drift tube and other factors [71]–[73] , as well as to the compaction of protein structure in the gas phase in comparison to the corresponding X-ray crystal structure [73] . Computational approaches such as ours or those by other groups [24] , [56] , [75] , may therefore be instrumental to understand how desolvation affects the structure and stability of other protein complexes . Such simulations may establish whether the present findings can be generalized . This type of calculations may be of help for the development of efficient strategies to optimize experimental factors to control the gaseous protein ion structure in ESI-MS experiments .
We first performed MD simulations in water based on the X-ray structure of hIns2 ( 1 . 0 Å ) ( PDB ID: 1MSO [76] ) . The protonation states of residues in solution were assigned according to the corresponding pKa values calculated by using the H++ webserver [77] . As a result , H26 , H31 , R43 , K50 and N-terminal residues ( G1 , F22 , G52 and F73 ) were positively charged and E4 , E17 , E34 , E42 and C-terminal residues ( N21 , T51 , N72 and T102 ) were negatively charged . The total charge of the complex is 0 . hIns2 was inserted into a water box with edges of 71×52×63 Å3 ( in total 22 , 519 atoms ) . The AMBER ff99SB-ILDN force field [78]–[81] and TIP3P force field [82] were used for the protein complex and for water , respectively . Periodic boundary conditions were applied . Electrostatic interactions were calculated using the Particle Mesh Ewald ( PME ) method [83] , and the cutoff for the real part of the PME and for the van der Waals interactions was set to 0 . 9 nm . All bond lengths were constrained using the LINCS algorithm [84] . Constant temperature and pressure conditions were achieved by coupling the systems with a Nosé-Hoover thermostat [85] , [86] and an Andersen-Parrinello-Rahman barostat [87] . A time-step of 2 fs was employed . The protein complex underwent 1000 steps of steepest-descent energy minimization with 1000 kJ·mol−1·Å−2 harmonic position restraints on the protein complex , followed by 2500 steps of steepest-descent and 2500 steps of conjugate-gradient minimization without restraints . The system was then gradually heated from 0 K up to 300 K in 20 steps of 2 ns . 100 ns long MD simulation at 300 K and 1 atm pressure was carried out using GROMACS 4 . 5 . 5 [88] . The structure nearest to the average conformation of the complex in aqueous MD simulation ( see Figure S1 ) was employed as starting structure for the MC/MD exploration of the protonation state space . The solvent molecules were removed . The MC/MD simulations ( see Text S1 for details ) were based on the OPLS/AA [63] force field energies augmented by additional energy terms associated with the GB of ionizable residues [38] . To validate the augmented term , the energies of 60 selected protonation states for q = 6+ without and with the GB correction , as well as with DFT were calculated using the Becke exchange and Lee-Yang-Parr correlation functional ( BLYP ) [89] , [90] and the TZV2P Gaussian basis set [91] . As in ref . [37] , [38] , [92] , only the N-terminal , C-terminal , R , K , H , Q , D , and E residues were allowed to protonate or deprotonate . We chose the OPLS/AA [63] force field because it offers the most complete set of base/conjugate acid pairs for these residues , e . g . the force-field parameters for the deprotonated arginine residue are missing in AMBER [93] or CHARMM [94] force fields . Issues related to a particular choice for the force field have been carefully addressed in our earlier work [37] , [38] . Specially , we showed that three different force fields ( GROMOS 41a1 [64] , AMBER99 [93] , and OPLS/AA [63] ) give the same gas-phase charge state for nine proteins of different size and fold , when the calculations were limited to protonation states containing the ionized residues common to all of the three force fields [38] . We considered protonation states at total charge states from q = 1+ to q = 15+ ( this includes the experimentally measured q = 6+ [52] ) . The MC/MD protocol converged after a number of MC steps in the range of 1 , 500 to 6 , 500 , depending on the charge state ( over a total of ∼4 , 000 to ∼120 , 000 , 000 possible protonation states for each charge , see Table S4 ) were performed for various charge states . The lowest energy protonation state for the main charge state ( q = 6+ ) underwent MD simulations at 300 K for 0 . 075 ms in the gas phase with the same setup as the one described for the aqueous MD simulation , except that the time-step was 1 . 5 fs and the force fields was OPLS/AA [63] . To check for dependence on the microscopic initial conditions , additional two MD simulations , each 0 . 035 ms long , on the same protonation state were performed using different starting velocities . To check for the dependence of the results from the force field , we also performed 0 . 025 ms long MD simulation using GROMOS 43a1 [64] . The latter force field along with OPLS/AA [63] , unlike others such as AMBER [93] and CHARMM [94] , have standard parameters for deprotonated arginine residues . The latter are present in the identified lowest energy protonation state of [hIns2]6+ ( see Table S1 ) . Furthermore , MD simulations on other lower energy protonation states at the main charge state , with charges located on different residues , have been also carried out ( see Table S5 , Table S6 and Text S1 ) . Secondary structure elements were detected by using Define Secondary Structure of Proteins ( DSSP ) [95] . All figures for the visualization of structures were drawn using PyMOL ( Molecular Graphics System , Version 1 . 3 , Schrödinger LLC ) . CCS values were calculated for structures every 73 . 5 ns using the trajectory method [96] implemented in the MOBCAL code [97] . The EDA [62] was carried out for the whole ( 0 . 010 µs long ) trajectory in water combined with the whole ( 0 . 075 ms long ) trajectory in the gas phase , for the whole gas-phase one alone and for the converged part ( 0 . 055 to 0 . 075 ms ) of the trajectory in the gas phase . The EDA was performed after iterative superposition of the MD trajectories on the crystal structure of hIns2 . The ProDy ( Protein Dynamics & Sequence Analysis ) interface [98] implemented in VMD1 . 9 . 1 [99] was used for the visualization of EDA . The MC calculations were carried out using standard Metropolis sampling [100] written as a bash/awk shell script , the MD using GROMACS 4 . 5 . 5 [88] . | Electrospray ionization ( ESI ) mass spectrometry ( MS ) plays a pivotal role in proteomics and structural biology . The applications of ESI-MS to protein complexes make use of the assumption that the vaporization of protein complexes into the gas phase ( as occurs during ESI-MS ) preserves the structural determinants of the complexes that are observed in water . We used computational methods to investigate this key issue by studying the gaseous structure of a pharmacologically relevant protein complex . The complex in the gas phase differs in a subtle yet significant way from the solution structure . This finding is likely of general relevance for protein-protein complexes . Hence , our work implies that the assumption used in proteomic studies , i . e . that in the gas phase non-covalent complexes generally preserve the representative structural determinants observed in the aqueous phase , needs to be reconsidered . Therefore we suggest that the analysis of complexes should be performed on an individual base rather than by generalized principles . | [
"Abstract",
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"simulations"
] | 2014 | Molecular Simulation-Based Structural Prediction of Protein Complexes in Mass Spectrometry: The Human Insulin Dimer |
Meiosis is a cellular program that generates haploid gametes for sexual reproduction . While chromosome events that contribute to reducing ploidy ( homologous chromosome pairing , synapsis , and recombination ) are well conserved , their execution varies across species and even between sexes of the same species . The telomere bouquet is a conserved feature of meiosis that was first described nearly a century ago , yet its role is still debated . Here we took advantage of the prominent telomere bouquet in zebrafish , Danio rerio , and super-resolution microscopy to show that axis morphogenesis , synapsis , and the formation of double-strand breaks ( DSBs ) all take place within the immediate vicinity of telomeres . We established a coherent timeline of events and tested the dependence of each event on the formation of Spo11-induced DSBs . First , we found that the axis protein Sycp3 loads adjacent to telomeres and extends inward , suggesting a specific feature common to all telomeres seeds the development of the axis . Second , we found that newly formed axes near telomeres engage in presynaptic co-alignment by a mechanism that depends on DSBs , even when stable juxtaposition of homologous chromosomes at interstitial regions is not yet evident . Third , we were surprised to discover that ~30% of telomeres in early prophase I engage in associations between two or more chromosome ends and these interactions decrease in later stages . Finally , while pairing and synapsis were disrupted in both spo11 males and females , their reproductive phenotypes were starkly different; spo11 mutant males failed to produce sperm while females produced offspring with severe developmental defects . Our results support zebrafish as an important vertebrate model for meiosis with implications for differences in fertility and genetically derived birth defects in males and females .
Meiosis is a process that generates haploid gametes via one round of DNA replication and two rounds of chromosome segregation . Typically , homologous chromosomes ( homologs ) separate during meiosis I , and sister chromatids separate at meiosis II . Errors at either stage can lead to the production of aneuploid gametes , which is a major contributor to miscarriage and birth defects in humans [1] . During meiosis I prophase , homologs undergo pairing and crossing over , which is essential for their proper segregation in nearly every organism studied to date [2 , 3] . Crossovers are created through a process termed recombination , where programmed DNA double-strand breaks ( DSBs ) are repaired using the homolog as a template , resulting in the exchange of homologous chromosome arms [2 , 3] . Meiotic DSBs are formed by Spo11 , a conserved topoisomerase-like enzyme [4] . They are then processed to reveal 3’ single stranded stretches of DNA that bind the strand exchange proteins , Dmc1 and Rad51 , and engage in homology search [4–6] . In meiosis , the repair template is preferentially skewed towards the homologous chromosome rather than the sister chromatid , thus facilitating the pairing process [2] . While hundreds of DSBs might form in a single meiotic cell , only a subset go on to form crossovers , with the others being repaired via a noncrossover pathway [2 , 3 , 7] . DSB formation and crossing over occur in the context of the chromosome axis , a proteinaceous structure to which a linear array of chromosome loops is attached; both sister chromatids of a homolog are attached to a single axis and held together by cohesins [7 , 8] . In many organisms , including mouse , budding yeast , and several plants , recombination initiation and repair intermediates are necessary for formation of the synaptonemal complex ( SC ) , a tripartite proteinaceous structure that forms between the two homolog axes and holds them together along their lengths [2 , 3 , 7–9] ( S1 Fig ) . However , DSBs are dispensable for SC formation ( synapsis ) in some organisms such as C . elegans , Drosophila , and the planarian Schmidtea mediterranea [10–13] . In C . elegans and Drosophila , synapsis is initiated at “pairing centers” and ensues without the need for recombination [12] . In most organisms studied to date , recombination and the SC are used to link the homologous chromosomes . Notable exceptions are Drosophila males [14 , 15] and Lepidopteran females [16] which do not form crossovers , and Tetrahymena [17] and fission yeast [18] which do not form the SC . SC formation initiates primarily near telomeres in many organisms , including human males [19 , 20] , cattle males [21] , the silkworm Bombyx mori [22 , 23] , the planarian Schmidtea mediterranea [13] , and some plants such as tomato [24] and barley [25 , 26] . In mouse males , while synapsis initiates interstitially as well as near the telomeres , there is a skew toward initiation at chromosome ends [27] . By contrast , synapsis in mouse and human females initiates primarily in interstitial regions [20 , 28] , while synapsis in female cattle initiates both near telomere ends and interstitially [21] . In many organisms , SC is nucleated preferentially at crossover fated sites [2] . Correspondingly , in mouse , human , and cattle , there is a skew toward crossovers in the distal regions of chromosomes in males but not in females [20 , 29 , 30] . During meiosis , telomeres are tethered to the nuclear envelope and their movement is directed by cellular cytoskeleton components [31–37] . One type of motion that is prominent in many species is the movement of chromosomes into and out of the bouquet , a conserved arrangement of chromosomes where telomeres are clustered together to one side of the nucleus . The bouquet has been hypothesized to restrict the chromosomes to one region of the nucleus thereby facilitating homolog recognition and pairing , possibly by limiting the homology search area or by active chromosome motion to disrupt weak non-specific interactions [2 , 38] . However , in some organisms the bouquet does not exist ( e . g . C . elegans and Drosophila ) or does not form until after homologs are already co-aligned ( budding yeast , Sordaria , mouse , and some plants ) [2 , 39] , in which case it may play additional roles such as removing interlocks that form between two synapsed chromosomes [40] . Previous studies have shown that telomeres can form end-to-end associations in mammalian spermatids [41 , 42] as well as in somatic and pachytene cells of some plants such as the dandelion-like smooth hawksbeard , Crepis capillaris [43 , 44] , pachytene cells of the cricket , Gryllus argentinus [45] , and human spermatocytes [46] . The number and timing of these associations during meiotic prophase is poorly understood . Our understanding of meiosis has been facilitated by the breadth of model organisms that have been studied , with each contributing new insight into the process . Budding and fission yeasts , C . elegans , Drosophila , mouse , and several plants have been instrumental to the study of the chromosome events of meiosis [9 , 47] . While the basic features of meiosis are well conserved , the order of events and their functional dependencies vary significantly across species [2 , 3 , 48] . Indeed , the analysis of species-specific features has greatly informed our understanding of the seemingly fluid relationships between double-strand breaks ( DSBs ) , the telomere bouquet , homolog pairing , synapsis , and recombination over evolutionary time scales [47] . There are remarkable similarities relating pairing , synapsis and recombination across phyla , even though difference in genome sizes can vary by orders of magnitude , especially when comparing mouse and humans to yeast , Drosophila , and C . elegans . Understanding how the chromosome events of meiosis are accommodated by larger genomes ( and vice versa ) necessitates the inclusion of additional model genetic organisms . Zebrafish has many advantages as a vertebrate model for meiosis . Zebrafish can produce hundreds of offspring from a single cross , and external development allows for early detection of developmental abnormalities , including those caused by aneuploidy [49–51] . Unlike mammalian females , zebrafish females produce new oocytes throughout adulthood [52 , 53] , simplifying the characterization of female meiosis , which occurs in the fetal ovary in mammals . In addition , transparent gonads allow for observation of multiple stages of meiosis in a whole mount . Several cytological studies have provided insights into some aspects of zebrafish meiosis . For example , it has been shown in males that DSBs and the initial loading of the chromosome axis protein , Sycp3 , and the SC transverse filament protein , Sycp1 , are polarized to one side of the nucleus near the bouquet [6 , 54–56] . Mlh1 foci , indicating sites of crossovers , have been shown to be distally skewed in males but not females [57] . These data are consistent with the genetic map where recombination is skewed to the telomeres in males yet more evenly distributed in females [58 , 59] . A major gap of knowledge is that the order of events and the relationship between chromosome structure and recombination are not known . For example , it is not known if Spo11 , a protein required for the formation of meiotic DSBs , is necessary for synapsis and homolog pairing in the zebrafish . This is an important relationship to determine as it sets the stage for further analyses of chromosome dynamics . In this study we set out to establish the relationship between DSBs , synapsis initiation , and the establishment of close , stable homolog juxtaposition ( which we refer to here as pairing ) in the zebrafish males and females . We analyzed the progression of chromosome synapsis and pairing , telomere interactions , and double strand break localization at the super-resolution level . We created a knockout mutation in the spo11 gene and found that both pairing and synapsis in the zebrafish are Spo11-dependent . We found dramatic sex-specific outcomes from disrupting Spo11: although synapsis and pairing defects were similar between spo11 mutant males and females , males were completely sterile while females were able to produce offspring , though with severe developmental defects . Our results establish zebrafish as a tractable vertebrate model for understanding the chromosome events of meiosis I prophase from an evolutionary vantage and opening new lines of research with implications for human fertility and genetically derived birth defects .
To better understand the relationship between the bouquet , Sycp3 loading , and synapsis in zebrafish , we set out to find when and where these events occur relative to one another in the prophase I nucleus . We stained spermatocyte nuclear spread preparations using a fluorescently tagged PNA probe by in situ hybridization to mark repeated telomere sequences , an Sycp3 antibody to mark the chromosome axis , and an Sycp1 antibody to mark the SC . The images were collected using structured illumination microscopy ( Fig 1 , S1 Fig ) . A general overview emerged . The telomere bouquet was prominent at the leptotene and zygotene stages ( Fig 1 , panels 1D-5D ) . Early Sycp3 loading occurred adjacent to the telomere probe and extended toward the middle of the chromosomes as meiotic progression advanced ( see magnified regions in Fig 1 , rows E , F , and G ) . When the average Sycp3 length reached about 1 μm from the end of the chromosome , Sycp1 lines appeared close to the telomeres and then extended inward; as Sycp3 lines extended , Sycp1 lines closely followed , yet lagging somewhat behind ( Fig 2A ) . Interestingly , some chromosomes appeared to have more than one synapsis initiation site , albeit they were still in close proximity to the telomere ( Fig 1 , panels 3F and 4F ) . To facilitate comparisons between nuclei , we established staging criteria based on the total length of Sycp1 in 30 pre-pachytene images ( Fig 2B ) . We divided the nuclei into five classes: leptotene ( L; Sycp1 = 0 μm ) , leptotene to early zygotene transition ( L/EZ; Sycp1 = 1–10 μm , with few short stretches of SC near the telomeres ) , early to mid-zygotene ( EZ/MZ; Sycp1 = 10–50 μm ) , mid- to late zygotene ( MZ/LZ; Sycp1 = 50–100 μm ) , and late zygotene ( LZ; Sycp1 > 100 μm ) . Spreads that contained more than three fully synapsed chromosomes were not measured as they were considered to be transitioning to pachytene and were referred to as “pre-pachytene” . In wild type zebrafish , we observed frequent end-to-end associations between telomeres , either as doublets or in higher order structures at all stages of prophase I ( Fig 1 , panels 1E and 1G-6G , Fig 2C ) . We assessed the extent of these associations by counting the total number of engaged telomere ends , defined by an Sycp3 line and its telomere associating with another end . One association could involve two or more engaged telomere ends . For a detailed description of our criteria see the methods . We observed the highest numbers of associations at the L to L/EZ stages , with an average of ~ 31% of telomeres engaged in associations with each other ( Fig 2C ) . The associations subsequently decreased to an average of ~ 6% but were still detected throughout the later stages including pachytene . In some cases , a short stretch of Sycp3 could be seen bridging the telomeres of unrelated chromosomes ( Fig 1 , panels 5G and 6G ) . The nature of these bridges is not known , however , Sycp3 protein can both bind dsDNA and form self-assemblies which are consistent with what we see [60 , 61] . Associations involving more than two chromosomes indicated that at least a subset of telomere associations occurred between nonhomologous chromosomes or at the opposite end of the same chromosome . This was especially evident at the zygotene stage where telomeres of synapsing chromosomes were seen forming associations with a non-partner telomere , and at the pre-pachytene and pachytene stages where telomeres of synapsed chromosomes associated with nonhomologous chromosomes ( Fig 1 , panel 6G ) . Our data suggest that telomere associations are a normal part of zebrafish meiosis I and not a pathological occurrence such as fusions caused by nonhomologous end-joining . In nearly every organism studied to date , axes of homologous chromosomes undergo some degree of co-alignment , or pairing , prior to synapsis , in which the distance between co-aligned axes is typically about 0 . 4 μm [2 , 62] . Analysis of co-alignments seen in several species suggest the chromosomes are held in close proximity by DNA intermediates of the homologous recombination pathway [2] . We inspected images of spermatocyte nuclear spreads for evidence of axis co-alignment in the absence of detectable SC , marked by Sycp1 . A detailed description of co-alignment assessment is provided in the methods . In brief , chromosome regions were considered co-aligned when Sycp3 lines were closely juxtaposed with the narrowest region between them at a distance of < 0 . 5 μm ( Fig 1 , Panels 1F and 2F , Fig 2D ) . We found that presynaptic co-alignment of chromosomes occurred near the telomeres and adopted two main types of configurations: funnel and pinch . In the funnel configuration , co-alignment occurred directly adjacent to the telomeres to form the stem of the funnel while the other ends of the Sycp3 lines diverged away from the stem . The diverging lines could either be long or short ( Fig 1 , panels 1F and 2F; Fig 2D ) , cross each other , or even fold backward toward the stem . In the pinch configuration , the narrowest region between the Sycp3 lines did not occur directly adjacent to the telomere , but a short distance away ( Fig 2D ) . We found a total of 23 funnel configurations and 10 pinch configurations among 24 wild-type spermatocyte cells from the L to the MZ/LZ stage . During leptotene , co-alignments were rare , indicating that chromosomes were not stably juxtaposed with their partners at this stage ( Fig 2E ) . We found the highest number of co-alignments during the L/EZ and EZ/MZ stages , when the chromosomes begin to actively engage with each other to initiate synapsis . By the MZ/LZ and LZ stages , we found almost no co-alignments since most or all of the chromosomes had already engaged in telomere proximal synapsis ( Fig 2E ) . As individual nuclei with presynaptic co-alignment usually have less than a total of five co-alignments ( Fig 2F ) , we believe that this is a transient stage mediated by homologous recombination that quickly progresses to synapsis initiation for any given chromosome pair . The funnel and pinch configurations likely represent recombination events that initiate very close to the telomere or slightly inward . It is likely that the pinch and funnel axis shapes are precursors to synapsis initiation since we saw similar configurations with short stretches of SC ( Fig 1 , panels 2E and 2F; Fig 2D ) . Moreover , unpaired telomeres in the pinch configurations suggest that stable telomere associations are not the primary driver of homolog pairing and that initial homology recognition can occur in sub-telomeric regions . While we observed pre-synaptic co-alignment near the telomeres , we found no evidence for similar co-alignment at interstitial regions of the axes . For chromosomes where synapsis had initiated , the distances between the diverging edges of the two Sycp3 lines were often much greater than 0 . 4 μm and were frequently bent in non-parallel orientations with respect to each other ( Fig 1 , panels 2E , 3E , 3F , 5F , 3G , 4G ) . This suggested that axes were not stably co-aligned at interstitial regions prior to synapsis . To determine when interstitial sites become stably co-aligned relative to SC formation , we performed fluorescence in situ hybridization ( FISH ) on cells at different stages of meiotic prophase I using a 68 kilobase bacterial artificial chromosome ( BAC ) probe located ~10 Mb from the end of chromosome V ( total 72 . 5 Mb ) ( Fig 3 , S2 Fig ) . We found that the BAC signals were far apart in the early prophase I stages but paired up as synapsis progressed ( EZ/MZ to LZ ) . In a few instances , we found cells where the BAC probe localized to forked regions of Sycp3 just ahead of synapsis ( Fig 3C ) . These data suggest that stable juxtaposition between homologs does not occur until they are synapsed at that region . Prior to pairing , the BAC signal presented as an amorphous shape , while at synapsed regions the shape was elongated and appeared to lie perpendicular to the axis ( Fig 3 , S2 Fig , LZ and Pachytene panels ) . The two prominent features of a meiotic chromosome are the axes that run along the chromosome length and the DNA loops that attach to the axis . It is possible that the change in shape of the BAC signal reflects a change in chromosome architecture , for example , from a fractal globule , characteristic of interphase chromosomes [63] , to a looped region that characterizes the DNA component of meiotic chromosomes [62] . Several lines of evidence point to differences between female and male meiosis in zebrafish . Females have longer chromosome axes and exhibit a more even distribution and higher numbers of crossovers [57–59 , 64] . In order to determine if early prophase events in females differed from males , we stained ovary nuclear surface spreads with the telomere probe and antibodies against Sycp3 and Sycp1 . We staged nuclei based on the overall appearance of axis extension and synapsis progression . We found that the progression of prophase I in females was similar to that in males: Sycp3 loading and synapsis initiated near both telomere ends in the bouquet and elongated toward the center of the chromosome , with synapsis lagging behind Sycp3; chromosomes appeared to become stably juxtaposed as synapsis progressed ( Fig 4 ) . Chromosome interlocks are common during the zygotene stage in several organisms including the silkworm , Bombyx mori , and maize , Zea mays , but most interlocks are resolved by pachytene [22 , 62 , 65 , 66] . In the zebrafish spermatocytes , we regularly found chromosomes that were intertwined or sometimes trapped between another set of homologs at the pre-pachytene stages when most of the chromosomes were already synapsed ( i . e . 16–24 fully synapsed chromosomes; Fig 5 ) . These configurations closely approximated interlock structures seen at late zygotene in other species [2] . Interlocks occur when one chromosome or a pair of chromosomes becomes entrapped between the space of two synapsing homologs . Thus , from a first approximation , the structures we see are likely interlocks . Interestingly , nuclei at this stage frequently also had individual pairs of chromosomes with extensive or complete de-synapsis , sometimes with another homolog appearing to be entrapped in the desynapsed region ( Fig 5 , Panels 1A-1C , 2A-3D , 5A-6D ) . Of 8 cells at this pre-pachytene stage , only 2 showed no anomalies . Of the remaining cells , 3 had both interlocks and de-synapsis , 1 had just an interlock , and 2 had just de-synapsis . The de-synapsis is unlikely to be due to the cells transitioning to diplotene , as some de-synapsed chromosomes were completely separated with no evident crossover connections , and some were entangled around other chromosomes . Although interlocks are not a common feature of pachytene cells , it is also possible that there is a subset of cells where interlocks persist through pachytene and the chromosome-wide de-synapsis we see are chromosomes in diplotene . Interestingly though , we never saw a spread nucleus showing a classic diplotene state as seen in other organisms where a complete set of de-synapsed bivalents were held together by one or more chiasmata , suggesting this state in males is transient or full-length Sycp3 axes start to degrade at this stage . Since the sites of crossovers in zebrafish are skewed toward the ends of chromosomes in males [57] , we suspected that co-alignment and synapsis near telomeres might be initiated by local DSBs . We first tested if γH2AX , a biomarker for DSBs , co-localizes with telomeres in sectioned testes and found a sharp polarization of γH2AX staining to one side of the nucleus when chromosomes were in the bouquet and then a more dispersed signal in cells where chromosomes had exited the bouquet ( Fig 6A ) . These results are consistent with a study that showed γH2AX signal clustered with initiation of axis formation marked by Sycp3 [55] . To evaluate the distribution of DSBs at the super-resolution level , we probed spermatocyte nuclear surface spreads with telomere probes and antibodies to Sycp1 and the DSB repair protein Rad51 . Previous work at lower resolution showed that Rad51 foci were primarily found near sites where Sycp3 loading had initiated [6] . Consistent with this finding , and with the γH2AX localization , we found that Rad51 foci were interspersed with the telomere foci in the bouquet cluster ( Fig 6B ) . If DSBs are required for initiating synapsis , then we expected to find that most SC stretches would be associated with a Rad51 focus . This was not the case , however , since there were many instances of SC stretches with no associated Rad51 foci ( Fig 6B , panels 1C-3C ) . We found that 39% ( n = 269 ) of synapsed ends in early zygotene had no associated Rad51 focus . This was surprising given that we also found that synapsis requires Spo11-dependent DSBs ( below ) . Three possible reasons could account for this observation: 1 ) some synapsis may occur independent of DSBs , 2 ) synapsis is initiated at Rad51-associated DSBs but Rad51 signal has been lost due to repair prior to imaging , or 3 ) some synapsis is initiated at Dmc1-associated DSBs that do not co-localize with the Rad51-associated DSBs . The latter is supported by data from Arabidopsis thaliana where Dmc1 and Rad51 DSBs do not colocalize [67] . We found that some cells at pachytene had Rad51 foci and they were located both near the telomeres and in interstitial regions . There are two ways we can envision the interstitial foci could arise: 1 ) All meiotic DSBs form at the same time when the cells are in the bouquet stage , in which case DSBs at interstitial locations would be recruited to the bouquet , or 2 ) breaks continue to form throughout prophase I . Further studies are required to distinguish between these models . Combined , our results show that DSBs are primarily clustered near the telomeres but are also found at interstitial regions during pachytene , which reflects the crossover pattern in zebrafish males [57 , 58] . In order to determine whether synapsis can occur in the absence of Spo11 , which is required for the formation of meiotic DSBs , we created a spo11-/- mutant . The spo11 gene in zebrafish consists of 13 exons encoding a 383-amino acid protein product ( GenBank: AAI65825 . 1 ) with the predicted TP6A_N superfamily domain at 96–157 aa and the predicted TOPRIM superfamily domain at 205–367 aa ( NCBI BLASTP 2 . 8 . 0 ) . We used TALENs targeted to the second exon to introduce an indel mutation by error prone repair . Sequencing of genomic DNA isolated from offspring of founder backcrosses identified an 11 bp deletion resulting in a frameshift mutation in the coding region that predicts a truncated protein of 57 aa lacking both the TP6A_N and TOPRIM domains ( Fig 7A ) . To confirm disruption of Spo11 function in the mutant , we probed whole mount testes of spo11-/- males with antibodies to γH2AX and the germ-cell specific Vasa protein and found that γH2AX clusters were absent in the germ cells , showing that the mutant is deficient for DSB formation ( Fig 7B ) . We next examined evidence of synapsis and pairing in nuclear surface spreads from spo11 mutants . Although Sycp3 loading initiated near the telomeres and elongated inward as in wild type , Sycp1 loading did not follow ( Fig 8A ) . We divided spo11 mutant spermatocytes into the L—L/EZ-like , EZ-LZ-like , and Post-LZ-like categories based on the overall resemblance of Sycp3 loading in the nucleus to equivalent wild-type stages . Post-LZ included pre-pachytene-like or pachytene-like stages . In spo11 mutant spermatocytes , 30 out of 40 cells had no synapsis and the remaining cells had between 1 and 4 short fragments of Sycp1 , which appeared either between two axes , on one axis , or as a lone filament ( Fig 8A , panels 3C-4C ) . These Sycp1 stretches may have been due to self-assembly of Sycp1 filaments [68] . In addition , the bouquet was also maintained . Telomere-proximal co-alignment between chromosomes , however , was disrupted ( Fig 2F ) . Intriguingly , we found an average of ~ 42% of telomeres engaged in associations in the L–L/EZ-like mutant cells as compared to the ~ 31% we see in equivalent stages of wild type ( Fig 8A , panels 1C-5C , Fig 8B; p = 0 . 0389 ) . Unlike in wild type , the telomere associations were maintained at high levels in the mutant throughout prophase I . Several possibilities could account for the loss of telomere associations in wild-type cells . Pairing and synapsis between the ends of homologous chromosomes could physically displace weak associations between non-related chromosome ends . Alternatively , a regulatory feature associated with the transition from leptotene to zygotene could signal loss of a subset of associations , or the reduction of entanglements later in meiosis could allow associations to be disrupted by the physical force of spreading . Any one of these possibilities could account for the persistence of associations in the spo11 mutant . Wild-type cells that were in the EZ/MZ to LZ stages gave a distribution of inter-BAC distances that were overall shorter than those in the L or L/EZ stage ( 0 . 24–3 . 13 μm vs . 9 . 3–25 . 3 μm , p = 0 . 0004 , Fig 8C ) . In the L to L/EZ stages the average length of Sycp3 lines was less than 2 μm while in the later stages , the average length of Sycp3 lines was greater than 2 μm . The sharp decrease in inter-BAC probe distance measurements suggests that pairing at the probed locus occurs shortly after synapsis is initiated . For the spo11 mutant , we staged the nuclei based on Sycp3 axis length since the SC was absent . BAC foci in the spo11 mutants remained at approximately the same distance from each other when the axes were short ( < 2 μm ) or long ( > 2 μm ) ( Fig 8C , S3 Fig ) . In mutant females , synapsis and pairing were also disrupted as was seen in males ( Fig 9 , S3 Fig ) . Together , these data indicate that Spo11 is required for the initiation and/or stabilization of synapsis and homolog juxtaposition in males and females . We found that spo11 mutant males could induce spawning in females but failed to fertilize eggs ( S4 Fig ) , indicating that they were either unable to produce or release their sperm . We inspected spo11 mutant testes using light microscopy and found they appeared more translucent compared to wild type ( Fig 10A , panels 1A and 2A ) , a phenotype that suggested a defect in sperm production . To confirm this , we isolated and stained whole testes with an antibody to the Vasa protein ( Fig 10A , panels 3A-4C ) . In wild-type zebrafish , Vasa is highly expressed in early germ cell clusters but diminishes as the spermatocytes progress in maturity , and is absent in mature spermatozoa clusters which can be identified by their tightly compacted nuclei [69] . We found that the spo11 mutant males lacked sperm , and correspondingly , Vasa was expressed in all cell clusters , though it did diminish compared to the early germ cells . Surprisingly , spo11 mutant females produced similar numbers of fertile eggs as wild type , however , the vast majority of their embryos died before 5 days post fertilization ( dpf ) and displayed a spectrum of abnormalities ( Fig 10B , 10C and 10D ) . We expect that the severe developmental defects displayed among the progeny of spo11 mutant females were a result of aneuploidy since it is unlikely that the chromosomes would be able to segregate properly with gross synapsis and pairing defects . The offspring that were normal at 5 dpf continued to grow into adults that developed as males . A similar offspring phenotype was seen in mlh1 mutants in the zebrafish , where the offspring were shown to be aneuploid , and the ones surviving to adulthood developed as males that were found to be triploid [49] . Together , our data show that despite similar synapsis and pairing defects , males and females display dramatically different reproductive outcomes . This suggests a difference in checkpoint response between the sexes in the zebrafish .
Super-resolution analysis of homologous chromosome synapsis and pairing in the zebrafish revealed a coherent timeline of events ( Fig 11 ) . 1 ) Assembly of the chromosome axis protein , Sycp3 , initiates almost exclusively at both ends of chromosomes and elongates inward . 2 ) DSBs cluster near the telomere region . 3 ) Co-alignments form between telomere-proximal chromosome axes in funnel or pinch configurations . 4 ) The synaptonemal complex protein , Sycp1 , loads between peri-telomeric axes and elongates slightly behind Sycp3 assembly . 5 ) Stable homolog juxtaposition at interstitial loci is not evident until the synaptonemal complex spreads across the region . As meiosis progresses , interlocks between chromosomes can be observed . Throughout the leptotene to pachytene stages telomere associations are present . One of the most striking findings of our analysis was that the key events of meiotic chromosome metabolism , including axis morphogenesis , DSB formation , stable homolog juxtaposition , and synapsis all occurred within the limited region of the nucleus defined by the bouquet . Moreover , the focus of these events was specifically limited to the ends of chromosomes . From a first approximation , the general lack of close , stable homolog juxtaposition at interstitial sites suggests that the two ends of the same chromosome are not distinguished as such . Since zebrafish have 25 pairs of chromosomes , any given end is thus challenged to find its homologous partner among 99 possible choices within the bouquet prior to zygotene . Processes that promote the efficiency of pairing could include time intervals that favor collisions by diffusion [70 , 71] , rapid prophase movement to increase the rate of collisions via attachment of telomeres to cytoskeletal motor proteins outside the nucleus [36 , 40 , 72 , 73] and/or through one or more DSB-independent pairing interactions [2 , 27] . For organisms that initiate synapsis at sites of DSBs , homolog juxtaposition along the lengths of chromosomes can often be detected prior to synapsis ( e . g . Sordaria ) [2] . However , in these organisms a dramatic polarization of DSBs toward the telomere region , like that seen in zebrafish , is not evident . By contrast , DSBs and synapsis initiation in human males and the planarian Schmidtea mediterranea show a polarization similar to zebrafish [13 , 74] . In the planarian , synapsis was shown to drive homolog pairing . It is possible that zebrafish homologs are paired by synapsis as well . A notable difference between the planarian and zebrafish , however , is that the planarian does not require Spo11 for synapsis whereas the zebrafish does , suggesting distinct SC nucleation methods between the two species . Our study does not answer the question of whether interstitial regions are physically juxtaposed by “zippering up” as SC spreads , or if a wave of DSBs creates new synapsis initiation sites and/or stabilizes SC . Interestingly , in zebrafish , the bouquet is also the organizing center of the Balbiani body ( Bb ) , a collection of embryonic patterning factors , mitochondria , and organelles which defines the animal-vegetal axis of the oocyte and is found in a wide variety of organisms including Drosophila , Xenopus , and mouse [75 , 76] . In zebrafish , disruption of the bouquet ex vivo by the addition of the microtubule inhibitor nocodazole also disrupts Bb precursors showing the two structures are mechanistically linked [77] . It will be interesting to test if other meiotic chromosome features are also linked to the Bb , or if the Bb contributes to meiotic progression . Our work uncovered several features of zebrafish biology that can stimulate new lines of enquiry to understand meiotic chromosome dynamics . First , nonhomologous telomere associations were prominent throughout meiosis , yet the nature of these associations is not well understood . One possibility is that they represent associations between heterochromatic regions like those seen in crickets [45] , or telomere-bound protein interactions , as has been proposed for Trf1 [46] . We also do not know if they represent interactions between the same chromosomes from cell to cell . Associations could represent an early phase of the pairing process where the bouquet facilitates interactions between all telomeres , and rapid chromosome movements act to disrupt weak nonhomologous interactions to favor stronger DSB-dependent homologous interactions [32 , 33 , 36] . In addition , it is unknown what structure at or near the telomere seeds the initial loading of Sycp3 , or the significance of the Sycp3 “bridges” sometimes seen between nonhomologous telomeres . Second , our results show that Spo11 is required for the co-alignment of axes and SC formation . We attribute this effect to the formation of DSBs by Spo11 since the earliest occurrences of Rad51 and γH2AX signals are skewed toward telomeres where co-alignment and SC first appear . Observing Rad51 foci and γH2AX staining first near telomeres and later at interstitial locations suggests that DSBs may form in a wave , where initial breaks near telomeres bring homologs together to initiate local synapsis , while subsequent breaks form as Sycp3 is progressively loaded to initiate and/or to stabilize SC elongation . Consistent with the latter model , we occasionally see more than one synapsis initiation site between two chromosomes , albeit close to the telomere . A previous study showed that RPA foci , known to mark intermediates of DNA replication and DSB repair , form lines along the elongating axis in the zebrafish [56] . It is not known , however , if these are a result of DNA replication or Spo11-dependent recombination intermediates . Another possibility is that one or a few DSBs near the telomere are sufficient to promote synapsis along the length of a chromosome . The kinetic relationship between Sycp3 loading and Spo11-dependent SC initiation and elongation points to a possible regulatory mechanism that couples these processes . A study in the medaka fish , Oryzias latipes , has shown that loading of Sycp3 and Sycp1 is polarized to one side of the leptotene nucleus , with Sycp3 lines appearing to slightly anticipate Sycp1 [78] . This suggests that the mechanism of Sycp3 loading and synapsis in zebrafish may be common to other fishes . Third , a transient interlock stage suggests a robust resolution mechanism . Interestingly , in cells where interlocks are observed , we also see pairs of chromosomes separated by long stretches of de-synapsed regions , sometimes disjoining two chromosomes completely . One possibility is that zebrafish employ long-range chromosome de-synapsis to resolve chromosome interlocks , as has previously been suggested in other organisms [62 , 66] . It is possible that late-forming interstitial DSBs may play a role in re-establishing homologous synapsis at pachytene following this method of interlock resolution . In budding yeast , mouse , and C . elegans , SC components are involved in downregulation of DSB formation [7] , thus it seems possible that local de-synapsis could activate new DSB formation . Fourth , our analysis shows that synapsis initiates near the telomeres and progresses inward in both males and females , despite the differences in Mlh1 distribution and the recombination landscape between the two sexes [57 , 58] . In mammals , the SC nucleation and crossover distribution landscapes correlate and are sex-specific ( mouse , human , cattle ) [20 , 27–30] . In zebrafish , it is possible that the relationship between SC nucleation and crossover designation differs between the sexes , given that in males the SC nucleation pattern resembles the crossover pattern whereas in the females it does not appear to . Zebrafish is not only an excellent model to study the events of meiosis per se , but also to study sexually dimorphic responses to meiotic perturbations . Zebrafish has previously been proposed as a model for germ cell aneuploidy [50 , 79] . We show here that despite exhibiting similar defects in synapsis and pairing , spo11 mutant males and females show vastly different outcomes in reproduction . The males are unable to produce sperm , while females produce eggs that result in severely deformed offspring . This is in line with previous studies that show sexually dimorphic outcomes: Disruptions of Mlh1 [49 , 51] , and Mps1 , a kinase required for the spindle assembly checkpoint [50] , show a tendency for females to produce aneuploid offspring . Unlike in spo11 mutants , where males are sterile , and mlh1 mutants , where males are predominantly sterile , both male and female mps1 mutants produce aneuploid offspring , although the rate is higher in females than males ( ~46% vs . ~26% respectively ) . This suggests complex mechanisms underlying causes of increased aneuploidy in zebrafish females . Sex specific differences are also seen in spo11 mutant mice; spermatocytes die by early pachytene whereas oocytes survive until diplotene/dictyate stage [80 , 81] . The arrest seen in mouse males , however , is likely different than the arrest seen in zebrafish . Among organisms with heterogametic sex determination , mechanisms have evolved to specifically accommodate unpaired chromosomes in the heterogametic sex , including meiotic sex chromosome inactivation ( MSCI ) [82 , 83] . As such , mutations that disrupt pairing might be expected to have a weaker effect in the homogametic sex , where the MSCI checkpoint may not be as robust [84] . In domesticated zebrafish , sex determination is polygenic , with no universal structural differences between chromosome sets of sexes in lab strains [58 , 85] . Consistent with these findings , we did not observe any chromosomal regions that remained unpaired during pachytene . Thus , the pronounced effect of the spo11 mutation in males is likely not due to the activation of the MSCI checkpoint . Instead , the failure to produce sperm may depend on another checkpoint , such as the synapsis or the spindle assembly checkpoints , that operate in other model systems [1 , 86–89] . Our findings highlight the importance of studying multiple model systems . While homolog pairing and recombination are considered universal features of meiosis , the means to getting there is quite varied among species . Interestingly , some meiotic prophase events in zebrafish resemble the corresponding events in human spermatogenesis , including the tendency of DSBs to skew near the ends of chromosomes and the initiation of synapsis at telomeres followed by inward synaptic progression [74 , 90] . Telomere-proximal synapsis initiation while Sycp3 loading is not yet complete has also been reported in human spermatocytes [19 , 20] . However , in humans the Sycp3 loading appears more extensive than in the fish by the time that synapsis ensues . Understanding spermatogenesis is important since sperm concentration and total sperm count has declined 50–60% between 1973 and 2011 among men in western countries [91] , and the causes behind male infertility remain unknown in about 40% of patients [92] . In addition , human females are more prone to generating aneuploidy as compared to males [1 , 93–95] , which resembles the situation in zebrafish . While the causes of aneuploidy and reduced fertility in humans are complex and the contributions are manifold , zebrafish could provide valuable insights into environmental , genetic , and sex-specific effects on adverse meiotic outcomes .
The UC Davis Institutional Animal Care and Use Committee ( IACUC ) has approved of this work under the protocol #20199; For noninvasive procedures ( e . g . fin clips for genotyping ) , zebrafish were anesthetized using tricaine . Invasive surgical methods were performed on fish euthanized by submerging fish in ice water . The wild type AB strain was used in the production of spo11 mutants . Wild type data presented in Figs 1–5 and 10 are from tank mates of spo11 mutants . AB strain fish were used for Fig 6A , and NHGRI strain fish were used for Fig 6B . NHGRI strain fish were used for test crosses in one of the two pooled data sets in Fig 10 . Other test crosses were done with AB strain fish . Fish were maintained as previously described [96] . Spo11 mutants were generated using TALENs targeting the second exon of spo11 . The TALENs were assembled and injected as previously described [97] . The TALEN sequences were: HD-NG-NI-NI-NI-NN-NN-NG-NN-NI-NI-NN-HD-NI-HD-half repeat HD , and NG-HD-HD-NI-NN-HD-NI-NN-NN-NI-NG-HD-NG-NI-NG-half repeat NG . Injected founder fish were raised to adulthood and outcrossed to wild type fish; the resulting offspring were screened for mutations in spo11 via high resolution melt ( HRM ) analysis and subsequent sequencing . HRM primer sequences are: fwd TCACAGCCAGGATGTTTTGA , and rev CACCTGACATTGTTCCAGCA . The HRM analysis was performed with either Light Scanner Master Mix ( BioFire Defence , Murray , UT , Catalog# HRLS-ASY-0003 ) , 10X LCGreen Plus+ Melting Dye ( Biofire Defence , Catalog# BCHM-ASY-0005 ) , or 20X Eva Green dye ( VWR , Radnor , PA , Catalog# 89138–982 ) using a CFX-96 real-time PCR machine and Precision Melt Analysis software ( BioRad , Hercules , CA ) . The data presented in this paper is from individuals of a population with an 11 bp deletion mutation in exon 2 that has been outcrossed 2–3 times . All our conclusions are based on experiments that were performed at least two times . All data sets comparing WT and spo11 mutants were collected from tank mates processed in parallel on the same days , including the spreads and staining the slides . The antibodies , the BAC probe and the Telomere PNA probes were tested multiple times on spreads and/or whole-mount gonads prepared on different days . The Student t-test was used for statistical analysis . All numerical data used for each plot is tabulated in S1 Table . Raw SIM data for all cells are available upon request . Images shown in each figure will be deposited at the Dryad Digital Repository ( https://datadryad . org/ ) . About 15–20 gonads were freshly dissected in 1X Phosphate Buffered Saline ( PBS ) . The gonads were placed in 2 ml Dulbecco’s Modified Eagle Medium ( DMEM ) in a 5 ml Eppendorf tube on ice . 4 mg of collagenase ( Sigma-Aldrich Chemical Co Inc , St . Louis , MO , Catalog# C0130-500MG ) dissolved in 200 μl DMEM were added and the gonads were gently shaken horizontally at 32°C for 50 minutes to an hour , until the liquid was cloudy , and the gonads were in small chunks . The tube was inverted rapidly several times every 10 minutes to facilitate dissociation . The collagenase was then washed out: DMEM was added up to 5 ml and the gonads were pelleted at 218g for 3 minutes . Then 3 ml of the supernatant were removed to reduce the liquid down to 2 ml . This was repeated 2 additional times for a total of 3 DMEM washes with the supernatant reduced to 1 ml after the last wash ( the pellet was not resuspended between the washes ) . DMEM was added up to 2 ml total , and 1 . 4 mg trypsin ( Worthington Biochemical Corporation , Lakewood , NJ , Catalog# LS003708 ) dissolved in 200 μl DMEM and 20 μl of 400 μg/ml DNaseI ( Roche Diagnostics , Pleasanton , CA , Catalog# 10104159001 ) were added for cell dissociation . The tube was gently shaken horizontally at 32°C for 5–15 minutes until the solution contained few clumps . The tube was inverted rapidly several times every 5 minutes to facilitate dissociation . 10 mg of trypsin inhibitor powder ( VWR , Catalog# IC100612 . 5 ) dissolved in 500 μl DMEM and 50 μl of 400 μg/ml DNase I solution were then added . The tube was briefly spun down , and the cell suspension was pipetted repeatedly up and down with Pasteur pipettes for 2 minutes to facilitate dissociation of any remaining clumps . The cell suspension was put through a 100 μm nylon Falcon filter ( Fisher Scientific , Waltham , MA , Catalog# 08-771-19 ) and transferred to a fresh 5 ml tube . DMEM was added to 5 ml total volume and the cells were pelleted at 218g for 5 minutes . The supernatant was removed and 5 μl of the DNase I solution was added directly to the pellet which was then resuspended by scraping the bottom of the tube on an empty tube rack . DMEM was added up to 5 ml and the cells were pelleted at 218g for 2 minutes . The DNase I treatment was repeated a total of 2–4 times until the resuspended pellet did not clump upon addition of DMEM . After the last treatment , the pellet was resuspended in 1–2 ml of 1X PBS and pelleted again at 218g for 5 minutes . The supernatant was removed and the pellet resuspended with a pipette tip ( ~3 mm cut off from tip to widen the aperture ) in 80–100 μl of 37°C 0 . 1M pH ~8 sucrose , and allowed to sit at room temperature for 3–5 minutes . Slides ( Fisher Scientific Premium Superfrost , Catalog# 12-544-7 ) were coated with 100 μl of 1% Paraformaldehyde ( PFA; Acros Organics , Catalog# 30525-89-4 ) with 0 . 15% Triton X-100 ( Fisher BioReagents , Catalog# 9002-93-1 ) and then ~20 μl of cell suspension was added directly to the center of the slide in a straight line . The slide was tilted to facilitate spreading . The slides were placed in a slightly cracked open flat humid chamber . The chamber was placed in a dark drawer and allowed to sit overnight . It was then opened , and the slides allowed to completely dry . The slides were rinsed for 5 minutes in H2O and then twice for 5 minutes in 1:250 Photo-Flo 200 ( Electron Microscopy Sciences , Catalog# 74257 ) in Coplin jars . The slides were dried and stored at -20°C until they were stained . About 6–10 gonads of females aged 60–80 dpf were dissected in 1X PBS . The gonads were placed in 2 ml DMEM in a 5-ml tube and passed through an 18-gauge needle and then a 20-gauge needle 15 times each . The cells were briefly spun down and then pipetted up and down with Pasteur pipettes for 2 minutes . The cell suspension was put through a 100 μm nylon Falcon filter and transferred to a clean 5 ml tube . The cells were then pelleted at 218g for 5 min . The pellet was composed of two layers , a bottom whitish layer and a top yellowish layer . The top layer was carefully removed with pipette and the remaining bottom layer was resuspended in 2 ml 1X PBS . The cells were then pelleted at 218g for 5 min , the supernatant was removed , and the pellet was resuspended with cut pipette tip in 80–100 μl 37°C 0 . 1M pH ~8 sucrose . The suspension was allowed to sit at room temperature for 3–5 minutes . The slides were prepared as in the “Adult testes chromosome spreads” protocol . PNA telomere probes TelC-Alexa647 and TelC-Cy3 were acquired from PNA Bio Inc , Thousand Oaks , CA ( Catalog# F1013 and F1002 respectively ) ; 50 μM stocks were prepared in formamide as per manufacturer’s instructions and stored at -80°C . The hybridization solution was prepared to a final concentration of 0 . 2 μM PNA telomere probe and 1 . 33 mg/ml bovine serum albumin ( Fisher Scientific ) in pre-hybridization solution . The pre-hybridization solution was composed of 50% formamide ( Fisher Scientific , Catalog# BP228-100 ) , 5X Saline-Sodium Citrate ( SSC; 20X stock: 3M NaCl and 0 . 3M Sodium Citrate ) , 50 μg/ml Heparin sodium salt from porcine intestinal mucosa ( Sigma-Aldrich Chemical Co Inc , Catalog# H3393-100KU ) , 500 μg/ml transfer RNA from wheat germ ( Sigma-Aldrich Chemical Co Inc , Catalog# R7876-2 . 5KU ) , 0 . 1% Tween 20 ( Bio-rad , Catalog# 170–6531 ) , and 1M Citric acid to bring the solution to pH ~6 . The pre-hybridization and hybridization solutions were stored in -20°C in the dark . BAC clone CH211-31P3 ( https://zfin . org/ZDB-BAC-050218-850 ) was obtained from the BACPAC Resources Center ( BPRC ) . The BAC was purified via Midiprep as previously described [98] . Purified BAC quality was assessed by running a sample on a 1% agarose gel , and the BAC’s identity was confirmed by PCR amplification of a segment of the nanos2 gene using the following primers: fwd ATGCAGTCCGAGAGTCAGCAGAG , and rev ATAACGGACACACGTAGCTCCTCAG . The Cot-1 preparation was adapted from [98] . Salmon testes DNA ( Sigma-Aldrich , Catalog# D1626-1G ) was prepared at 10 mg/ml in H2O by dissolving overnight at 55°C . 300 μl aliquots of the testes DNA were sonicated in Diagenode tubes ( Fisher Scientific , Catalog# NC0065146 ) in a Diagenode Bioruptor UCD-300 for ~60 15-second cycles or until the average fragment size was ~400–500 bp . The fragment size was checked on a 1% agarose gel . 500 μl of sonicated salmon testes DNA was denatured at ~100°C for 15 minutes and then incubated at 65°C for 4 minutes . 250 μl of 1M NaCl ( pre-heated to 65°C ) was added and the mix was incubated at 65°C for the duration of time needed for the Cot-1 fraction to re-anneal ( equation: 5 . 92/DNA concentration in mg/ml = time ( in minutes ) ) . Then 1 unit of S1 nuclease ( Thermo Fisher Scientific , Catalog# EN0321 ) per 1 μg of DNA was added together with 5X S1 nuclease reaction buffer . The mixture was incubated at 37°C for 30 minutes . The Cot-1 solution was transferred to a 15 ml conical tube , mixed with 10 ml of pH 8 Phenol:Chloroform:Isoamyl alcohol 25:24:1 ( Fisher Scientific , Catalog# BP1752-100 ) and centrifuged at 1500g for 5 minutes . The aqueous phase was transferred to a new 15 ml tube and mixed thoroughly with 0 . 1X volume of 3M sodium acetate . 1X volume of 100% isopropanol was added , the solution mixed gently to precipitate the DNA , and then centrifuged at 3000g for 10 minutes at 4°C . The supernatant was removed , and the pellet was allowed to air dry with the tube inverted at an angle . The pellet was re-hydrated in 30 μl H2O and the concentration was determined by nanodrop . The pellet was further cleaned with 1 ml Phenol:Chloroform:Isoamyl alcohol 25:24:1 followed by 70% EtOH . The final pellet was dried and resuspended in 30 μl H2O and the concentration was determined by nanodrop . The BAC probe labeling and preparation was adapted from [98] . The probe was labelled with Green dUTP ( Abbott Molecular , Abbott Park , IL , Catalog# 02N32-050 ) using the Nick Translation Kit ( Abbott Molecular , Catalog# 07J00-001 ) . 14 μl of the purified BAC was mixed with 23 . 4 μl of 0 . 1 mM dNTP mix ( 1:2:2:2 of dTTP:dATP:dCTP:dGTP ) , 10 μl of 10X Nick translation buffer , 10 μl of the Nick translation enzyme mix , 12 μl of 0 . 2 mM Green dUTP , and H2O to bring up the volume to 100 μl . The reaction was incubated in a thermocycler at 15°C for 16 hours , heated to 70°C for 10 minutes , and then held at 4°C . The labeled BAC was purified using DNA Clean & Concentrator-5 ( Zymo Research , Irvine , CA , Catalog# D4013 ) in 50 μl batches and eluted in 10 μl of the elution buffer . 25 μg of salmon sperm Cot-1 was added per batch and the batches were mixed together . The mixture was vacuum dried , and the pellet was resuspended in 10 μl of LSI buffer ( LSI/WCP Hybridization Buffer , Abbott Molecular , Catalog# 06J67-011 ) to make the stock BAC probe mix . The stock was stored in the dark at -20°C . For staining , the stock was further diluted in LSI buffer at a 1:19 stock:LSI ratio . The BAC probe staining procedure was adapted from [98] . Chromosome spread slides were placed in 3:1 MeOH:HAc at -20°C for 15 minutes . The slides were then washed 2 times in 1X PBS for a minimum of 2 minutes each and treated with 0 . 5 mg/ml Protease II ( Abbott Molecular Inc . , Catalog# 06J93-001 ) at 37°C for 5 minutes . The slides were washed 2 times in 1X PBS for a minimum of 5 minutes each , and then progressively dehydrated in 2-minute washes with 70% , 85% , and 100% EtOH . The slides were allowed to air dry completely and used immediately for staining . Prior to BAC probe staining , PNA telomere probe staining was performed as described in the “PNA telomere probe staining” section , and the slides were allowed to air dry completely after the final 1X PBS wash . At this point , 10 μl of the BAC probe ( 1:19 dilution in LSI buffer ) was added per slide , covered with a 24 x 50 coverslip , and sealed with rubber cement ( Elmer’s , Atlanta , GA , Catalog# E904 ) . The slides were heated in a hybridization oven at ~70–71°C for 3 minutes and then the oven temperature was allowed to drop to ~50°C after which the slides were transferred to a flat , humid chamber and incubated at 37°C overnight in the dark . The coverslip was peeled off and the slides were washed in coplin jars in 1 ) 50% formamide in 2X SSC at 45°C , 2 times for 5 minutes each , 2 ) 2X SSC at 45°C , 2 times for 5 minutes each , 3 ) 4X SSC + 0 . 05% Tween 20 for 8 minutes , 4 ) 1:1 2X SSC:PBSTw ( 1X PBS + 0 . 1% Tween 20 ) at room temperature ( RT ) for 5 minutes , and 5 ) PBSTw at RT , 3 times for 5 minutes . Excess PBSTw was removed from the slides by tapping their sides on a paper towel . The antibody staining and slide mounting were performed as described in the “Primary antibody staining” and “Secondary antibody staining” sections , with PBSTw used instead of PBT . All images were collected at the Department of Molecular and Cellular Biology Light Microscopy Imaging Facility at UC Davis . Chromosome spreads were imaged using the Nikon N-SIM Super-Resolution microscope in 3D-SIM imaging mode with Apo TIRF 100X oil lens . The images were collected and reconstructed using the NIS-Elements Imaging Software . Sections and fluorescent whole mounts were imaged using the Olympus FV1000 laser scanning confocal microscope . Images were processed using the Fiji ImageJ software . Only linear modifications to brightness and contrast of whole image were applied . All raw image files are available upon request . To analyze fertility , individual mutant fish were crossed to wild type fish to assess their ability to generate offspring . Offspring that were produced were tracked daily for up to 5 days to assess morbidity and mortality . A cDNA fragment of zebrafish ddx4/vasa encoding the COOH-terminal amino acids 479–651 ( based on accession number BC129275 ) was cloned into pET100 using the following primers: fwd 5’- CACCATGTTCATAGCAACATTTCTCTGTCAAG-3’ ( ATG initiation codon added ) ; rev 5’- TAACAGGTGTGAGGCCAGTTATTCC-3’ . The His-tagged protein was expressed in E . coli , purified using standard procedures and used to immunize chicken hens ( 91-day protocol , Pocono Rabbit Farm & Laboratory Inc . Canadensis , PA ) . Polyclonal IgY from crude serum was used at 1:500 . An N-terminal fragment of Sycp1 cDNA was amplified with Phusion DNA polymerase ( Thermo Fisher Scientific , Catalog#: M0530L ) using the following primers: Fwd 5’-aactttaagaaggagatataccATGCAAAAAGCATTCAACTT-3’ , and Rev 5’-tctcagtggtggtggtggtggtgctcGGTAACTTCTATTTCTGCATtt-3’ . The Sycp1 PCR product ( 1272 bp ) was then cloned into pET28b using NEBuilder HiFi DNA Assembly Master Mix ( NEB , Ipswich , MA , Catalog#: E5520S ) . BL21 ( DE3 ) cells containing pRARE and Sycp1 overexpression construct were grown in 2 . 6 L of LB with kanamycin and chloramphenicol until an OD600 = 1 and induced with a final concentration of 1 mM IPTG at room temperature for six hours . The Sycp1 peptide was purified under denaturing conditions using Novagen NiNTA purification resins ( Sigma , Catalog#: 70666 ) according to the manufacturer’s instructions . The Sycp1 peptide was concentrated to a final concentration of 1mg/ml in PBS using a 10kDa centrifugal filter ( Sigma , Catalog# UFC901008 ) . The Sycp1 peptide was injected into two chickens by Pocono Rabbit Farm and Laboratory following the 91-day polyclonal antibody production protocol . | Inherent to reproduction is the transmission of genetic information from one generation to the next . In sexually reproducing organisms , each parent contributes an equal amount of genetic information , packaged in chromosomes , to the offspring . Diploid organisms , like humans , have two copies of every chromosome , while their haploid gametes ( e . g . eggs and sperm ) have only one . This reduction in ploidy depends on the segregation of chromosomes during meiosis , resulting in gametes with one copy of each chromosome . Missegregation of the chromosomes in the parents leads to abnormal chromosome numbers in the offspring , which is usually lethal or has detrimental developmental effects . While it has been known for over a century that homologous chromosomes pair and recombine to facilitate proper segregation , how homologs find their partners has remained elusive . A structure that has been central to the discussion of homolog pairing is the bouquet , or the dynamic clustering of telomeres during early stages of meiosis . Here we use zebrafish to show that the telomere bouquet is the site where key events leading to homologous chromosome pairing are coordinated . Furthermore , we show that deletion of spo11 , a gene required for proper recombination in most studied organisms , resulted in very different effects in males and females where males were sterile while females produced deformed progeny . | [
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] | 2019 | The telomere bouquet is a hub where meiotic double-strand breaks, synapsis, and stable homolog juxtaposition are coordinated in the zebrafish, Danio rerio |
Stem cell dynamics in vivo are often being studied by lineage tracing methods . Our laboratory has previously developed a retrospective method for reconstructing cell lineage trees from somatic mutations accumulated in microsatellites . This method was applied here to explore different aspects of stem cell dynamics in the mouse colon without the use of stem cell markers . We first demonstrated the reliability of our method for the study of stem cells by confirming previously established facts , and then we addressed open questions . Our findings confirmed that colon crypts are monoclonal and that , throughout adulthood , the process of monoclonal conversion plays a major role in the maintenance of crypts . The absence of immortal strand mechanism in crypts stem cells was validated by the age-dependent accumulation of microsatellite mutations . In addition , we confirmed the positive correlation between physical and lineage proximity of crypts , by showing that the colon is separated into small domains that share a common ancestor . We gained new data demonstrating that colon epithelium is clustered separately from hematopoietic and other cell types , indicating that the colon is constituted of few progenitors and ruling out significant renewal of colonic epithelium from hematopoietic cells during adulthood . Overall , our study demonstrates the reliability of cell lineage reconstruction for the study of stem cell dynamics , and it further addresses open questions in colon stem cells . In addition , this method can be applied to study stem cell dynamics in other systems .
Mammalian stem cells and tissue dynamics in vivo are presently studied by lineage tracing methods [1] , [2] , which are dependent on the presence of specific stem cell markers [2] . These methods require generation of transgenic animals , development of sophisticated imaging modalities , and are contingent on the availability of stem cells in a specific tissue [2] , [3] . Our laboratory developed a method that utilizes somatic microsatellite ( MS ) mutations for reconstructing cell lineage trees [4]–[7] . This retrospective method , which was also applied by others [8]–[11] , is based on the notion that somatic mutations accumulated during normal cell divisions endow each cell of the body with a genomic signature that , with very high probability , is unique [4] . The distances between the genomic signatures of different cells , as measured using various mathematical methods [12] , can then be used to reconstruct the organism's cell lineage tree . In this application of our method , the cellular genomic signature is derived from a set of MS loci in mismatch-repair ( MMR ) deficient mice ( Mlh1−/− ) . The distance measure used is Maximum Likelihood estimator ( Materials and Methods ) . The MS mutation rate of these mice is much higher than that of wild type , thus increasing the precision of the cell lineage analysis . These mice exhibit normal morphology , but are infertile and develop cancer spontaneously [13] . Up to now , our method was validated using ex-vivo cell lineage trees [4] and applied to the lineage analysis of cells of a mouse with a tumor [5] . In addition , it was employed to estimate the number of cell divisions since the zygote , defined as cell depth [6] . The first aim of the present study was to validate the suitability of our method for the study of stem cell and tissue dynamics . We focused on the intestinal epithelium , since its stem cells were intensively studied by various tracing methods that clarified many aspects of their dynamics [2] , [14]–[21] . One such aspect , termed ‘monoclonal conversion’ , is a process by which intestinal crypts that originate at birth from more than one stem cell , drift toward monoclonality two weeks after birth [22]–[25] . Monoclonal conversion was found to be sustained during mouse life , which means that every few weeks a single stem cell becomes the ancestor of all the cells in the crypt [2] , [20] , [22]–[27] . Another aspect is the fact that intestinal crypt stem cells do not incorporate an immortal strand [2] , [20] , [21] . According to the immortal strand hypothesis , stem cells retain the older DNA strand during asymmetric cell divisions and relegate the newly synthesized DNA strand to the differentiated cell , thus avoiding inheritance of mutations caused by DNA replication [28]–[36] . This mechanism was shown to be present in neural stem cells [30] . Other studies suggest its presence in the intestine epithelium stem cells [34] , [35] . Most recently , it was shown that there is no asymmetric segregation of DNA within intestinal epithelial stem cells [2] , [20] , [21] , thus making the existence of the immortal strand mechanism , in this system unlikely . However , since this evidence is based on a specific stem cell marker , we still found an additional value in addressing this issue in the intestinal epithelium using our method . Another known result confirmed by our method is the correlation between physical location of crypts and their lineage proximity [37] . Our cell lineage analysis method was applied in the current study not only to validate known results but also to address open questions . Up to date , it was unclear whether during embryogenesis the colon is formed by its own specific progenitors or by cells that are also progenitors of other lineages . In addition , it is well established that during embryogenesis , intestine epithelium cells originate from a lineage different from that of bone marrow cells . However , during adulthood , bone marrow cells were shown to have the capacity to repopulate the gastrointestinal epithelium [38] , [39] , suggesting that both lineages may interact . Since some doubts were raised regarding the robustness of this process and its relevance to normal physiology [40] , we employed cell lineage analysis in the adult mouse to explore clonal relationships between the intestinal epithelium and other lineages , such as the hematopoietic lineage . In order to examine these issues , we applied our method to cells sampled from colonic crypts and other cell types from Mlh1−/− mice at different ages . Our results confirm that ‘monoclonal conversion’ takes place and that intestinal epithelium stem cells do not incorporate an immortal strand . We also confirmed the positive correlation between physical proximity and lineage in colon crypts , and revealed that colon crypts are clustered separately from B-lymphocytes , pancreatic cells ( beta and duct cells ) and hematopoietic stem cells from the bone marrow . Our findings indicate that the colon is constituted by a few distinct progenitors and that there is no evidence for hematopoietic renewal of the intestinal epithelium during adulthood .
Our method was first used to confirm that monoclonal conversion occurs in crypt stem cells , and that these cells do not incorporate an immortal strand . Although these facts were already demonstrated by previous studies , deriving this information also from reconstructed cell lineage trees both strengthens these results and establishes the reliability of our method . This validation of our method is followed by the use of the lineage tree reconstruction to generate new information about crypt stem cells . In population genetics , the most recent common ancestor ( MRCA ) of any set of organisms is the most recent individual from which all organisms in the group are direct descendants . Similarly , we refer to the cell that is the most recent ancestor of all cells in a crypt ( stem cells and others ) as the crypt's most recent common stem cell ( MRCSC ) . We employ two methods to estimate crypt's MRCSC . One is genotyping the DNA extracted from the entire crypt ( all cells in the crypt ) , considering that the average DNA of all crypt cells is a good approximation of the DNA of the crypt's MRCSC [4] ( Figure 1A and Figure S1 ) . Another method utilizes the cell lineage tree reconstructed from DNA extracted from individual cells isolated from a single crypt and refers to the most recent common ancestor node on the tree as the computational MRCSC of the crypt ( Figure 1B , blue square ) . Knowing the topology of the reconstructed cell lineage trees can help understand the history and dynamics of crypt stem cells , as illustrated by Figure 2 . The top of the figure presents the hypothetical reconstructed lineage tree of crypt cells and whole crypts sampled from a young mouse . It is well established that young mouse crypts are monoclonal [2] , [20] , [23]–[25] , therefore , in this tree individual cells randomly isolated from two crypts are separately clustered on the lineage tree ( red and green nodes , Figure 2A ) . In this young mouse the latest monoclonal conversion event in a crypt must have occurred only a few cell divisions earlier [2] , [20] , [24] , therefore individual crypt cells are only slightly deeper than their computed MRCSCs . The trees at the bottom panel of Figure 2 that were qualitatively drawn by us , represent different hypothetical scenarios as the mouse gets older; to illustrate how different biological scenarios may give rise to different cell lineage trees and , conversely , that a biological scenario can be inferred from the structure of the cell lineage tree . According to the first scenario ( Figure 2B ) , crypt stem cells retain an immortal strand [30] , [32]–[36] . In that case , they do not accumulate mutations during cell divisions and therefore the depth ( number of cell divisions since the zygote ) of crypt MRCSCs , depicted as blue nodes , and the depth of computed MRCSCs ( blue squares ) do not increase with mouse age . Due to the constant depth of crypt MRCSCs , the depth of crypt cells ( red and green nodes ) does not change with mouse age . According to the second hypothetical scenario ( Figure 2C ) , crypt stem cells do not retain an immortal strand . Thus , these stem cells accumulate MS mutations with mouse age . In addition , crypt stem cells undergo monoclonal conversions only once during their lifetime ( 2 weeks after birth ) , and maintain the crypt during growth and adulthood solely due to asymmetric divisions . Therefore , although crypt stem cells underwent many cell divisions and accumulated numerous MS mutations , they are all descendants of the original ancestor ( crypt MRCSC ) that constituted the crypt when it was young . In the resulting cell lineage tree , crypt MRCSCs ( blue nodes ) and computed MRCSCs ( blue squares ) do not get deeper with mouse age . However , individual crypt cells ( red and green nodes ) do get deeper with mouse age since the stem cells that maintain the crypt accumulate somatic mutations during asymmetric cell division . According to the third scenario ( Figure 2D ) , crypt stem cells do not retain an immortal strand either , but they undergo symmetric cell divisions that lead to constant monoclonal conversions throughout adulthood [2] , [20] , [23]–[25] . Thus in the cell lineage tree , similarly to the second scenario ( Figure 2C ) , crypt cells ( red and green nodes ) , do get deeper with mouse age due to the accumulation of MS mutations in crypt stem cells . However , unlike the second scenario , crypt MRCSCs ( blue nodes ) and computed crypt MRCSCs ( blue squares ) increase dramatically with mouse age , since , over time , crypt monoclonal conversion causes each crypt to become the progeny of a single , fairly recent , stem cell . Recent data support this third scenario [2] , [20] , [21] . Our method was applied to decipher which of the above hypothetical scenarios holds . For this purpose , whole colon crypts as well as individual crypt cells were isolated by tissue digestion from young and old mice ( 52 and 340 day-old ) . On the reconstructed cell lineage tree , single cells are represented as red and green nodes , whole crypts as blue nodes and computed crypt MRCSCs as blue squares ( Figure 1 and Figure 3 ) . We noted that the lineage tree reconstructed from an old mouse agreed with the third hypothetical scenario ( Figure 2D ) , indicating that crypt stem cells do not retain an immortal strand but do undergo constant symmetric cell divisions throughout adulthood leading to monoclonal conversions . For a deeper analysis of the resulting cell lineage trees , several parameters were examined quantitatively . This analysis revealed that in both young and old mice , individual cells randomly isolated from the same crypt were significantly clustered separately from all other cells ( p<10−7 for both red and green crypts of the young mouse , p<10−5 for the green crypt of the old mouse , and p = 0 . 0006 for the red crypt of the old mouse , Figure 3A and 3B ) . In addition , since MS mutations occur randomly and independently during cell division , and since there is great similarity between the genomic signatures of individual cells isolated from the same crypt , we conclude that each analyzed crypt is monoclonal with very high probability . We further examined the depth of whole crypts and single cells isolated from different crypts , assuming that the average mutation rate of MS in our system is about 1 to 100 cell divisions . This estimation is based on the already known division rate of crypt stem cells ( Materials and Methods ) . Our analysis revealed that the depth of colon whole crypts increases significantly and linearly ( r2 = 0 . 99 ) with mouse age ( Figure 3C ) . The median depth of whole crypts ( blue nodes ) at 52 , 199 , and 340 days is 128±4 , 284±18 , and 377±20 cell divisions , respectively . This total increase of about 250 cell divisions during 288 days is very close to the estimation in the literature [2] . In addition , we found that individual crypt cells become significantly deeper with mouse age ( Kolmogorov-Smirnov , p<10−5 ) , from 148±7 cell divisions in 52 day-old mouse to 478±19 cell divisions in 340 day-old mouse ( Figure S2 ) . Since the increase in depth with mouse age demonstrates that crypt stem cells accumulate MS mutations , these findings rule out the presence of an immortal strand . We define the depth of a crypt cell relative to the crypt's MRCSC to be the number of cell divisions that separate the cell from the crypt's MRCSC . We measured the depth of randomly sampled individual crypt cells ( Figure 3A , red and green nodes ) relative to their computed MRCSCs ( blue squares ) and found no statistically significant difference in this relative depth between young and old mice ( Figure 3 and Figure S3 ) . The fact that the number of cell divisions that occur in crypt cells since their MRCSCs is independent of mouse age confirms that monoclonal conversion occurs at the same rate independently of mouse age . Moreover , most crypt cells have a depth of about 45 cell divisions relative to their computed MRCSCs ( Figure S3 ) , which is very close to the published data [2] . Lastly , the average branch length between whole crypts ( blue nodes ) to the MRCA of whole crypts was examined . We found that this length significantly increases with mouse age , from an average length of 56±3 to 191±23 cell divisions in 52 and 340 day-old mice , respectively ( Figure 3A and 3B , Kolmogorov-Smirnov p<10−5 ) . This finding indicates that each crypt underwent an independent cell division process in the colon . In order to confirm that the depth of computed crypt MRCSCs of individual cells from the same crypt ( blue squares ) is reliable , we examined whether it is similar to the depth of whole crypts ( blue nodes ) . Our data show that these depths do not differ significantly . Specifically , the range of depths of whole crypts in the 52 day-old mouse was from 78 to 164 cell divisions , and that of the computed crypt MRCSCs of cells from the same crypt depths were 99 and 106 . The range of whole crypt depths of the 340 day-old mouse was from 232 to 499 , and that of computed crypt MRCSCs were 380 and 455 . This observation shows that computed crypt MRCSCs depth is similar to that of whole crypts , thus validating the reliability of depth estimation of internal branches . We checked for PCR noise by repeating the biochemical analysis of the same biological sample . This analysis revealed that repeat pairs are very close to each other in the lineage tree ( Figure S4 ) . This was true for both , DNA extracted from whole crypts and for DNA extracted from single cells , eliminating the possibility that the topology of the tree as well as depth estimation is influenced significantly by PCR noise . According to the literature , stem cells of the small intestine ( SI ) epithelium are similar to those of the colon in the sense that they do not retain an immortal strand and undergo constant monoclonal conversion [2] , [20] , [21] . We examined whether the reconstructed trees of the SI are similar to those of the colon . For this purpose , whole SI crypts were isolated by tissue digestion from 52 and 199 day-old mice . The median depth of whole SI crypts ( purple nodes , Figure 3 ) was 114±7 cell divisions at 52 days and 206±10 at 199 days ( Figure 3D–3F ) . This indicates that about 92 cell divisions took place during 147 days ( Kolmogorov-Smirnov p<10−6 ) . The increase in depth with mouse age demonstrates that crypt stem cells accumulate MS mutations ruling out the presence of an immortal strand in these cells . In addition , a significant increase with mouse age of the depth of whole crypts relative to the MRCA was observed . This relative depth increased from an average of 65±5 cell divisions in a 52 day-old mouse to an average of 137±9 in 199 day-old mouse ( Kolmogorov-Smirnov p<10−6 ) . This indicates that each small intestinal crypt underwent an independent cell division process . It is important to note that depth increase does not differ in a statistically significant way between crypts in the colon and the SI . To study the correlation between the location and lineage proximity of colon crypts , we randomly sampled colon crypts from longitudinal sections by laser capture ( Figure 4A , blue nodes ) . In addition , adjacent crypts were sampled from two small regions ( smaller than 1 mm ) in the colon ( cyan and magenta , Figure 4A ) . It can be seen that crypts that were sampled from submilimietric regions were significantly clustered on the lineage tree ( p = 0 . 005 ) in contrast to randomly sampled crypts ( Figure 4A ) , confirming the positive correlation between physical and lineage proximity [37] . Figure 4B indicates that there is no statistically significant difference in depth between crypts isolated from different regions . Overall , the above findings indicate that conclusions can be drawn reliably from analyzing reconstructed cell lineage trees in the context of colon stem cell dynamics . Colon crypts from a 278 day-old mouse were randomly sampled using laser capture microdissection ( blue nodes , Figure 5A ) . In addition , cell types such as pancreatic duct cells ( pink ) , CD34 positive hematopoietic stem cells from the bone marrow ( gray ) , B-lymphocytes extracted from the spleen , thymus and lymph nodes ( purple ) as well as beta cells extracted from different islets of Langerhans ( green ) were isolated . The linage tree of these cells was reconstructed using the above mentioned algorithm . We examined whether different colon crypts are clustered separately on the lineage tree , by testing whether crypts are enriched within a given cell population ( Materials and Methods ) . Such clustering of a cell population would suggest a small number of embryonically distinct progenitors . We found that randomly sampled colon crypts are clustered separately on this lineage tree ( p<10−15 , Figure 5A ) , indicating that only few distinctive progenitors generated this tissue . Colon crypts isolated from 278 day-old mouse are substantially deeper than all other cell types , including B-lymphocytes that are known to proliferate throughout adulthood ( Figure 5B ) . While the median depth of colon crypts in this mouse is 430±30 , the median depth of B-lymphocytes , CD34 positive cells from the bone marrow , beta cells and pancreatic duct cells is 130±11 , 95±3 , 79±3 , 80±9 , respectively . Interestingly , each of these cell types has a narrow depths distribution indicating a low standard error . Thus each of these cell types has a characteristic depth range . We noted that CD34 positive cells from the bone marrow , which are the founder population of B-lymphocytes , have much shallower and narrower distribution of depths than B-lymphocytes . In 30 day-old mouse , B-lymphocytes and beta cells depth is 73±3 and 85±6 , respectively ( Figure 5C ) . Therefore , we estimate that B-lymphocytes divide every 4 . 5 days and pancreatic beta cells depth does not increase significantly with mouse age .
Our study shows that reconstructed cell lineage tree obtained by the analysis of a few dozen MS loci per single cell in Mlh−/− mouse is sufficient to provide reliable information regarding stem cell dynamics . This conclusion is based on the fact that our trees deliver information that is consistent with well-established facts related to colon stem cells . First , our observation that single cells randomly sampled from the same crypt are always clustered on the trees indicates that our method enables the detection of monoclonality as well as the distinction between separated lineages in nature . Second , the elongation of whole crypt branches with mouse age shows that reconstructed cell lineage trees may demonstrate that in the colon , each crypt develops in an independent manner . Therefore , branch length may serve as a tool to detect stem cell dynamics . Third , the distance between single cells isolated from the same crypt to their computed MRCSCs was about 40 cell divisions , which is in accordance with the literature . This supports the accuracy of depth estimation of internal branches . Fourth , in accordance with the literature we found that adjacent crypts were clustered on the lineage tree , which shows that the colon is separated into small domains that share a common ancestor [37] . Phylogeography analysis could be applicable to many other tissues . Finally , the mutation rate used in our system was calibrated according to the division rate established in the colon which is one cell division per day [2] ( Materials and Methods ) . The mutation rate obtained from this calibration was applied to the SI and B-lymphocytes , resulting in depths estimation that agrees with that described in the literature [2] , [20] , [42] . The observation , that colon cells were enriched separately from B-lymphocytes and CD34 positive cells from the bone marrow as well as from other cell types , shows that this lineage is constituted by few progenitors . In addition , it indicates that unlike pathological conditions which allow the penetration of hematopoietic cells in order to reconstitute the intestine epithelium [38] , during normal physiology bone marrow cells do not significantly renew the intestine . In this study , we validated many aspects of colonic stem cell dynamics which are already known . Once established , our method may give new insights about healthy and pathologic tissues , in which many aspects of stem cell dynamics are still debated or unknown . The lack of information in these tissues could result from the absence of specific stem cell markers or from the low availability of these stem cells . The topology of reconstructed cell lineage trees can overcome these limitations and expose many aspects of stem cell dynamics . In the eye epithelium for example , due to the lack of specific stem cell markers , the lineage relationship between the cornea and the conjunctiva is still under debate . Specifically , it is not clear whether during adulthood , conjunctiva and corneal cells originate from the same or different stem cells [43] , [44] . The topology of the cell lineage tree may answer this debate . Enrichment of conjunctiva and corneal cells on separate branches would indicate that these cells compose two separated populations , while intermingling of these two populations on the tree would reveal that there is no lineage barrier between them . Overall our cell lineage reconstruction method shows the power of using somatic mutations to decipher developmental and physiological features in crypts and stem cell dynamics . This could be applicable to a wide range of other tissues and stem cells .
C57Bl/6 mice , Mlh1+/− ( kind donation of Prof . Michael Liskay ) [13] and 129SvEv mice , Mlh1+/− ( kindly provided by Prof . Ari Elson from the Weizmann Institute , Israel ) were mated to yield Mlh1−/− progeny of the dual backgrounds , enabling us to distinguish , in all our experiments , between two alleles in the same locus . All animal husbandry and euthanasia procedures were performed in accordance with the Institutional Animal Care and Use Committee at the Weizmann Institute of Science . Animals were sacrificed before colon isolation . The colon was then sliced into small pieces and incubated at 37°C in Hanks balanced salt solution ( HBSS , Sigma Aldrich ) containing 0 . 5 mM EDTA ( Sigma Aldrich ) . After 30 min , the tissue was removed from the medium into a glass tube containing 5 ml HBSS , and stirred for 15 min followed by 2 min centrifugation at 900 RPM . The supernatant was discarded , and the remaining cells were fixed in 70% ice cold ethanol . Single crypts were isolated under the microscope . To isolate single cells from a crypt , each crypt was incubated separately at 37°C for 5 min in a medium containing 0 . 025% pepsin at pH 2 , followed by tiny needle disassembly into single cells . Aliquots of 0 . 5 µl were spread on a flat bottom 96 well plate ( costar 3596 , corning ) and observed under the microscope . Drops that contained single cell were collected into 0 . 2 ml tubes and subjected to whole genome amplification . Frozen mouse tissues were cut at −20°C into 9 µm sections using a cryostat microtome ( CRYOTOME – LEICA CM3050 S ) and mounted on membrane-coated slides ( PALM MembraneSlides – 1 mm PEN membrane covered , PALM Microlaser Technologies ) . Tissue sections were stained with Hematoxylin and Eosin solutions ( Sigma Aldrich ) according to the following protocol: 1 min in 70% ethanol followed by several rinses in double-distilled water ( DDW ) , 30 sec in Hematoxylin , 2 min in tap water pre-filtered with 0 . 2 µm disposable filter units ( Schleicher & Schuell ) , several brief rinses in Eosin , several rinses in 70% ethanol and several rinses in 100% ethanol . Following staining , tissue sections were dried for 5 min at room temperature prior to laser micro dissection . As previously demonstrated [45] , laser micro dissection was performed using the PALM MicroBeam micro-dissection apparatus ( PALM Microlaser Technologies ) . Parameters for laser energy , focus , and speed were adjusted individually for every tissue section , such that dissection was performed with minimal laser energy . The minimal energy level was determined by performing continuous laser micro dissection with decreasing energy levels on a portion of the section adjacent to the area destined for cell isolation . Single cell samples were catapulted using default catapulting energy and focus parameters into adhesive caps of 0 . 2 ml micro-tubes ( PALM Microlaser Technologies ) . In order to verify successful catapulting , the single cells were subjected to whole genome amplification followed by a preliminary PCR over a panel of 16 microsatellite loci ( out of 120 ) . Bone marrow cells were harvested by flashing the marrow with PBS . Cells were frozen in 90% fetal calf serum ( Beit Haemek , Israel ) and 10% DMSO ( Sigma Aldrich ) . Prior to FACS analysis bone marrow cells were thawed and washed twice with PBS . Cells were stained with Anti CD34-pacific blue antibody ( eBioscience ) , and sorted by FACS ARIA . CD34 positive cells were separated to single cells by serial dilutions and microscopic observation as described above . WGA was performed using the Illustra GenomiPhi V2 DNA Amplification kit ( GE Healthcare Life Sciences ) according to the manufacturer's optimized instructions [46] . Briefly , single cells were picked up from a 96-well , flat bottom plate using 3 µl sample buffer from the kit and transferred to 0 . 2 ml PCR tubes . Cell lysis , 10 min at 30°C , was done by adding to each tube 1 . 5 µl cell lysis solution ( 600 mM KOH , 10 mM EDTA , 100 mM dithiothreitol ( DTT ) ) , followed by the addition of 1 . 5 µl neutralizing solution ( 4 vol 1 M Tris-HCl , pH 8 . 0 , added to 1 vol of 3 M HCl ) . WGA , 4 h at 30°C , was initiated by adding 14 µl mix composed of: 4 µl sample buffer , 9 µl reaction buffer , and 1 µl enzyme mix , all supplied with the kit . The reaction was terminated by heat inactivation at 65°C for 10 min . The resulting product was diluted 1∶20 in DDW and analyzed , without any further purification , by PCR , on a preliminary panel of 16 microsatellite loci . Positive cells were further tested on 120 MS loci panel ( Table S1 ) . It is important to note that many of the loci we analyzed are of the X chromosome and since in this work we used only male mice , we were able to receive loci with only one allele , thus avoiding , in these loci , the appearance of two alleles with the same length . PCR repeats and negative controls ( DDW ) were included in every PCR plate . Loci that exhibit a signal in the negative control were excluded from the analysis of all samples run on the corresponding PCR plate . Signal to noise ratio , introduced by the PCR amplification has been assessed for each tree ( Figure S4 ) . MS length was analyzed based on the capillary signals received by the 3730xl DNA Analyzer . Capillary signals that displayed more than one allele per locus were removed from the analysis . Only cells in which more than 25 alleles were amplified were included in the analysis . The size of each allele was determined , providing a genomic signature - the deviation of MS repeats at each locus from the putative zygote . The signatures were used to reconstruct lineage trees by Neighbor Joining algorithm [47] . Each entry in the distance matrix was taken as the maximum likelihood of the number of divisions separating the two cells , given the observed mutational distance between them . The mutational model assumed in the maximum likelihood approach is a multistep model including only insertion and deletion of one or two repeats in each mutation event . This model showed the best description of the ex-vivo trees ( Chapal-Ilani et . al . , unpublished results ) . The step probability function was estimated from ex vivo trees to be 7∶1 for the single step mutation . We also assumed that the probability of insertion and deletion is equal . In order to reconstruct a cell lineage tree with an accurate topology , a reliable estimation of the average mutation rate acquired per cell division is necessary , as it enables the conversion of relatively acquired mutations into an absolute number of cell divisions since the zygote ( depth ) . The estimation was executed by calibrating it to the known division rate of colon stem cells during adulthood , which is about one cell division per day [2] . Therefore , the number of cell divisions of mouse colon stem cells at a certain age is equal to its age plus the number of divisions that occurred during the embryonic period , which is known to be between 1–3 cell divisions per day . Thus , the difference in number of divisions between old and young mouse should be the difference between their ages at sacrifice . The estimation of the average mutation rate ( including mutation of one step or two steps together ) per cell division according to this calibration is 1/100 . This estimate is lower than the estimate we derived for cells dividing in vitro , 1/42 [6] , probably due to the differences between the in vivo and in vitro systems . Depth was calculated from the trees as the branch lengths leading from the root to each terminal leaf . Root signature was taken as the allele size values of tail cells [6] . Since the tail contains cells that originate from ectoderm , endoderm and mesoderm , its genomic signature represents the zygote , or one of its immediate descendants . A full description of the product length of each of the sampled cells is presented in Table S2 , and the mutation distribution of each of the cell types in the different animals is shown in Figure S5 . P-values for the difference in distributions of cell depths were calculated using the Kolmogorov-Smirnov 2 parameters test . Hypergeometric tests were carried out in order to detect a significant clustering of a predefined group of cells on the reconstructed lineage tree . According to the method , given a dichotomous classification of cells in an experiment where cells belong to group and cells belong to the complementary group , for every branch/internal node in the inferred lineage tree , the null hypotheses of no association between the sub-tree and the classification is tested . This is done by performing a hypergeometric test . Given a subtree of cells in which cells are of type , the branch p-value is the probability to see or more cells of type given that the cells are random samples from :We used a False Discovery Rate correction with an FDR of 20% to determine the p-value threshold for the tree in order to take into account the multi hypotheses , from the fact that there are many sub-trees . | The study of stem cell and tissue dynamics in vivo is often carried out by lineage tracing methods that depend on the presence of specific markers and on the availability of stem cells . In the current study , we applied a novel method for the reconstruction of cell lineage trees from microsatellite mutations accumulated during mouse life . We focused on the intestinal epithelium , since its stem cells were intensively studied by various tracing methods that clarified many aspects of their dynamics . We first showed the reliability of our method by confirming three previously established facts: the existence of “monoclonal conversion , ” the absence of an immortal strand mechanism in colon stem cells , and the separation of the colon into small domains each with a common ancestor . We also answered a few open questions , showing that the colon's lineage is separated from other lineages such as the hematopoietic and pancreatic lineages . Overall , our work presents a new approach for the study of stem cell dynamics and can similarly be used for studying stem cell dynamics in other systems . | [
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] | 2011 | Colon Stem Cell and Crypt Dynamics Exposed by Cell Lineage Reconstruction |
Embryonic development is defined by the hierarchical dynamical process that translates genetic information ( genotype ) into a spatial gene expression pattern ( phenotype ) providing the positional information for the correct unfolding of the organism . The nature and evolutionary implications of genotype–phenotype mapping still remain key topics in evolutionary developmental biology ( evo-devo ) . We have explored here issues of neutrality , robustness , and diversity in evo-devo by means of a simple model of gene regulatory networks . The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality . This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition . This class is a repertoire of distinct implementations of this key developmental process , the diversity of which provides valuable clues about its underlying causal principles .
The evolution of life forms on our planet has led to the generation of an enormous variety of living structures . How such patterns of organization emerge [1]–[3] , how contingency [4] and constraints [5] , [6] shape them and how they acquire robustness [7] are unanswered questions that have been at the forefront of biology for more than a century and are still open key questions . The research field encompassing these fundamental issues is referred to as evolutionary developmental biology or in short evo-devo [1] . With the increasing capacity of mathematical modeling to provide fresh insight into the biological processes [8] , computer simulations and experimental approaches in this field have recently reached common ground ( see [9] , [10] as recent reviews ) . A major conceptual problem for the modeling approach to evo-devo is the mapping between genotype ( hereditary genetic information ) and phenotype ( the physical characteristics of the resultant organism ) . It is the phenotype that determines the organism's chances of survival ( fitness ) , as it is on it that natural selection acts . The set of all genotypes , their resultant phenotypes and associated fitness is called fitness landscape . Since Wright's pioneering idea in the early 30's [11] that the hill-climbing process of population's adaptive evolution intimately depends on how smooth or rugged the fitness landscape is , numerous theoretical works have been contributing to what now can be considered as the theory of fitness landscapes [5] , [12]–[14] . Moreover , empirical studies of fitness landscapes can nowadays be performed in the laboratory [15]–[17] , revealing the real evolutionary paths undertaken by the organisms , and thus opening a previously-unavailable window on the actual evolution process . The extensively studied theoretical case that has become the classic example of evolution in a fitness landscape is provided by RNA folding [18]–[20] . Here the genotype is defined by the nucleotide sequence , whereas the phenotype consists of the secondary structure formed by the ( planar ) pattern of the base pairs . Within the RNA context , the existence of iso-phenotypic genotypes ( or neutrality ) has significant implications in evolution , in general [21]–[24] and evo-devo , in particular [25] . More precisely , neutrality is hypothesized to allow a more exhaustive search in the genotype space and consequently , better accessibility to diverse and potentially fitter phenotypes [13] , [26] . The neutrality feature has been encountered and studied in other works of similar nature to the RNA's , such as in the origin and complexification of the protein universe [27] , or in tunable-neutrality models of abstract molecular species [28] , but also in other fields of very different nature . An example is provided by a model of feed-forward signaling networks [29] . Here , a minimal Boolean network receives a set of input signals , and computes the output . The genotype is defined by the wiring diagram ( the network topology plus the weight of each interaction ) , whereas the phenotype is specified by the Boolean computation being performed . An example closer to the current study is a Boolean model of genetic networks [30] , a study that inquires on the requirement of “genetic flexibility” or more precisely , of phenotype continuity in evolution , and the subsequent constraints it may pose to species evolution in a changing environment . In a more recent work , the same group developed an evolutionary model of network evo-devo [31] that adds to the same approach as the current study , with the two works providing complementary clues on the evolution of minimal developmental modules . Again under the Boolean approach , Andreas Wagner's studies ranging from the “epigenetic stability” of developmental pathways [32] to bridging robustness and evolvability by means of neutrality features in models of gene networks [33] complete the framework in which the present work is formulated . Moreover , the present formulation constitutes a continuation of the model introduced in [34] , as well as a Hawk's eye view of an isolated genetic sub-system . Its exhaustive study allows uncovering of features that are generally not accessible from statistical large-scale studies of similar nature . As far as we know , no parallel exhaustive analogies of Boolean approaches have been applied within the context of spatially-explicit evo-devo . We have addressed here the role of neutrality and robustness in the evolution of minimal developmental modules . It is now apparent that the genetic networks responsible for major events in the development of organisms present significant robustness to a wide range of perturbations [35] . Moreover , experimental works reveal that certain genes and their interactions are recurrently encountered in very diverse organisms ( e . g . Homeobox genes [1] , [36] ) , suggesting that minimal genetic modules may underlie fundamental developmental pathways . The current work is inspired by the pioneering theoretical and empirical analysis of developmental genetic regulatory networks in long-germ-band insects ( Drosophila melanogaster ) ( [37]–[39] and references therein ) and plant ( Arabidopsis thaliana ) development [40] . As anticipated by [34] , Drosophila is a suitable model organism to inquire on small gene modules that control specific parts of the development process . The goal of the current work is not a precise explanation of a specific genetic module , but a description of possible underlying principles of network assemblage and evolution . In this context , our guiding questions are: what classes of spatial expression patterns can possibly emerge from signals mediated by juxtacrine ( intra or inter-cellular ) interactions in a minimal genetic network ? Are there intrinsically robust modules and what are their defining characteristics ? Our approach addressing these questions is organized as follows . We introduce the model of gene interactions whose dynamics provides the gene expression pattern . We present the minimal set of genes producing a specific , biologically-relevant expression pattern , and the exhaustive analysis of all possible gene interactions and their associated expression patterns . Among all these topologies , we identify those providing a robust expression pattern , being thus the candidates for the developmental modules discussed above . Ultimately , an evolutionary study of populations of such networks conditioned on diversity is presented , revealing rapid evolution towards robust stripe-like expression patterns . We show that the structure of the encountered minimal robust networks relates to the phenomenon of lateral inhibition , a widespread mechanism of biological pattern formation , emphasizing thus the importance of these minimal development-driving modules .
In the calculation of the expression patterns of the genetic networks , we have continued the Boolean approach of [34] , and we have inspired also from more recent studies and extensions of the reaction-diffusion ( continuous ) connectionist model 49–52 . By the existence of these two approaches , continuous and discrete ( Boolean ) , or analog and digital , respectively , the resultant conclusions can pinpoint gradient-specific and topological mechanisms responsible for specific processes . In this sense , both approaches are needed and thus necessary for a complete understanding . The Boolean modeling approach has been widely employed in modeling the logic of genome architecture , of which development is a constitutive part [31] , [34] . These models have been shown to successfully recover the same expression patterns as those resultant from continuous models [37] , [53] . Even though we emphasize here the literature on Boolean modeling in evo-devo , the continuous approach of reaction-diffusion models constitutes the standard tool for evo-devo . Since the revolutionizing work of Alan Turing on pattern-formation and morphogenesis [54] , there have been rapid and continuous advances in our understanding of what are now called Turing patterns ( see [55] for a recent review ) . As in the case of Boolean modeling , this approach too is constantly employed for addressing new questions in this field . Until recently there has been a significant emphasis on the analyses providing answers to how gene networks work , an answer being mechanisms such as Turing bifurcations . With the advances in computational methods , the issue of increasing interest is why the gene networks have the topology observed , an issue that needs to be addressed in the light of evolution . Again , it is a problem whose resolution is facilitated by applying both approaches , continuous ( [56] , [57] just to mention a few ) and discrete [31] , [52] . In the current model , the network is composed of N genes whose state can be active ( state = 1 ) , or inactive ( state = 0 ) . Among these genes , a number G are local genes that code for intra-cellular molecules , and the rest H , are hormones [50] that code for short range , diffusible paracrine molecules ( see Figure 1 ) . More precisely , the first group of genes interact intra-cellularly with all the genes , while the short-range signaling proteins coded by hormones interact only inter-cellularly with the local genes , affecting thus their expression in neighboring cells . In the previous formulation of [34] , the two types of interactions , local and non-local , are referred to as the internal and external gene network , respectively . In this context , a standard term in evo-devo for “hormone” is morphogen [58] , [59] , whose gradient concentration determines the fates of surrounding cells . Intimately related to the already mentioned concept of positional-information , the diffusion-controlled concentration and residence-time of a morphogen are interpreted by cells as committing signal for a certain state . We have chosen to employ here the term morphogen instead of hormone [50] , even though our Boolean approach does not distinguish gradients of concentration . We consider one-dimensional organisms composed of a collection of C cells . In our case , C = 8 , with larger values having no substantial influence on the results presented here . The equations determining the time evolution of the pattern are ( 1 ) ( 2 ) where denotes cell index , , local gene's index , , morphogen index , and ( 3 ) ( 4 ) Here the G×N matrix A ( internal network; see also Figure 2 ) includes the intra-cellular interactions ( continuous arrows in Figure 1 ) and the H×G matrix B ( external network ) , the inter-cellular interactions ( dashed arrows in Figure 1 ) . The interactions consist of either activation or inhibition , with the values of the matrix being +1 or −1 , respectively . The function ∨ is the “OR” function ( the result is 1 if either of the short-range signals from neighboring cells is active , and 0 , otherwise ) . For the two extremes of the organism ( the anterior and posterior poles ) , the cells have a single neighbor . The function Θ is the threshold function yielding 1 if the argument is positive , and 0 , otherwise . As initial condition , a maternal signal is considered at the anterior pole ( leftmost cell ) , with only the first gene being active , i . e . ; , where δij = 1 if i = j and zero , otherwise . For this initial condition and the chosen interaction matrices , we determined the steady states . More precisely , we only consider the one-state attractors ( fixed point attractor ) , discarding thus the unstable and the oscillatory cases ( see Methods ) . Using the previous definitions , we can define the mapping between wiring and pattern ( Figure 2 ) as: ( 5 ) implying that for each genotype ( genes' wiring ) Wa = ( Aij , Bkl ) ∈W , we have a phenotype ( expression pattern ) . As we shall see , this system shares with other genotype-phenotype mappings a set of interesting features . On one hand , one-point mutants of a given genotype can generate very diverse phenotypes , and on the other , multiple genotypes can generate the same phenotype ( Figure 2 ) . One can also see that the Boolean approach allows a direct relationship between genotype and phenotype , a discretization that would have been hampered in a continuous modeling . As a first approach , we have studied the diversity of expression patterns with the aim of characterizing this genotype-phenotype mapping for a specific case of ( G , H ) . Additionally , by introducing a fitness function , we have studied how adaptation proceeds through the nature of the mapping Ω . In order to select a model for study , we have sought the existence of a specific expression-pattern feature that appears in all developmental modules studied so far . It consists in a stripe-like pattern of a one-cell-wide alternating active-inactive values . For the rules defined above , we found that the minimal number of genes capable of producing such an expression pattern is composed of 2 local genes and 2 morphogenes . Four-element networks have already been shown , through slightly different model assumptions , to be the minimal nets able to generate all possible types of Boolean spatial arrangements [52] . One can exhaustively study all the possible interaction networks of ( N , H ) = ( 4 , 2 ) as it is a tractable number: . For larger networks , the number of configurations becomes intractable for an exhaustive study , but we shall address the statistical study of larger networks as a continuation of the present work . Among the configurations for ( N , H ) = ( 4 , 2 ) and through the approach presented in Methods , there are 405 908 genetic networks that reach point attractors , giving rise to 457 different organism ( or tissue ) patterns produced by 43 distinct gene patterns . Some patterns are very common , as they can be produced by many distinct networks , while other patterns result from very specific topologies . Ordering or ranking by decreasing frequency associates thus a rank to the patterns , resulting into the distribution N1 ( r ) of a rank r . It has been reported to follow Zipf's law , N1 ( r ) ∝a ( b+r ) −γ , for both RNA folding [19] and feed-forward signaling nets [52] . In the present case , the observed distribution follows a power law N1 ( r ) ∝r−γ , with γt = 2 . 3 for tissue patterns frequency ( Figure 3A ) and γg = 3 . 8 for gene patterns frequency ( Figure 3B ) . The system of local-genes and morphogenes as described above presents symmetry with respect to the latter ( Figure 3C ) . The symmetry in the local genes is broken by the initial condition–first gene is active . Therefore , a significant majority of the interaction matrices have a symmetric pair that is equivalent in terms of the interactions and thus resultant expression pattern ( 457 tissue patterns reduce to 263 unique or non-degenerate patterns ) . However , in the present study we have addressed also the issue of evolution , for which the totality of possible networks has to be employed in order to allow for different evolutionary paths . Thus , we chose to maintain this degeneracy . Robustness and evolution have been shown to be closely linked , even though there is no consensus on this correlation being entirely positive or rather a positive-negative trade-off [62] , [63] . The developmental scheme has to be robust enough to guarantee a reliable organism but not too robust to impede evolutionary changes and thus improved adaptive solutions . In this direction , theoretical studies of gene networks can shed light on the mechanisms responsible for this trade-off . Such a task is difficult to assign to experimental approach but perfectly assignable to theoretical modeling , even though the inspiration and final results relate to the fossil record [64] and experimental work [65] . In this context and for the evolutionary part of our study , we have associated a fitness function weighting pattern complexity . The fitness function associated to a given phenotype is inspired in previous works on the RNA folding landscape [66] and it is: ( 6 ) with β = 0 . 01 and , where the parameters H and A are the entropy and activity measure , respectively . Networks giving rise to unstable expression patterns are attributed a minimum fitness value , F = 0 . 01 . The measure of activity , A , is defined as the fraction of the genes active in at least one cell . As we study the case ( N , H ) = ( 4 , 2 ) , the activity A takes the values 0 . 0 , 0 . 25 , 0 . 75 , 1 . The activity A is introduced in order to guarantee that all genes are used at least once through development . The entropy of the resultant gene expression is a measure of the heterogeneity of the pattern and is defined in terms of ( 7 ) where H ( gi ) is the ( spatial ) entropy of the i-th gene . Since only ON-OFF states are allowed , it reduces to ( 8 ) being p1 the probability that gi takes the ON state , i . e . . As defined , H ( gi ) = 0 for a fully homogeneous pattern and H ( gi ) = log 2 for a pattern with equal number of ON and OFF states . Having defined the fitness function , the entire fitness landscape for the case-study of N = 4 can be calculated . A glance at the fitness landscape shows that only through one-link mutations , a given expression pattern and/or fitness value can be maintained in long neutral paths . For illustrative purposes , we arbitrarily chose an example of such neutrality in diversity in Figure 8 by a path of one-link mutations maintaining the expression pattern ( fitness ) and robustness . In our evolutionary study , we have used a constant population model ( N = 500 networks ) of non-overlapping generations , with the individual networks replicating according to their fitness . By simulating the temporal evolution of this population initiated by identical networks of only one link , we have witnessed the increase in the average fitness of the population as more diverse patterns appear . A couple of examples of such evolutionary paths is shown in Figure 9 . We display both the time evolution of the mean fitness ( ) and robustness ( ) , and the corresponding path in the ( L+ , L− ) space . As a general trend in our evolutionary experiments , we have noticed that the population rapidly becomes dominated by stripe networks , constituting a stable almost-unitary fraction of the total population . It is interesting to remark that , even though the mean robustness varies , it fluctuates around a high value . This behavior is expected , as one can infer from the robustness distribution of the stripe networks ( Figure 5B ) . Even so , it remains an important result , as it intrinsically relates high robustness with stripe patterns . As a general characteristics for the evolutionary paths , we have noticed that all networks increasingly acquire positive interactions ( Figure 9A and 9C ) which provide an increase in diversity , and implicitly in the entropic measure H . The last steps prior to reaching the maximum fitness are characterized by the acquisition of negative regulatory interactions , stabilizing and diversifying the expression pattern . We wondered about the particularities of the networks of maximum fitness together with maximum robustness . First of all , there exist several such networks characterized by a proper balance between activating and inhibiting interactions ( Figure 10 ) . In average , this proper balance results to be L+/L−≈1 , and ensures their robustness and the maximum diversity of expression pattern . Interestingly enough , all these networks present the same expression pattern , a stripe pattern in all genes . We expected that maximum fitness networks could be of non-stripe pattern , as maximum diversity can be obtained through other patterns too ( e . g . an all-active half plus an all-inactive half; similar to the example of gene pattern in Figure 3B ) . Unexpectedly , no other pattern of maximum diversity other than the all-stripes one exists among the stable patterns . This points to the fact that , in such a minimal pattern-formation module , there is a tight inter-dependence between the stripe-like pattern and high robustness values . This is supported by two issues . The first indication is related to the robustness distribution of the stripe networks ( Figure 5B ) where it can be seen that they are biased towards high robustness values , with more than 60% of them having maximum robustness . The second argument , as mentioned above , relates to the fact that non-stripe networks of maximum entropy do not exist among stable networks . Even though individual genes may be present in an organism in the form of all-active half and an all-inactive second half , these individual gene patterns do not combine into an H = 1 stable organism . In fact , we notice that such a gene pattern exists in stable organisms only in combinations with null gene pattern . Finally , in support of the tight relationship between robustness and stripe networks , the neurogenic network in Drosophila embryo has been shown to present such inter-dependence [48] , [67] , and we shall come back to this issue shortly . Moreover , we remarked that all these robust stripe networks form a connected meta-graph or a neutral meta-graph , where connections imply one-link mutation . A relevant conclusion from this observation relates to the stability of the expression pattern against changes in the interaction rules . The robustness to the interaction rules relates to genetic robustness , in which gene knock-outs are contemplated . Such robustness has been observed for the developmental module that underlies the ABC model of floral organ specification in A . thaliana [53] , consistent with an overall floral plan widely conserved among flowering plants . Similarly , structural alterations ( gene knock-outs ) of the neurogenic gene regulatory network in Drosophila appear to be well tolerated by the system from the point of view of the resultant gene expression [48] . In the general context of genome architecture , there is undeniable evidence of redundancy ( or multiple backup circuits ) [68] as a key element , though not unique , responsible for this structural robustness property . This type of robustness manifests itself by the resilience of circuit designs to the removal or loss of a given unit . In the relationship between robustness and modularity too , it is interesting to mention the distinction between redundancy and degeneracy [69] , where degeneracy refers to different units performing a given function , while the redundancy relates to the presence of multiple identical copies of a unit . Several models have explored the role of evolution in driving the formation of backup circuits [70] , [71] , emphasizing the gene duplication processes as the primary dynamical building-block of innovation [72] . It is worth noticing that there exist several minimal networks at the root of all these particular best networks . By minimal we refer to the minimum number of genetic interactions leading to this robust fittest phenotype . For visualizing the relationship between them , we have represented all the fittest networks in the form of an inclusion directed meta-graph in Figure 11 . Nodes represent networks , and we considered that network A is connected to network B if one link has been added to the network A to produce network B . As a detail , the size of the node is an indication of the number of constitutive interactions of the associated network . All these networks have in common the same gene expression pattern , a pattern characterized by stripe-like expression for all the genes ( Figure 11 ) . In addition to these symmetry considerations , we also noticed that pairs of these minimal networks ( brackets in the upper part of Figure 11 ) share common construction of the stable expression pattern from the initial condition . For illustrative purpose , the steps necessary to reach the stable patterns have been drawn in Figure 12 for two minimal networks ( networks indicated by an asterisk in Figure 11 ) . One can identify a connection motif as the key element responsible for the robustness and diversity , a motif emphasized in Figure 12 . By isolating this interactions in the colored boxes we emphasize also the fact that the inhibitory interaction can be provided either by a morphogen or a local gene ( see the pairs under brackets in Figure 11 ) . The resultant robust configurations and the interaction motif recall a key process in pattern formation , especially in developing tissues: lateral inhibition with feedback [55] . Lateral inhibition refers to a type of cell-cell interaction in which a cell that adopts a particular fate inhibits its immediate neighbors from doing likewise . The modeling of the neurogenic genes Notch and Delta , and their associated trans-membrane proteins sheds light on the mechanism of amplification of differences between adjacent cells [73] . Moreover , it has been shown that for the neurogenic network in Drosophila embryo , the lateral inhibition buffers the expression pattern against perturbations ( knock-outs ) [48] , resulting in a tight correlation between robustness and stripe-like pattern mentioned above . We have considered in the present study the one-dimensional organisms , as this approach provides a clarifying perspective on the basics of pattern formation in such minimal networks , and thus a faster identification of the underlying key features for robustness and diversity . Preliminary results on the 2D ( N , H ) = ( 4 , 2 ) case yield interesting comparisons with the 1D case . Among these , slightly more than 10% of the most-robust fittest 1D networks constitute the set of most-robust fittest networks ( according to eq . 6 ) in the 2D case . In this context , although most of our qualitative trends are also observed , the number of non-null stable patterns is slightly reduced ( 189 658 in 1D compared to 165 856 in 2D ) . This decrease is consistent with the higher degrees of freedom allowed by the dimensional increase . It also opens the possibility of increased instability , and thus less robustness . In future works , we shall inquire on the necessary features of the interaction network leading to the maintenance of robustness and diversity independently of the spatial framework .
Embryonic development is a particular field in biology characterized by a constant feedback between theoretical analysis and experimental work . Even though experimentalists still remain cautious on the predictive power of the former , there have been important advances in clarifying the organizational principles of embryonic pattern formation [1] , [3] , [55] , [58] . Restricting ourselves to studies on Drosophila development ( even though the conclusions seem universal ) , extensive simulations have shown that topology constrains the possible behavior of a regulatory network [74] . Similar studies on plant development also support this conclusion [40] . Moreover , in the context of development and not only , a crucial relationship has been proved to exist between topology and robustness [39] , [74] . It is thus apparent that under the requirements of a given phenotype , selection will ensure that increasingly stable networks of interactions evolve towards it . In this direction , developmental modules appear to play the major organizing role . These kernels of the entire developmental genetic network perform distinct regulatory functions and constitute information-processing units in the correct and precise unfolding process of development [75]–[77] . Thus , two of the central key topics of developmental biology are the evolution and robustness of patterning mechanisms , and the still unsettled relationship between them . In this context , we have studied small epigenetic networks that could behave evolutionarily as minimal modules capable of producing a stripe expression pattern similar to those common in early embryonic development . In the present approach the minimal number of genes capable of producing such an expression pattern is N = 4 , number that allows an exhaustive analysis of the genotypic space . Considering both topological and robustness issues , we have determined the space of expression patterns produced by such module using a dynamical modeling inspired from previous related studies of Boolean and continuous models [50] , [52] , [78] , [79] . Among all possible expression patterns , we have identified those presenting enhanced reliability in maintaining their expression through perturbations . From performing evolutionary experiments ( Figure 9 ) , we can conclude that the paths towards the most robust and diverse expression pattern are short . In other words , the optimal modules are rapidly encountered in the landscape . We find necessary a comparison between the above-mentioned continuous models and the currently employed discrete approach . The former works are related to a different class of assumptions , both on the dynamical side ( namely , Michaelis-Menten kinetic description of gene-gene interactions ) and in the type of questions being considered ( namely , a statistical study of the parameter space and network structure ) . In these works , search algorithms explored extended regions of the parameter space and , once a pattern-forming network was found , a network reduction process was applied in order to find minimal modules . The leading mechanisms pervading the formation of stripes cannot be directly compared with our study ( where the equivalent nonlinearities would be of higher order , Hill-like class ) . Moreover , we have concentrated here on a well-defined , small-sized network such that the calculation of the entire space of possibilities could be feasible . Exploring the landscape structure in such a systematic way would be much more difficult ( if possible at all ) under the continuous approximation , and thus our conclusions need to be restricted to the discrete level . Nevertheless , we consider that a direct comparison of results between continuous and discrete models requires a detailed dedicated study . At least in the segment polarity network in Drosophila , there is general agreement between continuous and discrete models . That is , comparison has been conducted between approaches associated to a given system and thus characterized by similar assumptions . A general comparison of capabilities and limitations of discrete versus continuous models has not been addressed , as far as we know , and it is thus an important open question . Here the analysis of the most robust modules uncovered a set of networks , all forming a meta-graph where links are one-point mutations between networks . The existence of this meta-graph is an indication of structural robustness of such networks , as many mutations can be neutral . Also associated to this set , there exist certain minimal networks responsible for robustness and diversity , and many additional interactions provide a back-up mechanism or alternative pathways . The generic properties of the optimal modules indicate thus that lateral inhibition is likely to be a generic form of creating ON-OFF spatial patterns , although the exact structure of the generating module might differ , given the observed neutrality . Future work will explore how these modules might emerge and evolve within larger gene regulatory webs , the underlying phylogenetic patterns as well as the impact of network topology on evolvability and developmental plasticity .
The equations determining the evolution of genes' state in time are:where ∨ is the “OR” function . Similarly , genes coding for short-range signaling molecules receive inputs only from the first set , with specific equations at the boundaries reading: The function Φ ( x ) is a threshold function , i . e . Φ ( x ) = 1 if x>0 and zero ( inactive ) otherwise . Given the initial condition and after transient time T ( = N*C , with C the number of cells ) time steps , we check on the stability of the resultant pattern , considering only the fixed-point attractors and not the oscillatory ones . We consider such a relatively short transient time as relevant to the evolutionary studies that we shall introduce in the following section . As defined , the phenotype in our model is given by the steady state defined by the N×C matrix P* given by:where and indicate the stationary values of each regulatory element after the transient . With our previous definitions , we can properly define the mappingwhere for each genotype Wa = ( Aij , Bkl ) ∈W , we have a phenotype . The distance between two genotypes , Wa and Wb is defined by ( 9 ) where δa , b ( Aij ) = 0 if , and it is 1 otherwise . If d ( Wa , Wb ) = 1 , the networks Wa and Wb are connected in a meta-graph ( see Figure 11 ) . The Python code developed for the calculation of the fitness landscape and for the evolution experiments is available as Protocol S1 . The dataset corresponding to the landscape of the study case ( N , H ) = ( 4 , 2 ) is also hosted online as Dataset S1 . | The diversity of life is a consequence of changes in the genotype ( genes and their interdependence ) , but it is upon the observable organism's morphology ( phenotype ) that natural selection acts . Thus , the study of genotype–phenotype mapping can reveal key mechanisms driving life's capacity of continuous evolution and resilience in diverse environments . In this context , it has been observed that small numbers of genes form robust functional developmental modules , hierarchically reused throughout development . Here we analyze the evolution of small genetic modules toward higher diversity and robustness . Given the small size of the gene network , we can afford to analyze all possible topologies and thus the entire fitness landscape . This exhaustive study as well as simulations of evolutionary processes uncover a set of genetic interactions producing robust and diverse phenotypes . We single out the distinctive features of these networks responsible for their stability against environmental and structural perturbations . More precisely , all these robust genotypes can be related to the key mechanism of lateral inhibition for which a cell of a given type inhibits its neighbors to keep them from adopting the same type . Their distinctive features can thus shed light on the underlying mechanisms leading to pattern formation through lateral inhibition . | [
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] | 2008 | Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition |
Adenoviruses are DNA viruses that naturally infect many vertebrates , including humans and monkeys , and cause a wide range of clinical illnesses in humans . Infection from individual strains has conventionally been thought to be species-specific . Here we applied the Virochip , a pan-viral microarray , to identify a novel adenovirus ( TMAdV , titi monkey adenovirus ) as the cause of a deadly outbreak in a closed colony of New World monkeys ( titi monkeys; Callicebus cupreus ) at the California National Primate Research Center ( CNPRC ) . Among 65 titi monkeys housed in a building , 23 ( 34% ) developed upper respiratory symptoms that progressed to fulminant pneumonia and hepatitis , and 19 of 23 monkeys , or 83% of those infected , died or were humanely euthanized . Whole-genome sequencing of TMAdV revealed that this adenovirus is a new species and highly divergent , sharing <57% pairwise nucleotide identity with other adenoviruses . Cultivation of TMAdV was successful in a human A549 lung adenocarcinoma cell line , but not in primary or established monkey kidney cells . At the onset of the outbreak , the researcher in closest contact with the monkeys developed an acute respiratory illness , with symptoms persisting for 4 weeks , and had a convalescent serum sample seropositive for TMAdV . A clinically ill family member , despite having no contact with the CNPRC , also tested positive , and screening of a set of 81 random adult blood donors from the Western United States detected TMAdV-specific neutralizing antibodies in 2 individuals ( 2/81 , or 2 . 5% ) . These findings raise the possibility of zoonotic infection by TMAdV and human-to-human transmission of the virus in the population . Given the unusually high case fatality rate from the outbreak ( 83% ) , it is unlikely that titi monkeys are the native host species for TMAdV , and the natural reservoir of the virus is still unknown . The discovery of TMAdV , a novel adenovirus with the capacity to infect both monkeys and humans , suggests that adenoviruses should be monitored closely as potential causes of cross-species outbreaks .
Adenoviruses , first isolated in the 1950s from explanted adenoid tissue , are double-stranded nonenveloped DNA viruses that naturally infect many vertebrates , including humans and nonhuman primates . The human adenoviruses in the Mastadenovirus genus , comprised of all mammalian adenoviruses , are classified into 7 species A-G , and at least 51 different serotypes ( and 5 proposed types , HAdV-52 to HAdV-56 ) have been described to date [1] , [2] . Adenoviruses are the cause of an estimated 5–10% of febrile illnesses in children worldwide [3] . Some serotypes , such as human adenovirus type 14 ( HAdV-14 ) , have been associated with severe and potentially fatal outbreaks of pneumonia in residential facilities and military bases [4] . Adenoviruses have also been associated with other clinical syndromes including conjunctivitis , hepatitis , and diarrhea [5] . In nonhuman primates , most epidemiologic studies of adenoviruses have focused on their identification in fecal samples from asymptomatic animals [6] , [7] , [8] . Overt respiratory disease associated with simian adenoviruses has also been observed [9] . Although adenoviruses are significant pathogens , genetically modified strains are being actively explored as potential vectors for vaccines and gene therapy [10] . Infection by adenoviruses has generally been thought to be species-specific . Human adenoviruses do not usually replicate in monkey cells in the absence of helper viruses [11] , and do not productively infect rodents ( and vice versa ) [12] . Studies of sera from animal handlers and zoo workers exposed to chimpanzees in captivity fail to detect antibodies to chimpanzee adenoviruses [13] , [14] . However , recent serological surveys have found antibodies to New World and Old World monkey adenoviruses in donor human sera from regions where the monkeys are endemic [14] , [15] . In addition , phylogenetic analyses of adenoviruses from greater apes reveal that they fall precisely into “human” adenoviral species B , C , and E [7] . The high degree of sequence relatedness within members of each species suggests that at least some adenoviral strains may be capable of infecting both nonhuman primates and humans . Beginning in May of 2009 , a deadly outbreak of fulminant pneumonia and hepatitis occurred in a closed colony of New World titi monkeys of the Callicebus genus at the California National Primate Research Center ( CNPRC ) . Routine microbiological testing for an infectious etiology was negative . We previously developed the Virochip ( University of California , San Francisco ) as a broad-spectrum surveillance assay for identifying viral causes of unknown acute and chronic illnesses [16] , [17] , [18] , [19] , [20] , [21] , [22] . The Virochip , a pan-viral microarray containing ∼19 , 000 probes derived from all viral species in GenBank ( n∼2500 ) [21] , [23] , has been previously successful in detection of novel outbreak viruses such as the SARS coronavirus [22] , [24] and the 2009 pandemic H1N1 influenza virus [23] . Here we apply the Virochip to identify a novel and highly divergent adenovirus as the cause of the titi monkey outbreak . In addition , we present clinical and serological evidence that this virus may have infected a researcher at the CNPRC and a family member , thus demonstrating for the first time the potential for cross-species infection by adenoviruses .
In early 2009 , the CNPRC housed 65 titi monkeys in one quadrant of an animal building . The index case , a healthy adult titi monkey , presented on May 14 , 2009 with cough , lethargy , and decreased appetite ( Fig . 1A , T1 ) . Despite aggressive treatment with intravenous fluids and antibiotics , the animal developed severe respiratory distress and was humanely euthanized 5 days later . A second case presented 4 weeks later near the entrance to the building ( Fig . 1A , T54 ) . In the interim period , 3 healthy titi monkeys had been relocated from a separate building ( Fig . 1A , T2 , T3 , and T19 ) , with 2 of the 3 monkeys placed into the cage formerly occupied by the index case , reflecting a total at-risk population of 68 . Over the ensuing 2 months , 21 additional monkeys , including one of the relocated monkeys , presented with clinical signs similar to those shown by the index case ( attack rate = 23/68 , or 34% ) ( Figs . 1A and 1B ) . Clinical signs in affected animals included cough , lethargy , poor appetite , tachypnea , and abdominal breathing . These symptoms progressed to overt respiratory distress and death or humane euthanasia within an average of 8 days . Chest radiographs typically revealed diffuse interstitial pulmonary changes and bronchoalveolar consolidation indicative of pneumonia , with right middle lobe predominance ( Fig . 1C ) . Animals displaying clinical signs were quarantined and aggressively treated by veterinarians with supplemental oxygen , anti-inflammatory medications , bronchodilators ( nebulized albuterol ) , broad-spectrum antibiotics , and antivirals ( oseltamivir and/or ribavirin ) . In total , 19 animals died or were euthanized due to the illness during the outbreak ( case fatality rate = 19/23 , or 83% ) . Only 4 monkeys survived , even though the majority of sick animals ( 17/23 , or 74% ) consisted of apparently healthy adults and juveniles . Interestingly , none of the 133 rhesus macaques ( Macaca mulatta ) housed in the same building became sick during the outbreak , and neither did any of the Old World monkeys from surrounding outdoor colonies of rhesus and cynomolgus macaques ( Macaca fascicularis ) . Gross necropsy findings were similar in all titi monkeys and were characterized primarily by diffuse , consolidated pneumonias , with occasional evidence of fibrinous pleuritis , pericardial/pleural edema , and hemorrhage ( Fig . 1D-1 ) . Some livers , spleens , and lymph nodes were found to be abnormally enlarged . Hepatic necrosis and hemorrhage , along with ascites , were occasionally appreciated . On histologic examination , the normal cellular architecture of the lung and trachea was destroyed , and prominent intranuclear inclusion bodies were observed in the liver , lung , and trachea ( Figs . 1D-2 and 1D-3 ) . A routine microbiological workup for infectious causes of the outbreak , including bacterial , mycoplasma , and fungal cultures , was negative . Respiratory viral testing failed to detect evidence of respiratory syncytial virus , adenovirus , influenza virus A and B , human metapneumovirus , and parainfluenza virus types 1 , 2 , and 3 . Given the clinical presentation of a severe acute viral respiratory illness and the appearance of intranuclear inclusion bodies on histological examination , we strongly suspected that a virus that had eluded detection by conventional assays was the cause of the titi monkey outbreak . Nasal , lung , and liver swab samples collected during necropsy were analyzed using the Virochip [21] , [23] . Microarrays were analyzed using ranked Z-scores to assess the highest-intensity viral probes [18] . From a lung swab sample from an affected monkey , 4 of the top 80 probes on the Virochip corresponded to adenoviruses . Other viruses or viral families with ≥4 probes among the top 80 , including chimpanzee herpesvirus ( Herpesviridae ) , bovine viral diarrhea virus ( Flaviviridae ) , and endogenous retroviruses ( Retroviridae ) , were regarded as less likely to cause fulminant pneumonia and hepatitis , so were not pursued any further . The 4 adenovirus probes mapped to 2 different gene regions corresponding to the DNA polymerase and penton base ( Fig . 2A ) . Interestingly , the 4 viral probes were derived from 2 different Adenoviridae genera ( SAdV-23 , simian adenovirus 23 , PAdV-A , porcine adenovirus A , and HAdV-5 , human adenovirus 5 , in the Mastadenovirus genus; FAdV-D , fowl adenovirus D , in the Aviadenovirus genus ) , suggesting the presence of a divergent adenovirus that was not a member of any previously known species . To confirm the Virochip finding of an adenovirus , we used consensus primers to amplify a 301 bp fragment from the hexon gene by PCR [25] . The fragment shared ∼86% nucleotide identity with its closest phylogenetic relatives in GenBank , SAdV-18 , an Old World vervet monkey adenovirus , and the human species D adenoviruses . The newly identified adenovirus was designated TMAdV , or titi monkey adenovirus . Specific PCR for TMAdV was then used to screen body fluids and tissues from affected monkeys ( Table 1 ) . PCR results were positive from post-necropsy liver and lung tissues as well as from sera , conjunctival swabs , oral swabs , and nasal swabs collected at time of quarantine in 8 different affected monkeys , but were negative from a throat swab from an asymptomatic animal whose other 5 cage mates had become sick . In addition , nasal swabs were negative in 3 asymptomatic , minimal-risk titi monkeys housed in a separate building . To confirm the presence of virus in diseased tissues , we examined lung tissue from affected monkeys by transmission electron microscopy , revealing abundant icosahedral particles characteristic of adenovirus filling the alveoli ( Fig . 1D-4 ) . Next , to assess persistent subclinical infection from TMAdV , we analyzed serum samples from at-risk asymptomatic or affected surviving monkeys 2 months after the outbreak ( n = 41 ) . All post-outbreak serum samples were negative for TMAdV by PCR ( Table 1 ) . To assess potential TMAdV shedding , stool samples collected from all cages housing titi monkeys 2 months post-outbreak were analyzed by PCR ( n = 27 ) , and were found to be negative . In addition , we checked for TMAdV in rectal swab samples from rhesus macaques housed in the same building as the titi monkeys ( n = 26 ) and in pooled droppings from wild rodents ( n = 2 ) living near the titi monkey cages . All macaque and rodent fecal samples were negative for TMAdV by PCR . We also sought to determine whether PCR assays commonly used to detect human adenoviruses in clinical or public health settings could detect TMAdV . Adenovirus PCR was performed on a TMAdV-positive clinical sample , a TMAdV culture , and a human adenovirus B culture ( as a positive control ) using an additional 5 pairs of primers , according to previously published protocols [26] , [27] , [28] Three of the 5 primer pairs , designed to detect human respiratory adenoviruses B , C , and E , failed to amplify TMAdV [27] . The remaining 2 pairs of primers , both derived from highly conserved sequences in the hexon gene [26] , [28] , were able to detect TMAdV in culture as well as directly from clinical material . To facilitate whole-genome sequencing of TMAdV , deep sequencing of a lung swab from one affected titi monkey and lung tissue from another affected monkey was performed . Out of ∼11 . 9 million high-quality reads , 2 , 782 reads and 3 , 767 reads aligned to the SAdV-18 genome by BLASTN ( Fig . 2B , blue ) and TBLASTX ( Fig . 2B , transparent blue ) , respectively , with reads mapping to sites across the genome . De novo assembly of the complete TMAdV genome from reads that aligned to SAdV-18 was not possible due to insufficient sequence coverage ( <46% ) . The poor apparent coverage was the result of high sequence divergence of the TMAdV genome from SAdV-18 , which hindered the identification of most of the 16 , 524 actual deep sequencing reads derived from TMAdV ( Fig . 2B , red ) . Thus , after partial assembly of TMAdV using overlapping reads aligning to the SAdV-18 genome , remaining gaps were closed by specific PCR . The complete genome of TMAdV was found to be 36 , 842 base pairs in length , with a base composition of 20 . 8% A , 29 . 8% C , 29 . 8% G , and 19 . 6% T , and a GC content of 59 . 6% , comparable to that of adenoviral species Groups C , D , and E in the Mastadenovirus genus . The deduced genomic structure of TMAdV was also similar to that of other mastadenoviruses and consists of 34 open reading frames ( Fig . 2C ) . Whole-genome phylogenetic analysis placed TMAdV in an independent species group separate from the known human adenoviral species A–G ( Fig . 3 ) . Among all 95 fully-sequenced adenovirus genomes in GenBank , the closest simian adenoviral relatives to TMAdV were SAdV-3 , SAdV-18 , and SAdV-21 , with pairwise nucleotide identities ranging from 54 . 0% to 56 . 3% ( Fig . 4 ) . The closest human adenoviral relatives were the species D adenoviruses , which share 54 . 3% to 55 . 1% identity to TMAdV , with human adenoviruses of other species slightly less similar ( 51 . 1%–54 . 6% ) . The placement of TMAdV into a separate group by phylogenetic analysis was also observed when looking individually at the hexon , polymerase , penton base , and fiber genes ( Fig . S1 ) . Scanning nucleotide pairwise identity plots revealed that , among the major adenovirus genes , the DNA polymerase and hexon are more conserved , whereas the E1A and fiber are more divergent ( Fig . 4 ) . The significant overall sequence divergence of TMAdV from known human and simian adenoviruses is highlighted by the finding that PAdV-A ( porcine adenovirus A ) , a non- primate mammalian adenovirus , shared only a slightly less similar whole-genome pairwise identity to TMAdV of 47 . 0% ( Fig . 4 ) . In fact , in the DNA polymerase gene , TMAdV shared a pairwise identity with PAdV-A of 67 . 2% , comparable to its pairwise identities with the other human adenoviruses , 59%–71 . 7% ( Figs . 4 and S1 ) . Although TMAdV was found to be highly divergent from other adenoviruses , different isolates of TMAdV from 3 affected titi monkeys were remarkably conserved , sharing 100% identity across the full-length hexon gene ( data not shown ) . The high level of sequence divergence in TMAdV held true at the amino acid level as well , with amino acid identities relative to other mastadenoviruses ranging from 20 . 8% to 27 . 5% for the fiber , the most divergent protein , to 68 . 7%–78 . 2% for the hexon ( Table 2 ) . Although bearing low sequence similarity to other adenoviruses , the penton base of TMAdV contained an RGD motif that presumably binds αv integrins . By both nucleotide and amino acid comparisons , the closest phylogenetic relative to TMAdV in GenBank overall was SAdV-3 ( Fig . 4; Table 2 ) . Bootscanning analysis revealed no evidence for recombination of TMAdV with other adenoviruses at either the whole-genome or individual gene level ( Fig . S2 ) . The main neutralization determinant for adenoviruses , the epsilon determinant ( ε ) , is formed by loops 1 and 2 in the hexon protein [29] . The epsilon determinant of TMAdV was significantly divergent from that of other mastadenoviruses , with amino acid identities in loop 1 varying from 30 . 6% to 44 . 8% and in loop 2 varying from 54 . 4% to 67 . 0% ( Table 2 ) . This observation suggested that cross-neutralization of TMAdV with sera reactive against other human/simian adenoviruses is unlikely . We next attempted to culture TMAdV in an A549 ( human lung adenocarcinoma ) cell line , a BSC-1 ( African green monkey kidney epithelial ) cell line , and PMK ( primary rhesus monkey kidney ) cells ( Fig . 5 ) . Direct inoculation of cell cultures with a lung swab sample from an affected titi monkey produced a weak initial cytopathic effect in macaque BSC-1 and human A549 cells at day 7 . However , despite multiple serial passages , we were unable to propagate the infected cell culture supernatant in either BSC-1 or PMK cells . In contrast , propagation in human A549 cells resulted in viral adaptation by passage 6 and generation of a fully adapted strain of TMAdV by passage 10 that was able to productively infect all 3 cell lines . Thus , culturing and propagation of TMAdV were successful in a human A549 cell line , but not in established or primary monkey kidney cell lines . In hindsight , only one individual at the CNPRC reported becoming ill during the titi monkey outbreak , the researcher in closest , daily contact with the animals . Symptoms began near the onset of the outbreak , although whether they began prior to or after identification of the index case is unclear . The researcher , with a past medical history of multiple sclerosis , initially developed symptoms of a viral upper respiratory infection ( URI ) , including fever , chills , headache , and sore throat , followed by a dry cough and “burning sensation in the lungs” that was exacerbated by a deep breath or coughing . The researcher endorsed a history of recurrent upper respiratory infections , and did not regard the illness as related to the titi monkey outbreak . Although symptoms persisted for 4 weeks , at no time did the researcher seek medical care , and no antibiotics were taken during the illness . We carried out contact tracing to identify family members and other individuals in close contact with the researcher . Interestingly , two family members in the household also developed flu-like symptoms about 1–2 weeks after the researcher initially became sick . Their symptoms – fever , cough and muscle aches – appeared milder than those of the researcher and completely resolved within 2 weeks . Neither individual sought medical care for these symptoms , and notably , neither had ever visited the CNPRC . To explore a potential link between the outbreak and associated illness in humans , we blindly tested available sera from titi monkeys ( n = 59 ) , rhesus macaques housed in the same building ( n = 36 ) , CNPRC personnel and close contacts ( n = 20 ) , and random human blood donors ( n = 81 ) for evidence of recent or prior infection by TMAdV by virus neutralization ( Fig . 6 ) . Nineteen serum samples from 15 at-risk affected ( symptomatic ) titi monkeys were tested . Among 3 affected titi monkeys surviving the outbreak , 2 monkeys mounted a vigorous neutralizing Ab response to TMAdV , with negative pre-outbreak Ab titers ( <1∶8 ) but antibody titers 2 months after the outbreak of >1∶512 , while 1 monkey exhibited a positive but much weaker response . Affected titi monkeys who died during the outbreak exhibited a wide range of neutralizing Ab titers , from <1∶8 to >1∶512 ( those without Ab likely died before mounting a response ) . To investigate the possibility of subclinical infection by TMAdV , we also examined serum samples from asymptomatic titi monkeys ( n = 40 ) and nearby rhesus macaques ( n = 36 ) , collected 2 months after the outbreak . Fourteen of 40 asymptomatic titi monkeys tested ( 35% ) had antibody to TMAdV , indicating that the incidence of subclinical infection was significant ( Fig . 1A; Fig 6 ) . In fact , one of the 14 asymptomatic titi monkeys with positive Ab titers was located in the minimal-risk building . In contrast , only 1 of 36 rhesus macaque samples was positive , with an Ab titer of 1∶16 . The 1 antibody-positive rhesus serum sample was negative by specific PCR for TMAdV ( data not shown ) , as was stool from the cage in which the rhesus monkey was housed ( Table 1 ) . Approximately 4 months after the outbreak , serum samples were collected from CNPRC personnel in direct contact with the titi monkeys . Serum samples were also collected from the two family members of the clinically ill CNPRC researcher 1 year after the outbreak . Only two samples were found positive for neutralizing Abs to TMAdV: ( 1 ) Ab titers for the clinically ill researcher were 1∶32 , and ( 2 ) Ab titers for one of the family members of the clinically ill researcher were 1∶8 . Among 81 random blood donors from the Western United States , 2 individuals ( 2/81 , 2 . 5% ) had positive Ab titers of 1∶16 and 1∶8 . Pooled rabbit sera containing antibodies to human adenovirus serotypes 1 through 35 , representing species A–E , were unable to neutralize TMAdV ( data not shown ) . Thus , the results of our serological survey appear unlikely to be due to nonspecific cross-reactivity from prior exposure to known human adenoviruses .
In this study , we employed a pan-viral microarray assay , the Virochip , to identify a novel adenovirus associated with a fulminant pneumonia outbreak in a colony of New World titi monkeys . Despite the absence of an animal model , which precludes a strict fulfillment of Koch's postulates , there are several lines of evidence implicating this novel adenovirus , TMAdV , as the cause of the outbreak . First , conventional testing for other pathogens , including other viruses by Virochip , was negative , and affected monkeys did not respond to empiric therapy with antibiotics or antivirals ( ribavirin and oseltamivir in anecdotal use are not effective against adenoviral infections ) [30] . Second , the clinical presentation of pneumonia and hepatitis is consistent with the known spectrum of disease associated with adenoviral infections . Third , TMAdV sequence was recovered by PCR in various body fluids and tissues from affected monkeys , including blood , respiratory secretions , and lung/liver tissue ( Table 1 ) . Fourth , the finding of intranuclear inclusions in diseased tissues , as well as direct visualization of adenoviral-like particles ( TMAdV ) in lung alveoli by electron microscopy ( Figs . 1D-2 to 1D-4 ) , support a primary role for TMAdV in the pathogenesis of tissue injury in affected monkeys . Finally , there was a significant neutralizing Ab response in surviving animals , with 2 monkeys having titers undetectable prior to the outbreak but rising to >1∶512 at convalescence ( Fig . 6 ) . Although TMAdV retains the core genomic features common to all adenoviruses ( Fig . 2C ) , phylogenetic analysis clearly places TMAdV within a separate branch , with no closely related neighbors ( Figs . 3 and S1 ) . A phylogenetic distance of >10% combined with the lack of cross-neutralization defines TMAdV as a new species [31] . Since emerging adenovirus strains such as HAdV-14 and HAdV-D22/H8 ( otherwise known as HAdV-D53 ) are known to arise from recombination events among related ancestral strains [32] , [33] , we performed bootscanning analysis to look for such events in TMAdV . The bootscanning analysis , however , failed to show evidence of recombination , likely because closely related and/or ancestral strains to TMAdV have not yet been identified . Entry of adenoviruses into cells involves an initial attachment of the fiber knob to the cell receptor , followed by internalization via a secondary interaction of the penton base with αv integrins [34] , [35] . The presence of an RGD motif in the TMAdV penton base implies that the virus uses αv integrins for internalization [35] . However , the high sequence divergence in the fiber protein ( Table 2 ) , as well as the absence of fiber motifs conserved among adenoviruses that bind CAR [36] , [37] ( coxsackievirus-adenovirus receptor ) or CD46 [38] , [39] , [40] ( data not shown ) , suggest that neither of these two human adenoviral receptors may be the attachment receptor for TMAdV . Further studies will be necessary to identify the preferred cellular attachment and internalization receptors for TMAdV . Despite its isolation from affected titi monkeys , we were unable to propagate TMAdV in both established ( BSC-1 ) and primary ( PMK ) monkey kidney cells ( Fig . 4 ) . The virus , however , grew efficiently in a human A549 lung adenocarcinoma cell line . One explanation for this finding is that TMAdV may be unable to productively infect cells derived from Old World monkeys ( e . g . rhesus and African green monkeys ) . An alternative possibility is that successful propagation of TMAdV may depend on infection of a specific host cell type , such as A549 lung , and not BSC-1 or PMK kidney cells . Nevertheless , after 10 passages in human A549 cells , the fully adapted strain of TMAdV exhibits an extended host range with the ability to productively infect both monkey and human cells . This observation implies that TMAdV possesses an inherent capacity to cross the species barrier and infect both humans and nonhuman primates . Efforts to identify host range and cell tropism of TMAdV , as well as the specific sequence changes responsible for adaptation to growth in cell culture , are currently underway . The virulence of TMAdV in healthy and apparently immunocompetent titi monkeys ( 83% case fatality rate ) is highly unusual for infections by adenovirus . In humans , deaths due to adenovirus infections or outbreaks are generally low ( up to 18% for pneumonia associated with HAdV-14 [4] ) . Furthermore , severe infections from human adenoviruses are more commonly associated with older age , immunosuppression , and chronic underlying conditions such as kidney failure [4] , [41] . Young , healthy individuals are in general much less likely to succumb to adenoviral-related illness . The severity of TMAdV-related illness in affected titi monkeys suggests that this species of monkey may not be the natural host for the virus . The failure to detect fecal shedding of TMAdV in convalescent or asymptomatic animals also suggests that the virus does not normally infect titi monkeys ( Table 1 ) . Although the exact origin of TMAdV remains unclear , we can speculate on several possibilities . One possibility is that a cross-species “jump” from captive macaques to a susceptible colony of titi monkeys precipitated the outbreak . As there have been no new introductions of monkeys into the closed colony for the past 2 years , this conjecture relies on asymptomatic infection and transmission of TMAdV in the captive rhesus/cynomolgus macaque population at the CNPRC . CNPRC personnel who visited macaque areas would occasionally enter titi rooms with no change in personal protective equipment , thus providing a potential route of transmission for the virus . In addition , specific antibodies were detected in 1 of 36 ( 2 . 8% ) asymptomatic rhesus macaques housed in the same building ( Fig . 6 ) , indicating that TMAdV has the capacity to infect this species of Old World monkey . Notably , the closest identified phylogenetic relative to TMAdV among the complete genomic sequences available in GenBank is a rhesus monkey adenovirus , SAdV-3 ( Fig . 4; Table 2 ) . Furthermore , serological evidence for cross-species adenoviral transmission events between different nonhuman primate species has been previously reported in the literature [42] . Although we failed to detect TMAdV in rodent droppings found near titi monkey cages ( Table 2 ) , it is still possible that the virus arose from an unknown animal reservoir . In this regard , the high sequence divergence of TMAdV relative to the known human/simian adenoviruses ( Fig . 3 ) , and comparable sequence similarity in the polymerase gene to a porcine adenovirus ( Figs . 3 and S1 ) are striking . The four-week interval between the index case and the second case appears overly long given a typical incubation period for adenovirus infections of no more than 1 week [43] . This may be explained by our finding of a high rate of subclinical infection by TMAdV in asymptomatic titi monkeys ( 35% ) , but may also be due to separate introductions of TMAdV into the colony from an as-yet unidentified reservoir . Our study data also support the potential for cross-species transmission of TMAdV between monkeys and humans . The researcher's fever , cough , and pleuritic symptoms ( “burning sensation in the lungs” ) are consistent with the development of a prolonged viral respiratory illness . Interestingly , pleurisy has been specifically reported in association with certain human adenovirus infections [44] . The clinical presentation , time of illness concurrent with the onset of the outbreak , and presence of neutralizing Abs in convalescent serum all strongly point to primary infection of the researcher by TMAdV . The detection of weakly neutralizing Abs ( 1∶8 ) in a serum sample from a sick family member of the researcher also suggests that TMAdV may be capable of human-to-human transmission . The decreased levels of neutralizing Abs to TMAdV in the researcher ( 1∶32 ) and a family member ( 1∶8 ) relative to those in infected titi monkeys ( up to >1∶512 ) are consistent with a recent study showing much higher levels of neutralizing antibodies in chimpanzees than in humans with adenovirus infections , possibly due to more robust adenovirus-specific T-cell responses in humans than in monkeys [45] . Several lines of evidence support the contention that the direction of TMAdV transmission was zoonotic ( monkeys to humans ) rather than anthroponotic ( humans to monkeys ) . First , the closest known relative to TMAdV in GenBank is SAdV-3 , an Old World monkey adenovirus ( Fig . 3; Table 2 ) . Second , our results show that PCR assays for human adenoviruses in common use are capable of detecting TMAdV . Although sequencing of PCR amplicons for human adenoviruses is not performed routinely in diagnostic virology , TMAdV would presumably have been detected previously in large-scale studies of hexon sequencing of Ad field isolates if it were circulating in the community [46] , [47] . Finally , the available sequence data in GenBank is heavily biased towards human adenoviruses , and much less is known about the potential diversity of the simian adenoviruses . We also cannot formally exclude the possibility that the outbreak arose from anthroponotic transmission . In our study , 2 of 81 , or 2 . 5% of random adult blood donors exhibited borderline titers of neutralizing antibody to TMAdV , indicating either a low prevalence of TMAdV in the human population or cross-reactivity to a related virus ( although no evidence of cross-reactivity was found with HAdV serotypes 1 through 35 ) . Future large-scale studies of TMAdV seroepidemiology will be needed to better understand transmission of TMAdV between monkeys and humans . Nevertheless , our discovery of TMAdV , a novel adenovirus with the capacity to cross species barriers , highlights the need to monitor adenoviruses closely for outbreak or even pandemic potential .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The use and care of all animals followed policies and guidelines established by the University of California , Davis Institutional Animal Care and Use Committee ( IACUC ) and CNPRC ( Animal Welfare Assurance #A3433-01 ) . The protocol for the maintenance and breeding of the titi monkey colony was approved by the University of California , Davis IACUC ( Protocol #15730 ) . No specific animal research protocol was drafted for this study , as only excess clinical samples were analyzed for diagnostic purposes . Animals in extreme respiratory distress were humanely euthanized by veterinarians . Extensive veterinary care was provided to all animals affected by the outbreak in order to minimize pain and distress . Serum samples from staff at the CNPRC , close contacts , and random adult blood donors were collected under protocols approved by institutional review boards of the University of California , Davis ( Protocol #200917650-1 ) and University of California , San Francisco ( Protocol #H49187-35245-01 ) . Specifically , written informed consent was obtained from staff at the CNPRC and close contacts for analysis of their samples . Any potentially identifying information has been provided with the explicit permission of the individuals involved . Sera from random blood donors were obtained from the Blood Systems Research Institute ( San Francisco , CA ) ; sera were derived from affiliated donor banks in California ( Blood Centers of the Pacific , San Francisco , CA ) , Nevada ( United Blood Service , Reno , NV ) , and Wyoming ( United Blood Services , Cheyenne , Wyoming ) and de-identified prior to analysis . The California National Primate Research Center ( CNPRC ) , which houses over 5 , 000 nonhuman primates , is a part of the National Primate Research Centers Program and is accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care , International ( AAALAC ) . At the beginning of 2009 , the CNPRC maintained a colony of 74 titi monkeys ( Callicebus cupreus ) and a colony of over 4 , 500 rhesus macaques ( Macaca mulatta ) . No new animals have been introduced into either colony for over 2 years . All titi monkeys are maintained in small social groups , while rhesus macaques are maintained in small or large social groups . All animal facilities are maintained in compliance with United States Department of Agriculture specifications . Eighty-eight percent of the titi monkey population ( n = 65 ) were housed in 1 quadrant of an indoor animal building , and all titi monkeys demonstrating clinical signs originated from this building ( i . e . “at-risk” room ) ( Fig . 1A ) . Rhesus macaques ( n = 133 ) were housed in the other 3 quadrants of this same building , and surrounding the building were outdoor housing units with rhesus macaques and cynomolgus macaques ( Macaca fasicularis ) . Three additional titi monkeys were moved into the at-risk room less than 2 weeks after presentation of the index case , reflecting a total at-risk population of 68 animals . The remaining 6 titi monkeys were housed in an indoor animal building greater than 500 yards from the at-risk population ( i . e . “minimal-risk” room ) . The outbreak lasted approximately 3 months from May to August of 2009 . Affected titi monkeys died from 3–24 days after appearance of clinical signs , with an average time to death or humane euthanasia of 8 days . Clinical and epidemiological data , including daily census reports , were tracked and recorded by veterinary and management staff . All personnel entering the titi monkey rooms ( both at-risk rooms and minimal-risk rooms ) needed to pass within approximately 20 feet of macaque enclosures prior to entry . CNPRC personal protective equipment ( PPE ) policy requires a change of PPE between entrance/exit of animal rooms housing different species . Staff compliance of this policy may have been compromised . Measures have since been taken by CNPRC management to ensure compliance with existing policies . Bacterial , mycoplasma , and fungal cultures were performed at the CNPRC . Clinical samples were also sent to an outside laboratory ( Focus Diagnostics , Cypress , CA ) for respiratory viral testing by centrifugation-enhanced shell vial culture followed by direct fluorescent antibody staining for 8 viruses ( respiratory syncytial virus , adenovirus , influenza virus A and B , parainfluenza virus types 1 , 2 , and 3 , and human metapneumovirus ) . Gross and histopathological analyses of post-mortem tissues were performed by a board-certified veterinary pathologist specializing in nonhuman primate/laboratory animal medicine , a branch of Primate Services at the CNPRC . At necropsy , tissue samples from the trachea , lung , and liver were collected and fixed in 10% formalin . Tissues were routinely processed and embedded in paraffin . 3-µm sections were stained with hematoxylin and eosin ( HE ) and examined by light microscopy . For transmission electron microscopy , tissue fragments ( 2×2 mm ) were excised from paraffin blocks of lung , deparaffinized , and processed as previously described [48] . Total nucleic acid was extracted from body fluid or swab samples using commercially available kits ( Qiagen , Valencia , CA ) . 200 µL of sample were passed through a 0 . 22 µm filter ( Millipore , Temecula , CA ) to remove bacteria and cellular debris and then treated with Turbo DNase ( Ambion , Culver City , CA ) to degrade host genomic DNA prior to extraction . For tissue samples , lung or liver tissue was homogenized in a 15 mL Eppendorf tube using a disposable microtube pestle ( Eppendorf , San Diego , CA ) and scalpel , and RNA extraction was then performed using TRIzol LS ( Invitrogen , Carlsbad , CA ) , followed by isopropanol precipitation and two washes in 70% ethanol . Extracted nucleic acid was amplified using a random PCR method to generate cDNA libraries for Virochip and deep sequencing analyses as previously described [18] , [21] . The current 8×60 k Virochip microarrays used in this study contain 19 , 058 70mer probes representing all viral species in GenBank , and combine probes from all previous Virochip designs [17] , [18] , [21] , [23] . Four probes derived from 2 different Adenoviridae genera ( SAdV-23 , PAdV-A , HAdV-5 , and FAdV-D ) yielded an adenovirus signature on the Virochip that was found to be TMAdV . With the exception of SAdV-23 , these highly conserved probes are part of the core Virochip design and were derived from all available adenoviral sequences in GenBank as of 2002 [21] . One explanation why more high-intensity probes to simian adenoviruses were not seen by Virochip analysis is that the genomes of many simian Ads , including SAdV-3 and SAdV-18 ( the two closest phylogenetic relatives to TMAdV in GenBank ) , were not sequenced until after 2004 [7] , [49] , and thus their genomes are not as well-represented on the Virochip microarray . Virochip analysis was performed as previously described [21] , [23] . Briefly , samples were labeled with Cy3 or Cy5 fluorescent dye , normalized to 10 pmol of incorporated dye , and hybridized overnight using the Agilent Gene Expression Hybridization kit ( Agilent Technologies , Santa Clara , California ) . Slides were scanned at 3 µm resolution using an Agilent DNA Microarray Scanner . Virochip microarrays were analyzed with Z-score analysis [18] , hierarchical cluster analysis [50] , and E-Predict , an automated computational algorithm for viral species prediction from microarrays [51] . Only Z-score analysis , a method for assessing the statistical significance of individual Virochip probes , yielded a credible viral signature on the microarray . We initially used consensus primers derived from a highly conserved region of the hexon gene to confirm the Virochip finding of an adenovirus by PCR [25] . After recovering the full genome sequence , we then designed a set of specific PCR primers for detection of TMAdV , TMAdV-F ( 5′-GTGACGTCATAGTTGTGGTC ) and TMAdV-R ( 5′-CTTCGAAGGCAACTACGC ) . The TMAdV-specific quantitative real-time PCR was performed on a Stratagene MX3005P real-time PCR system using a 25 µL master mix consisting of 18 µL of water , 2 . 5 µL of 10X Taq buffer , 1 µL of MgCl2 ( 50 mM ) , 0 . 5 µL of deoxynucleoside triophosphates ( dNTPs; 12 . 5 mM ) , 0 . 5 µL of each primer ( 10 µM ) , 0 . 5 µL SYBR green , 0 . 5 µL of Taq polymerase ( Invitrogen , Carlsbad , CA ) , and 1 µL of extracted nucleic acid . Conditions for the PCR reaction were 40 cycles of 94°C for 30 s , 55°C for 30 s , and 72°C for 30 s . Amplicons were purified on a 2% agarose gel , cloned into plasmid vectors using TOPO TA ( Invitrogen , Carlsbad , CA ) , and sent to an outside company ( Elim Biopharmaceuticals , Hayward , CA ) for Sanger sequencing in both directions using vector primers M13F and M13R . To assess linearity and limits of sensitivity for the TMAdV PCR assay , 12 serial log dilutions were made of a standard plasmid constructed by cloning the 157-bp TMAdV amplicon into a TOPO plasmid vector . Purified plasmid clones at each serial dilution were quantified using a Nanodrop spectrophotometer and then spiked into negative serum , stool , or oral swab sample matrix , each matrix consisting of a pool of 10 sera , 10 stool samples , or 3 oral swabs , respectively . For each sample type , a standard curve for the TMAdV PCR assay was calculated from 3 PCR replicates at each dilution of nucleic acid extracted from the spiked matrix ( data not shown ) . To determine limits of sensitivity for the assay , probit analysis of results from 6 PCR replicates of 7 serial log dilutions ( from a starting concentration of ∼1 . 2×105 copies/mL ) was performed using SPSS 16 . 0 ( SPSS Inc . , Chicago , IL ) . By probit analysis , the 95% limit of detection for TMAdV was 781 , 377 , or 35 viral genome equivalents/mL for serum , stool , or oral swab samples , respectively ( data not shown ) . To facilitate whole-genome sequencing of TMAdV , we prepared amplified cDNA/DNA libraries for deep sequencing from lung tissue and a lung swab sample from 2 different monkeys using previously published protocols [23] , [52] . Briefly , randomly amplified libraries were cleaved with a Type IIs restriction endonuclease ( GsuI ) and truncated adapters were ligated on the resulting strand ends . Full-length adapters containing strict 6-nt barcodes were added via an additional 15 cycles of PCR . Amplified libraries were size-selected on a 2% agarose gel at approximately 350 bp average length and then sent to an outside company ( Elim Biopharmaceuticals , Hayward , CA ) for deep sequencing on an Illumina Genome Analyzer IIx ( Illumina , San Diego , CA ) . Paired-end reads were sequenced for 73 cycles in each direction . Paired-end reads were subsequently filtered to eliminate low-complexity sequences with a Lempel-Ziv-Welch ( LZW ) compression ratio below 0 . 4 [53] , split into individual reads , classified by barcode , and stripped of any remaining primer sequences using BLASTN alignments ( word size = 11 , E-value = 1×10−5 ) . After low-complexity filtering and barcode/primer trimming , 11 , 950 , 557 sequence reads remained , with each read consisting of 67 nucleotides , for a total of ∼800 megabases of sequence . Reads were then aligned using BLASTN ( word size = 11 , E-value = 1×10−5 ) and TBLASTX ( word size = 11 , E-value = 1×10−5 ) to the genome sequence of SAdV-18 ( Fig . 2B ) . Overlapping reads aligning to SAdV-18 were used to assemble portions of the TMAdV genome with Geneious software ( version 3 . 6 . 5 ) [54] , employing the SAdV-18 genome as a reference sequence and requiring a 20-bp minimum overlap and 95% overlap identity . Aligning reads were also used to design PCR primers to close remaining gaps in the TMAdV genome . Amplicons derived from specific TMAdV PCR primers were gel-purified , cloned , and sequenced as described above . The 5′ end corresponding to the inverted terminal repeat ( ITR ) of TMAdV was obtained by PCR using a forward degenerate consensus primer and a reverse TMAdV-specific primer . The 3′ end was recovered using a forward primer near the 3′ end of the genome and a reverse primer derived from 5′-ITR sequence . To identify predicted coding regions in the TMAdV genome , we used the fully annotated genome sequence of SAdV-21 in GenBank as a reference . First , we aligned the two genomes and identified all ORFs that were present with Geneious [54] . We then selected the candidate ORF that best matched the corresponding ORF in the annotated reference genome . For adenovirus genes that are spliced ( e . g . E1A ) , the identification of a GT-AG intron start-stop signal was used to pinpoint the correct ORF . To confirm the accuracy of the coding sequence , the sequence of each identified ORF was aligned to a database containing all adenoviral proteins in GenBank by BLASTX . To generate whole-genome and individual gene nucleotide phylogeny trees , all 95 fully sequenced unique adenovirus genomes were first downloaded from GenBank . Multiple sequence alignments were then performed on a 48-core Linux system using ClustalW-MPI [55] . Trees were constructed after bootstrapping to 1000 replicates by the neighbor-joining method ( based on Jukes-Cantor distances ) in Geneious [54] , [56] . Pairwise alignments were calculated using Shuffle-LAGAN ( window size , 400 bp; step size 40 bp; translated anchoring ) , a glocal alignment algorithm that is able to calculate optimal alignments by using both local alignments and global maps of sequence rearrangements ( e . g . duplications of the fiber gene in adenovirus genomes with 2 fibers ) [57] . Sliding window analysis of the Shuffle-LAGAN pairwise alignments was performed using the online mVISTA platform [58] . More accurate alignments were obtained with Shuffle-LAGAN than with either ClustalW-MPI or Geneious ( data not shown ) . Bootscanning analysis was performed according to the Kimura 2-parameter method using 1000 replicates with Simplot ( version 3 . 5 . 1 ) [59] . Pairwise amino acid amino acid alignments between predicted TMAdV proteins and corresponding proteins in other adenoviruses ( Table 2 ) were performed using Geneious [54] . A549 ( human lung adenocarcinoma ) and BSC-1 ( African green monkey kidney epithelial ) cell lines as well as PMK ( primary rhesus monkey kidney ) cells are routinely maintained at the Viral and Rickettsial Disease Laboratory ( VRDL ) branch of the California Department of Public Health . Media consisting of Hank's medium ( for A549 cells ) or Dulbecco's modified Eagle's medium ( DMEM ) ( for BSC-1 cells ) were supplemented with 1×nonessential amino acids ( Invitrogen , Carlsbad , CA ) , 10% fetal bovine serum , 100 U of penicillin/mL and 100 µg of streptomycin/mL . PMK cells were maintained in tubes containing growth media and antibodies to SV-40 and SV-5 polyomaviruses ( Viromed , Pasadena , CA ) . Clinical samples were clarified by centrifugation for 10 min×4000 g and passaged through a 0 . 2-µm filter . Cell culture passages were subjected to 3 freeze-thaw cycles and clarified as above . After achieving 80–90% confluency , cell culture media were changed to maintenance media with 2% FBS and were inoculated with 200 µL of clinical sample or 100 µL of passaged viral supernatant . Viral replication was monitored over 14 days by visual inspection under light microscopy for cytopathic effect ( CPE ) . To confirm the generation of infectious virus , viral supernatants were quantitated by an end-point dilution assay . A virus stock of TMAdV ( passage 7 ) was produced on human A549 cells , aliquoted , and quantitated by end-point dilution . To perform the virus neutralization assay , 55 µL of viral supernatant at a concentration of 100 TCID50 and 55 µL of serum ( starting at a 1∶8 dilution ) were mixed and incubated for 1 hour at 37°C . As a control for each serum sample , 55 µL of culture media and 55 µL of serum were mixed and treated in an identical fashion . While mixtures were incubating , A549 cells grown in T-25 plates were trypsinized and 4 , 000 cells in 100 µL of media were added to each well of a 96-well plate . After incubation , 100 µL of mixture were inoculated into appropriate wells containing 4 , 000 cells per well and the entire plate was placed in a 37°C 5% CO2 incubator . Cells in the plate wells were observed for evidence of CPE every other day for 1 week . For wells that showed inhibition of viral CPE , the corresponding serum samples were diluted in six 2-fold steps and then retested . The reciprocal of the highest dilution that completely inhibited viral CPE was taken as the neutralizing antibody titer . To assess cross-neutralization of TMAdV by known human adenoviruses , 7 pools of in-house reference sera at the VRDL ( rabbit hyperimmune sera ) and collectively containing antibodies to human adenovirus serotypes 1 through 35 were available for testing . For each pool , 55 µL of rabbit sera and 55 µL of viral supernatant at a concentration of 100 TCID50 were mixed , incubated for 1 hour at 37°C , and inoculated onto A549 cells in wells of a 96-well plate as described above . Cells in the plate wells were observed for evidence of CPE every other day for 1 week . All Virochip microarrays used in this study have been submitted to the NCBI GEO database ( study accession number GSE26898; microarray accession numbers GSM662370-GSM662391; microarray design accession number GPL11662 ) . The annotated , whole-genome sequence of TMAdV has been submitted to GenBank ( accession number HQ913600 ) . Deep sequencing reads have been submitted to the NCBI Sequence Read Archive ( accession number SRA031285 ) . | Infection from adenoviruses , viruses that cause a variety of illnesses in humans , monkeys , and other animals , has conventionally been thought to be species-specific . We used the Virochip , a microarray designed to detect all viruses , to identify a new species of adenovirus ( TMAdV , or titi monkey adenovirus ) that caused a deadly outbreak in a colony of New World titi monkeys at the California National Primate Research Center ( CNPRC ) , and also infected a human researcher . One-third of the monkeys developed pneumonia and liver inflammation , and 19 of 23 monkeys died or were humanely euthanized . The unusually high death rate ( 83% ) makes titi monkeys unlikely to be natural hosts for TMAdV , and the genomic sequence of TMAdV revealed that it is very different from any other known adenovirus . The researcher developed an acute respiratory illness at the onset of the outbreak , and was found to be infected by TMAdV by subsequent antibody testing . A clinically ill family member with no prior contact with the CNPRC also tested positive . Further investigation is needed to identify whether TMAdV originated from humans , monkeys , or another animal . The discovery of TMAdV suggests that adenoviruses should be monitored closely as potential causes of cross-species outbreaks . | [
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] | 2011 | Cross-Species Transmission of a Novel Adenovirus Associated with a Fulminant Pneumonia Outbreak in a New World Monkey Colony |
Promising results have been reported for a urine circulating cathodic antigen ( CCA ) test for the diagnosis of Schistosoma mansoni . We assessed the accuracy of a commercially available CCA cassette test ( designated CCA-A ) and an experimental formulation ( CCA-B ) for S . mansoni diagnosis . We conducted a cross-sectional survey in three settings of Côte d'Ivoire: settings A and B are endemic for S . mansoni , whereas S . haematobium co-exists in setting C . Overall , 446 children , aged 8–12 years , submitted multiple stool and urine samples . For S . mansoni diagnosis , stool samples were examined with triplicate Kato-Katz , whereas urine samples were tested with CCA-A . The first stool and urine samples were additionally subjected to an ether-concentration technique and CCA-B , respectively . Urine samples were examined for S . haematobium using a filtration method , and for microhematuria using Hemastix dipsticks . Considering nine Kato-Katz as diagnostic ‘gold’ standard , the prevalence of S . mansoni in setting A , B and C was 32 . 9% , 53 . 1% and 91 . 8% , respectively . The sensitivity of triplicate Kato-Katz from the first stool and a single CCA-A test was 47 . 9% and 56 . 3% ( setting A ) , 73 . 9% and 69 . 6% ( setting B ) , and 94 . 2% and 89 . 6% ( setting C ) . The respective sensitivity of a single CCA-B was 10 . 4% , 29 . 9% and 75 . 0% . The ether-concentration technique showed a low sensitivity for S . mansoni diagnosis ( 8 . 3–41 . 0% ) . The specificity of CCA-A was moderate ( 76 . 9–84 . 2% ) ; CCA-B was high ( 96 . 7–100% ) . The likelihood of a CCA-A color reaction increased with higher S . mansoni fecal egg counts ( odds ratio: 1 . 07 , p<0 . 001 ) . A concurrent S . haematobium infection or the presence of microhematuria did not influence the CCA-A test results for S . mansoni diagnosis . CCA-A showed similar sensitivity than triplicate Kato-Katz for S . mansoni diagnosis with no cross-reactivity to S . haematobium and microhematuria . The low sensitivity of CCA-B in our study area precludes its use for S . mansoni diagnosis .
There is growing awareness , political commitment , and financial resources to control neglected tropical diseases ( NTDs ) [1]–[3] . Preventive chemotherapy , that is the repeated large-scale administration of drugs to at-risk populations , has become the key strategy for the control of several NTDs , including schistosomiasis [3]–[5] . Although the issue of diagnosis has received only token attention in the current era of preventive chemotherapy , its importance must be emphasized for rapid identification of high-risk communities warranting regular treatment , appraisal of drug efficacy , monitoring progress of control interventions , and improved patient management [6]–[8] . With regard to intestinal schistosomiasis due to Schistosoma mansoni and S . japonicum , the Kato-Katz technique is the most widely used diagnostic approach in epidemiological surveys [8] , [9] . Although the Kato-Katz technique is relatively simple to perform , it requires a minimum of equipment ( i . e . , microscope , chemicals , and test kit material ) and well-trained laboratory technicians [10] . Moreover , a shortcoming of the Kato-Katz technique is the only low-to-moderate sensitivity for S . mansoni diagnosis in low endemicity areas [11]–[13] . Hence , multiple Kato-Katz thick smears are required to enhance sensitivity [14] , but this poses operational challenges and strains financial resources . The detection of circulating antigen of S . mansoni in urine has been suggested as an alternative to the Kato-Katz technique [15]–[17] . Indeed , both circulating anodic antigen ( CAA ) and circulating cathodic antigen ( CCA ) can be detected in sera and urine of individuals infected with S . mansoni [18] . Both antigen-detecting assays are sensitive and specific and correlate with the presence and intensity of infection [19] . Antigen detection in urine using a rapid diagnostic test ( RDT ) based on an enzyme-linked immunosorbent assay ( ELISA ) technique is potentially useful and non-invasive and could change the management of infected individuals , particularly at the peripheral level in endemic countries where microscopes and qualified laboratory technicians are often not available [6] , [7] . A point-of-contact ( POC ) CCA urine test has been developed for the diagnosis of S . mansoni [15] , which is now commercially available as a RDT in cassette form . In view of promising results obtained thus far [17] , [20] , [21] , the Schistosomiasis Consortium for Operational Research and Evaluation ( SCORE ) initiated a multi-country study to assess the accuracy of a commercially available CCA cassette test for the diagnosis of S . mansoni . The study reported here is part of this multi-country evaluation . We assessed the accuracy of a commercially available urine CCA cassette test ( designated CCA-A ) for S . mansoni diagnosis . Additionally , we employed an experimental formulation of the test ( CCA-B ) . Nine Kato-Katz thick smears from each participant served as diagnostic ‘gold’ standard . In addition , our team employed the ether-concentration method on sodium acetate-acetic acid-formalin ( SAF ) -fixed stool samples for the diagnosis of S . mansoni , urine filtration for the identification of S . haematobium eggs , and Hemastix dipsticks for the detection of microhematuria in urine . The study was carried out in south Côte d'Ivoire , in three settings where S . mansoni is endemic at different levels , whereas S . haematobium co-exists in one of the settings .
The study protocol was approved by the institutional research commission of the Swiss Tropical and Public Health Institute ( Basel , Switzerland ) and was cleared by the ethics committees of Basel ( EKBB; reference no . 377/09 ) and Côte d'Ivoire ( reference no . 1993 MSHP/CNER ) . District health and education authorities , village chiefs , parents/legal guardians , and participating children were informed about the purpose and procedures of the study . Parents/legal guardians provided written informed consent for their children to participate . Additionally , all children assented orally . Participation was voluntary and children could withdraw at any time without further obligation . All parasitological results were coded and treated confidentially . At the end of the study , children attending the schools involved in this study were treated with praziquantel ( single 40 mg/kg oral dose ) and albendazole ( single 400 mg oral dose ) free of charge , irrespective of the child's helminth infection status [22] . In October/November 2010 , we carried out a cross-sectional survey in three epidemiological settings in the district of Azaguié , south Côte d'Ivoire . Azaguié is located approximately 40 km north of Abidjan , the economic capital of Côte d'Ivoire . The settings were selected after a pre-screening done in 10 schools . For the pre-screening , in each school , 25 children were randomly selected . All children attending grades 3–5 ( CE1 , CE2 , and CM1 ) were given a unique number , lots including all numbers were closed and placed in a box , and finally 25 lots per school were drawn . The selected children provided a single stool and a single urine sample , which were examined for S . mansoni with triplicate Kato-Katz thick smears and S . haematobium with a single filtration , respectively . Based on this pre-screening , we selected the following sites , according to SCORE guidelines: setting A , low S . mansoni endemicity ( i . e . , prevalence: 10–24% ) ; setting B , moderate S . mansoni endemicity ( prevalence: 25–49% ) ; and setting C , co-endemic for S . mansoni and S . haematobium . According to the literature , a single Kato-Katz thick smear for diagnosis of S . mansoni in low endemicity settings has a sensitivity of only 20–30% [23] , [24] . However , since our study was to be carried out in both low and moderate endemicity settings , we assumed that a single Kato-Katz thick smear has a maximum sensitivity of 60% . The sensitivity of the CCA test is reported to be 80% or higher [15] , [25] . Using these sensitivity estimates , a significance level of 5% , and a power of 80% , our sample size of complying children was calculated at 90 . Assuming a compliance of 70% for the submission of each of three requested stool samples , the number of children to be included in each study setting was at least 199 . To achieve this sample size , we selected by computer-based randomization 220 children aged 8–12 years from readily available school lists of Abbé-Begnini ( setting A ) , Azaguié Gare ( setting B ) , and M'Bromé/Makouguié ( setting C ) . The purpose and procedures of the study were explained to the village authorities , the school directors , and the teachers of the selected schools . Teachers were invited to prepare class lists , including names , sex , and age of the children attending grades 3–5 . Next , the study was explained to the children in lay terms and they were provided with an information and consent sheet with further details of the study and children and parents' rights . Children who submitted a written informed consent from their parents/guardians and assented orally themselves were given a 125 ml plastic container labeled with a unique identifier ( ID ) . Children were invited to return the containers filled with a fresh lime-sized morning stool sample the following day . Upon collection of the filled container , a new empty container was handed out for stool collection on the next day . This procedure was repeated over a week until most children had submitted a total of three stool samples . Each day , between 10:00 and 12:00 hours , participating children were provided with another empty container labeled with the respective ID for collection of urine samples . Stool and urine samples were transferred to a laboratory at the Université de Cocody and processed the same day . From each stool sample , triplicate Kato-Katz thick smears were prepared , using 41 . 7 mg templates , following standard protocols [9] . In brief , triplicate Kato-Katz thick smears were prepared on microscope slides , labeled with a child's ID plus letter A , B , or C . Slides were allowed to clear for at least 30 min before quantitative examination under a microscope by experienced laboratory technicians . The number of S . mansoni and other helminth eggs ( e . g . , Ascaris lumbricoides , hookworm , and Trichuris trichiura ) was counted and recorded for each species separately . For quality control , 10% of the Kato-Katz thick smears were re-examined by a senior technician . In addition , from the second day stool sample , ∼1 g of feces was weighed into plastic vials containing 10 ml of a SAF solution . Within 8 weeks , the SAF-fixed stool samples were processed with the ether-concentration method , following a standard protocol [12] , [26] . In brief , the stool-SAF solution was rigorously shaken and then poured through medical gauze placed on a plastic funnel into a conical glass tube . The conical tubes were centrifuged for 1 min at 500× g . Subsequently , the supernatant was discarded and 7 ml of 0 . 85% sodium chloride ( NaCl ) solution and 2–3 ml ether were added to the pellet . Tubes were closed with a rubber stopper , manually shaken for ∼30 sec and then centrifuged for 5 min at 500× g . This procedure leads to the separation of the suspension in four layers . The three top layers were discarded and the complete sediment layer was placed on a microscope slide , covered with a slip and subsequently examined under a microscope for helminth eggs ( i . e . , S . mansoni and soil-transmitted helminths ) and intestinal protozoon cysts . All urine samples were subjected to CCA-A ( batch 32727 ) on the day of sample collection . The first urine sample was additionally subjected to CCA-B ( batch 32686 ) . Both CCA urine cassette assays were obtained from Rapid Medical Diagnostics ( Pretoria , South Africa ) and performed at ambient temperature , following the manufacturer's instructions . Briefly , one drop of urine was added to the well of the testing cassette and allowed to absorb . Once fully absorbed , one drop of buffer ( provided with the CCA test kits ) was added . The test results were read 20 min after adding the buffer . In case the control bands did not develop , the test was considered as invalid . Valid tests were scored as either negative or positive , the latter further stratified into 1+ , 2+ , or 3+ according to the visibility of the color reaction . All tests were read independently by two blinded investigators and in case of discordant results discussed with a third independent investigator until agreement was reached . In addition to the CCA cassettes , each urine sample was subjected to a filtration method for S . haematobium egg counts and to a Hemastix dipstick ( Siemens Healthcare Diagnostics GmbH; Eschborn , Germany ) for microhematuria assessment on the day of sample collection . In brief , samples were shaken , and 10 ml of urine filtered through a 13-mm diameter small meshed filter ( 20 µm; Sefar AG; Heiden , Switzerland ) , which was then placed on a labeled slide and examined under a microscope for S . haematobium eggs [8] . For appraisal of microhematuria , a Hemastix dipstick was soaked in urine , left in the open air for 1 min , before scoring according to the manufacturer's instructions . Data were entered twice in a Microsoft Excel spreadsheet , transferred in EpiInfo version 6 . 4 ( Centers for Disease Control and Prevention; Atlanta , GA , USA ) and validated . Statistical analyses were done with STATA version 10 ( Stata Corp . ; College Station , TX , USA ) . Only those children who had complete data records were included in the final analysis ( i . e . , nine Kato-Katz thick smears , a single ether-concentration , three CCA-A , one CCA-B , three urine filtrations , and three Hemastix dipsticks ) . To obtain a standardized measure of infection intensity , expressed as eggs per gram of stool ( EPG ) , for each individual , we calculated the arithmetic mean S . mansoni fecal egg counts ( FECs ) from the nine Kato-Katz thick smears and multiplied by a factor 24 . Infection intensity of S . mansoni was classified into light ( 1–99 EPG ) , moderate ( 100–399 EPG ) , and heavy ( ≥400 EPG ) . Egg counts of S . haematobium were utilized to stratify into light ( 1–49 eggs/10 ml of urine ) and heavy infection intensities ( ≥50 eggs/10 ml of urine ) [4] . The strength of agreement between nine Kato-Katz thick smears and triplicate CCA-A , one CCA-B , and one ether-concentration for each endemicity setting was assessed by kappa statistics ( κ ) , as follows: κ<0 indicating no agreement , κ = 0–0 . 2 indicating poor agreement , κ = 0 . 21–0 . 4 indicating fair agreement , κ = 0 . 41–0 . 6 indicating moderate agreement , κ = 0 . 61–0 . 8 indicating substantial agreement , and κ = 0 . 81–1 . 0 indicating almost perfect agreement [27] , [28] . As proposed by the SCORE secretariat , the results from nine Kato-Katz thick smears were considered our ‘gold’ standard . We determined the sensitivity ( proportion of true-positives detected by the test ) and specificity ( proportion of true-negatives detected by the test ) of single and multiple tests . As with some of our previous work , we used a second ‘gold’ standard by considering a positive test result ( regardless of the test ) as true-positive [29] , [30] . Hence , we combined results from all tests ( i . e . , nine Kato-Katz thick smears plus triplicate CCA-A , one CCA-B , and one ether-concentration ) and therefore maximized specificity . We employed an ordinal logistic regression approach , which is an extension of the general linear model to ordinal categorical outcomes to assess the correlation between CCA-A and CCA-B color reaction categories and S . mansoni FECs . The arithmetic mean FEC of three Kato-Katz thick smears per stool sample per day served as continuous explanatory variable , whereas the color reaction of the CCA test was considered as categorical outcome . This statistical procedure was also used to compare between the CCA test results considered as categorical outcome , and different infection intensity categories of S . mansoni ( i . e . , light , moderate , and heavy ) utilized as categorical explanatory variables . A logistic regression was performed to assess the association between CCA-A and CCA-B test results , expressed as binary outcome variable ( negative/positive ) with S . haematobium egg count as continuous explanatory variable and mircohematuria as categorical explanatory variable among children without a S . mansoni infection . Non-overlapping 95% confidence intervals ( CI ) or p-values≤0 . 05 were considered as statistical significance .
Figure 1 shows the adherence of school children to provide multiple stool and urine samples for a suite of diagnostic tests for detection of S . mansoni and S . haematobium infection . Overall , 674 school children aged 8–12 years were enrolled with slightly more boys than girls ( 343 vs . 331 ) . The number of children in settings A , B and C was 234 , 220 and 220 , respectively . At least one stool or one urine sample was provided by 223 , 178 and 206 children in settings A , B and C , respectively . Overall , 465 children submitted three stool samples , which were subjected to triplicate Kato-Katz thick smears . Results from a single ether-concentration method were available for 555 children . Three CCA-A test results were available for 489 children , whereas 545 children had the first urine sample additionally subjected to a CCA-B test . Finally , three urine filtrations for S . haematobium diagnosis and three Hemastix dipstick tests for appraisal of microhematuria were done for 489 children . Results on three stool samples ( examined with nine Kato-Katz thick smears and a single ether-concentration ) and three urine samples ( examined with three CCA-A , one CCA-B , three urine filtrations and three Hemastix dipsticks ) were available from a total of 446 children . Among them 48 . 7% ( n = 217 ) were boys and the median age of the cohort was 10 years . All further analysis focused on this cohort of children . Table 1 shows the number of children examined and those positive for S . mansoni and S . haematobium , as assessed by different diagnostic approaches , stratified by study setting . As indicated in Table 2 , our ordinal logistic regression analysis showed that for an increase of S . mansoni infection intensity by 1 EPG , the likelihood of a stronger color reaction of the CCA-A ( odds ratio ( OR ) = 1 . 07 ) and the CCA-B ( OR = 1 . 03 ) is significant ( both p<0 . 001 ) . When S . mansoni FECs were not considered as continuous , but stratified according to pre-set thresholds into no , light , moderate and heavy infection intensity , we found that for each increase in infection intensity category , the likelihood of a stronger color reaction of both CCA-A ( OR = 36 . 5 ) and CCA-B ( OR = 25 . 2 ) is highly significant ( both p<0 . 001 ) . Figure 2 shows the correlation between infection intensity classes according to pre-set thresholds [22] and the percentage of infected individuals as determined by a single or triplicate CCA-A and a single CCA-B . Table 3 shows that , if only S . mansoni-negative children were included in a logistic regression analysis and adjustments were made for S . haematobium egg counts and infection intensity classes , no significant association between the CCA-A positivity rate and S . haematobium egg counts was found ( OR = 1 . 09; p = 0 . 121 ) . There was also no significant association between the CCA-A positivity rate and microhematuria classes detected ( p>0 . 05 ) . Due to the small number of children found positive with the CCA-B test no logistic regression analysis was performed .
For the rapid identification of populations at highest risk of schistosomiasis and other helminth infections that warrant preventive chemotherapy , as well as for monitoring progress of control interventions and new efforts toward elimination , assessment of drug efficacy , and improved patient management , the importance of an accurate diagnosis at the individual and population level must be emphasized [6] , [7] , [31] . The widely used Kato-Katz technique for the diagnosis of S . mansoni ( and S . japonicum ) has several shortcomings: in low endemicity settings this technique considerably underestimates the ‘true’ prevalence of infection [8] , [11] , [32]–[34] . Moreover , a minimum of equipment and well trained laboratory technicians are needed for quality results . Promising results have been reported with a CCA urine test for the diagnosis of S . mansoni in different settings [17] , [35] . Some of the previous investigations , however , lacked a rigorous diagnostic ‘gold’ standard , as CCA test results were compared with singe or duplicate Kato-Katz thick smears from one or two stool samples [21] , [36] . Within the frame of a SCORE-funded multi-country study , we have now assessed the accuracy of a commercially available CCA urine cassette assay ( CCA-A , batch 32727 ) and an experimental formulation ( CCA-B , batch 32686 ) provided by the same manufacturer and tuned to have a higher specificity , which was run in parallel with the commercially available test in three epidemiological settings of south Côte d'Ivoire . Results of the CCA tests were compared with nine Kato-Katz thick smears ( three stool samples , each subjected to triplicate Kato-Katz thick smears ) . Additionally , we performed a single ether-concentration test using SAF-fixed stool samples . The influence of S . haematobium infection and presence of microhematuria on the performance of the CCA test was determined . In all three settings , a single CCA-A showed a similarly high sensitivity than triplicate Kato-Katz thick smears from a single stool sample , but both approaches missed a considerable number of infections when considering nine Kato-Katz thick smears as ‘gold’ standard . As expected , CCA-B showed a higher specificity than CCA-A , but the sensitivity of CCA-B was considerably lower than that of CCA-A . Indeed , a single CCA-B showed a significantly lower sensitivity than a single CCA-A , and triplicate Kato-Katz thick smears , particularly in settings A and B where the endemicity of S . mansoni was lower than in setting C . We were surprised by the low sensitivity of the ether-concentration method for S . mansoni diagnosis , which warrants follow-up investigations . The CCA-A seems to be an appropriate test for the diagnosis of S . mansoni in our study area in south Côte d'Ivoire where the prevalence of S . mansoni is above 25% and no recent control efforts have been implemented . Importantly , the co-endemicity of S . haematobium did not influence the accuracy of the CCA-A for the diagnosis of S . mansoni . Additionally , a concurrent infection with soil-transmitted helminths showed no negative influence on the accuracy of the CCA urine test for S . mansoni diagnosis , confirming recent observations made by Shane and colleagues in a study done in Kenya [17] . Furthermore , our study did not reveal a significant association between CCA-A positive results and microhematuria , as determined by Hemastix dipsticks , which relaxes the manufacturer's indication that false-positive results can occur if an individual presents microhematuria . However , further studies in different settings are warranted to confirm that microhematuria or urinary tract infections are not negatively impacting on CCA test results . Also the ability of the CCA test to detect antigen of juvenile Schistosoma worms , which are not yet producing eggs , needs further investigation . Noteworthy , the sensitivity of 56 . 3% of a single CCA-A in the setting A with a S . mansoni prevalence of 32 . 9% ( based on nine Kato-Katz thick smears ) is considerably lower than the sensitivity of 96 . 3% detected with a single CCA cassette of the same manufacturer in a Kenyan setting with a similar prevalence ( 38 . 8% ) [17] . This difference might be explained by our more rigorous diagnostic approach , i . e . , triplicate instead of duplicate Kato-Katz thick smears of three consecutive stool samples as ‘gold’ standard and by working in a slightly lower endemicity area . The sensitivity of a single CCA-A for S . mansoni diagnosis increased from 56 . 3% ( setting A ) to 69 . 6% ( setting B ) and 89 . 6% ( setting C ) in parallel to increasing prevalence ( 32 . 9% to 53 . 1% and finally to 91 . 8% ) , and corresponding mean FECs ( 17 . 4 EPG to 62 . 4 EPG and finally to 482 . 8 EPG ) . These findings emphasize the impact of higher prevalences and infection intensities on the positivity rate of the CCA . The strong association between the intensity of the color reaction of the CCA-A band and S . mansoni infection intensities according to FECs by the Kato-Katz method in our studies is in line with previous reports of the CCA dipstick and cassette [37] , [38] . The results of the experimental CCA-B formulation , which has been tested on a single urine sample from all children , are suboptimal . Indeed , only low sensitivities and a poor agreement with results of the Kato-Katz method were found , particularly in the lower endemicity areas ( settings A and B ) . In our hands , despite high specificity , the CCA-B in its current formulation cannot be recommended for S . mansoni diagnosis in south Côte d'Ivoire . The following issues speak for or against the application of the CCA-A versus the Kato-Katz method in helminth control programs or public health centers: at first view , in moderate-to-high-risk communities for S . mansoni infections as found in our study in Côte d'Ivoire ( i . e . , prevalence above 25% ) , the collection of a single stool sample and its examination with triplicate Kato-Katz thick smears seems to be an acceptable approach for S . mansoni diagnosis . The advantage of the Kato-Katz method is that it can concurrently detect other helminth species , such as the three main soil-transmitted helminths ( i . e . , A . lumbricoides , hookworm , and T . trichiura ) , which is not possible with the CCA . However , the Kato-Katz method requires a minimum of equipment , including a microscope , and well trained laboratory technicians who can identify helminth species-specific eggs in the thick smears . For application of the CCA-A , no additional equipment and only a minimum of training are needed . However , it only detects S . mansoni and no concurrent soil-transmitted helminth infections . The cost of a single cassette ( approximately US$ 2 ) is currently still out of reach of people at highest risk of intestinal schistosomiasis ( i . e . , poor rural dwellers in sub-Saharan Africa ) [17] . However , the cost of triplicate Kato-Katz thick smears are likely higher than a single CCA test [10] . From a convenience and logistical point of view , the collection of urine samples for the CCA is more straightforward than collection of stool for the Kato-Katz method . Indeed , urine production is more convenient for the patient and can be done without special efforts on the spot and at the same day resulting in high compliance rates , while stool production is inconvenient and collection can render a second consultation necessary and thus further exacerbate costs [8] , [39] . The performance and sensitivity of the CCA test in low-risk communities ( prevalence below 10% ) , identified by the application of multiple Kato-Katz thick smears on stool samples collected over multiple days , remains to be elucidated . Noteworthy , our study intended to test the CCA in a setting with a S . mansoni prevalence of 10–24% as requested by SCORE . However , we observed a considerable increase in the prevalence of S . mansoni when not only applying triplicate Kato-Katz from a single stool sample as in the pre-screening , but nine Kato-Katz thick smears overall from three stool samples: the observed prevalence increased from 17% to 34% in setting A , and from 36% to 54% in setting B . Due to this rigorous diagnostic approach we ended up with higher prevalences . Retrospectively , this had to be expected , as predicted by mathematical modeling and field observations [11] , [13] . If the CCA test proves to be more sensitive than multiple Kato-Katz thick smears in settings characterized by low prevalence and intensity of S . mansoni infection intensities , it will be a most useful test . For example , in areas where intense helminth control efforts have diminished the prevalence and intensity of S . mansoni infections and control programs are focusing elimination , population screenings are necessary to identify remaining S . mansoni hot-spots for targeted anthelmintic treatment and other interventions . For these large-scale screenings the CCA-A would be an excellent tool due to its fast and easy application . We conclude that in the current study area of south Côte d'Ivoire , where the prevalence and intensity of S . mansoni are still high , partially explained by the prior lack of control efforts , the CCA-A can become a useful method for S . mansoni diagnosis in health centers at the periphery and schistosomiasis control programs . On the other hand , while the specificity of the CCA-B test was high , its current formulation cannot be recommended for S . mansoni diagnosis . Clearly , there is a need to evaluate the CCA test in settings characterized by low S . mansoni prevalences and infection intensities to assess its potential role in schistosomiasis control programs progressing toward transmission control and local elimination and for reliable individual diagnosis . | We aimed to assess the accuracy of a commercially available rapid diagnostic test for the detection of an infection with the blood fluke Schistosoma mansoni in urine . In total , 446 school children from three different settings of south Côte d'Ivoire provided three stool and three urine samples . Stool samples were examined with the widely used Kato-Katz technique and analyzed with a microscope for S . mansoni eggs . Urine samples were examined with a filtration method for S . haematobium eggs and with a rapid diagnostic test for S . mansoni that is based on detecting circulating cathodic antigens ( CCA ) . We used a commercially available test ( designated CCA-A ) and an experimental formulation ( CCA-B ) . Examination of nine Kato-Katz thick smears per child revealed a prevalence of S . mansoni in the three settings of 32 . 9% , 53 . 1% , and 91 . 8% . The sensitivity of triplicate Kato-Katz from the first stool sample was comparable to a single CCA-A ( 47 . 9–94 . 2% vs . 56 . 3–89 . 6% ) , and significantly higher than the sensitivity of a single CCA-B test ( 10 . 4–75 . 0% ) . CCA-A showed a considerably lower specificity than CCA-B ( 76 . 9–84 . 2% vs . 96 . 7–100% ) . In the settings studied in south Côte d'Ivoire , the CCA-A test holds promise for the diagnosis of S . mansoni , whereas results with CCA-B were suboptimal . | [
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] | 2011 | Accuracy of Urine Circulating Cathodic Antigen (CCA) Test for Schistosoma mansoni Diagnosis in Different Settings of Côte d'Ivoire |
Rift Valley fever virus ( RVFV ) causes severe disease in livestock concurrent with zoonotic transmission to humans . A subset of people infected with RVFV develop encephalitis , and significant gaps remain in our knowledge of how RVFV causes pathology in the brain . We previously found that , in Lewis rats , subcutaneous inoculation with RVFV resulted in subclinical disease while inhalation of RVFV in a small particle aerosol caused fatal encephalitis . Here , we compared the disease course of RVFV in Lewis rats after each different route of inoculation in order to understand more about pathogenic mechanisms of fatal RVFV encephalitis . In aerosol-infected rats with lethal encephalitis , neutrophils and macrophages were the major cell types infiltrating the CNS , and this was concomitant with microglia activation and extensive cytokine inflammation . Despite this , prevention of neutrophil infiltration into the brain did not ameliorate disease . Unexpectedly , in subcutaneously-inoculated rats with subclinical disease , detectable viral RNA was found in the brain along with T-cell infiltration . This study sheds new light on the pathogenic mechanisms of RVFV encephalitis .
Africa suffers from periodic outbreaks of Rift Valley fever ( RVF ) , a disease of both livestock animals and humans . Abnormally heavy rainfall in 2018 led to cases of RVF in animals and people in the countries of South Sudan , Uganda , Gambia , Rwanda , Kenya , and the archipelago of Mayotte [1–3] . Concern that the spread of RVFV in competent mosquito vectors could lead to emergence beyond its current endemnicity in Africa and the Arabian Peninsula has prompted the World Health Organization to include RVFV as a pathogen of concern and a priority for research and development [4] . Not all human infections with RVFV are obtained through mosquito bite; another mechanism of infection of humans with RVFV is through handling infected livestock or consuming milk or meat from sick animals [5 , 6] . Most humans infected with RVFV survive the infection but experience generalized symptoms of fever , headache , nausea , vomiting , and body pains [7] . A small number of patients develop rapidly-progressing hemorrhagic fever with significant liver necrosis , while other patients may develop meningoencephalitis [8] . Neurological signs consist of hypersalivation , confusion , coma , hallucination , and signs of meningeal irritation [9] . Both the hemorrhagic/hepatotropic and encephalitic manifestations of RVF have high mortality rates in humans ( ~50% for hospitalized patients ) [8] . Development of severe disease outcomes is associated with exposure to RVFV when handling infected animals [6 , 10] . In both laboratory animals and humans , vaccines and therapeutic drugs that can protect from hepatotropic and hemorrhagic RVF often fail to protect from neurological manifestations [11–15] . Therefore , a more detailed understanding of the neuropathogenic mechanisms of RVF is merited . Infection of adult Lewis rats with a fully virulent strain of RVFV by inhalation provides a reproducible model of lethal viral encephalitis [16] . After aerosol infection with RVFV strain ZH501 , Lewis rats develop neurological signs and are moribund within 7–8 days . Our recent study demonstrated that widespread permeability of the brain vasculature in lethally-infected rats occurred at the end of the disease process , from 5 days post-infection ( dpi ) onwards [17] . We found that RVFV was replicating within the brain prior to changes in brain vascular permeability . Previous studies have not determined what types of immune cells infiltrate the brain during the course of RVF encephalitis in rats . To address this , we will characterize the immune populations present during RVFV encephalitis using flow cytometry and fluorescent imaging . Unlike aerosol ( AERO ) exposure , infection of Lewis rats by subcutaneous ( SC ) injection of the virus results in a sub-clinical infection [16 , 18] . This is in contrast to mice , where there was no difference in survival between SC and AERO exposure routes , although AERO exposed mice developed more severe neuropathology [15] . Here we report our efforts to utilize the difference in disease outcome of Lewis rats infected by SC or AERO to shed light on the pathogenic mechanisms resulting in lethal encephalitic disease . Our main findings are that neutrophils and macrophages are the primary cell types infiltrating the brain during lethal RVFV encephalitis . When neutrophils were prevented from entering the CNS , the disease outcome after AERO infection was not altered . In comparison , subclinical disease after SC infection is associated with detectable viral RNA in the brain during the course of infection , despite no demonstrable clinical signs . This study provides important knowledge about the pathogenic events leading to lethal RVF encephalitis .
Lewis rats become infected but do not develop clinical signs of disease after SC infection with the pathogenic wild-type ZH501 strain of RVFV [16 , 18] . This is in stark contrast to what happens after AERO infection in the same strain of rat ( Fig 1A ) . Lewis rats succumb to encephalitic disease within 6–8 days after AERO infection , depending upon the dose ( LD50 = 112 pfu ) [16] . Signs of illness ( fever , weight loss and neurological signs ) begin at 5 days post-infection ( dpi ) and continue until euthanasia criteria are met [16 , 19] . In this study , we compare the course of sub-lethal ( SC ) and lethal ( AERO ) infection in Lewis rats to better understand the mechanisms separating these opposing clinical outcomes . Our previous study showed that after AERO infection of Lewis rats with 1x103 pfu of RVFV , virus progresses through the brain from the olfactory bulb posteriorly to the brain stem and spinal cord [17] . Here , we infected Lewis rats with a higher dose of RVFV ( 3x104 pfu ) and compared it to SC infection ( 1x105 pfu ) to understand viral spread through the animals after inoculation at different locations ( Fig 1B–1E ) . Each day after infection from 1–6 dpi , rats were euthanized to collect tissues ( n = 3–7 per time point ) . Viral RNA ( vRNA ) was measured by qRT-PCR in CNS and peripheral tissues . Given the higher AERO virus dose compared to the previous study , the temporal spread of virus through the CNS was compressed , although there were higher titers in the anterior CNS tissues such as the olfactory bulb ( Fig 1B ) . We hypothesized that the reason Lewis rats do not develop illness after SC inoculation is because virus replication is controlled within the periphery and does not reach the brain . Unexpectedly , we found detectable vRNA in all CNS regions of SC-inoculated rats throughout the time-course observed ( 1–6 dpi; Fig 1D ) . vRNA titers in the brains of SC-inoculated rats did not rise during the course of infection , but remained at consistent levels as compared to AERO infection , which resulted in a steady increase in vRNA in all brain regions over the duration of the experiment up to 1x106 pfu/ml equivalents . The detection of vRNA in the brains of SC-infected rats was consistent over 2 separate serial-sacrifice experiments using 3 rats/time point for each experiment ( n = 6 rats/time point ) . Because we were able to detect vRNA in all of the brain samples across all of the time points at levels 3-logs above the q-PCR cutoff suggests these are not a result of cross-contamination of the PCR reaction . Attempts to isolate infectious virus from brain cortex samples from both AERO- and SC-infected rats by passage twice on Vero cells resulted in minimal cytopathic effect ( CPE ) . In passaged samples obtained from early infection ( 1–3 dpi ) , vRNA was variably detected in the passaged cultures from both AERO- and SC-infected rats ( 2 of 9 and 1 of 9 passaged cultures were vRNA+ , respectively ) . Passaged cortex samples from SC-infected rats at later time points ( 4–7 dpi ) yielded more consistent detection of vRNA in the passaged cultures ( 7 of 12 cultures were vRNA+; 58% ) . Our previous study compared infectious virus and vRNA levels within the brains of AERO-infected rats and found infectious virus detectable by plaque assay at 5 dpi and onwards , while vRNA was detectable by 1 dpi [19] . Here , we attempted to culture infectious virus rather than plaque it , assuming that this method would be more sensitive to isolating very low levels of infectious virus . We were surprised at the difficulty culturing infectious virus from the early brain samples , particularly in the early samples from the AERO group because we can reproducibly detect substantial levels of vRNA and we can also visualize the virus by IF and IHC . Difficulty culturing may be due to the homogenization procedure , performed using an Omni tissue homogenizer , which may render low levels of infectious virus difficult to culture , whereas effects of homogenization on higher starting levels of infectious virus are not as obvious . Alternatively , culture of low levels of virus may be hampered by factors in the brain homogenate or the virus may remain cell-associated . Given that 58% of the 4–7 dpi samples from SC-infected rats were vRNA+ after passage , there appears to be virus within the brain of these animals . It is not known if this is replicating infectious virus that could reactivate at a later date and cause disease in the rats . Distribution of vRNA in cervical lymph node ( CLN ) was similar after either route of infection; both routes has detectable virus in the CLN at 1 dpi ( Fig 1C and 1E ) . vRNA was detectable in serum of SC-infected rats at 1 dpi but not until 2 dpi in the AERO-infected rats . Approximately 100-fold more vRNA was found in the liver and spleen of the AERO-infected rats compared to SC-infected . To compare differences in disease course between SC and AERO exposure , whole blood was analyzed by complete blood count ( CBC ) analysis and flow cytometry ( S3 Fig ) . A comparison of parameters obtained from both techniques showed congruence and validation for both analysis methods . Total white blood cell ( WBC ) numbers did not significantly differ from pre-infection ( baseline ) after either infection route ( Fig 2A ) , but there were changes in specific cell populations over time . Thrombocytopenia was sustained after AERO but not SC infection ( Fig 2B ) . Unlike AERO-infection , granulocytosis was limited after SC infection ( Fig 2C and 2D ) . Lymphopenia ( measured by both methods ) occurred by 1 dpi through 5 dpi in both groups , but the SC-infected rats returned to baseline levels quicker while AERO-infected rats only partially recovered . Lymphopenia and granulocytosis are documented findings during lethal RVF infection , in both animal models and human clinical samples [8 , 19–22] . These data provide a direct comparison of changes in the peripheral blood between SC vs AERO infection routes and also serve to validate both the CBC analysis and flow cytometry as complementary methods for blood cell typing in rats . Leukocytes were isolated from rat brain hemispheres harvested each day after infection to determine the phenotype and timing of infiltrating cells by flow cytometry . Expression levels of CD45 distinguishes resting , resident microglia ( CD45med ) from activated microglia or peripheral leukocytes ( CD45hi ) [23] . In a normal , uninfected rat brain , two CD45+ populations are distinguishable , with the majority being CD45med phenotype ( Fig 3A , left panel ) . In contrast , the brain from an AERO-infected rat at end-stage disease contains many CD45hi cells , and they are more granular and complex ( larger SSC-A ) ( Fig 3A , right panel ) . SC-infected rat brains harvested at 7 dpi were of an intermediate phenotype; both CD45 populations were detectable ( Fig 3A , middle panel ) . Using total CD45+ cells , we characterized peripheral macrophages infiltrating the CNS as CD163+ , neutrophils as RP-1+ CD11b+ , and microglia as Iba-1+ ( S4 Fig ) . After live-dead exclusion , vital brain cell gating , and singlet inclusion , all parameters are expressed as the number of cells per gram of brain tissue based on back calculating cell counts using a hemocytometer with the percentage of total CD45+ cells . Upon examination of brain samples harvested daily over the entire time course , from 1–7 dpi , the total live cell counts increased during the course of infection in AERO-infected rats ( Fig 3B ) . Unexpectedly , the AERO-infected rats had an early transient increase in CD45+ cell numbers on 1 dpi comprised of both neutrophils and macrophages , possibly suggesting proliferation of resting microglia and early leukocyte entry to the CNS may be detrimental to the clinical outcome ( Fig 3D–3F ) . After 1 dpi , the number of cells in AERO-infected brains remained near pre-infection levels until a major increase in cells at 5 dpi and after . This corresponds to increased vascular permeability observed in AERO-infected Lewis rats from 5 dpi onwards in our previous study [17] . The cells in end-stage AERO-infected brains were primarily CD45hi ( 10-fold overall increase from baseline ) and consisted predominantly of neutrophils ( 250-fold change ) and macrophages ( 5-fold change ) , with very little change in T-cell numbers . The CD45hi cells may be macrophages infiltrating from the periphery or resident brain microglia that became activated and increased CD45 expression . Due to the subclinical disease , we did not expect to see leukocyte infiltration into the brains of SC-infected rats . This not the case , as we observed influx of cells into the CNS of SC-infected rats , albeit not as great as was seen with AERO-infected rats . There was a slight increase in CD45hi cells into the SC-infected brains that was significant at 7 dpi ( Fig 3C ) . There was not an early change in either CD45med or CD45hi cells at 1 dpi as was seen in the AERO infected rats , nor was there a dramatic increase in neutrophils nor macrophages at 6–7 dpi . There was , however , a sharp increase in T-cells ( both CD4 and CD8 ) at 6 dpi ( Fig 3G–3I ) . Taken together , immune infiltration into the brain was observed after both SC and AERO infection , but the AERO-infected rats had a more dramatic infiltration of neutrophils and macrophages at end-stage disease after the vasculature became permeable [17] . Conversely , a late T-cell infiltration as associated with rats that survive SC infection . Inflammatory cytokine expression occurs within the sera and brains of AERO-infected rats that die of encephalitis [19] . We used a multiplex cytokine panel to compare samples from AERO and SC-infected rats to provide insights as to differential cytokine responses that are associated with non-lethal disease . Within the sera of SC-infected rats , we found elevated levels of the Th2 cytokines IL-5 and IL-13 , the Th17 cytokine IL-17A , and TNF-α ( Fig 4A ) . AERO-infected rats had no significant changes in any of these cytokines in the serum . However , the brains of AERO-infected rats had high levels of inflammatory chemokines IL-1α , IL-1β , Gro/KC , MCP-1 , MIP-1α , and MIP-1β end stage disease ( Fig 4B ) . These data are similar to what we observed in a monkey model of RVF encephalitis , where an early cytokine response in the serum was associated with survival , whereas late cytokine storm in the brain occurred during lethal ( AERO ) disease [20] . To determine the in vitro susceptibility of CNS cell types to RVF infection , human neurons ( SH-SY5Y ) , human microglia ( HMC3 ) , rat microglia ( HAPI ) , and Vero cells ( for comparison ) were infected at a multiplicity of infection ( MOI ) of 1 . 0 . Viral growth over time was determined by qRT-PCR and viral plaque assay over 48 hours . SH-SY5Y were either undifferentiated ( immature ) or differentiated with retinoic acid . RVFV replicated to high levels in each cell line , with immature SH-SY5Y cells producing the highest titers by 48hpi ( Fig 5A ) . There was a 4-log spread of virus titers by both assays across the different cell lines by 48 hpi . This emphasizes the broad tropism of RVFV and its ability to replicate in different cell types including microglia and neurons . The immature SH-SY5Y cells were significantly more permissive for infection and virus production than the differentiated neurons , indicating that differentiation status may play a role on virus tropism . We developed an intracellular flow cytometry method to identify infected cells using a monoclonal antibody to the viral Gn glycoprotein . This method was validated using RVFV-infected Vero cells and other permissive CNS cell lines ( Fig 5B–5D ) . The Gn-specific antibody was able to detect viral antigen within each cell type based on median fluorescent intensity ( MFI ) ( Fig 5B–5D ) . For the remainder of this study , we focused on AERO-infected rats . Intracellular flow cytometry was used to detect viral antigen within freshly obtained leukocytes from AERO-infected rat brains at 1 , 4 , and 7 dpi ( Fig 6 ) . We isolated brain leukocytes as described above , performed live/dead , singlet inclusion , and vital brain cell gating , followed by gating on Iba-1+ cells ( S2 Fig ) . CD45 expression was used to distinguish resting microglia ( CD45med ) from activated microglia ( CD45hi ) ( Fig 6A ) . Viral antigen was detectable in Iba-1+CD45med cells , Iba-1+CD45hi cells , and neutrophils by 7 dpi ( Fig 6B and 6D ) , at which point nearly all of the Iba-1+ cells contained viral antigen . Additionally , the CD45hi cells were of increased complexity as measured by SSC-A ( Fig 6A ) , suggesting a morphological distinction from those events in the CD45med gate . This change may be the result of microglia changing from a ramified state to an ameboid state , which occurs upon microglial activation [24] . We used immunofluorescence and confocal microscopy to confirm the immune cell infiltration and infected cells within the olfactory bulb and cerebral cortex of AERO-infected rats . vRNA was detected using an in situ hybridization probe ( RNAscope ) specific for a region within the RVFV N protein . At 1 dpi , vRNA appeared within the glomerular layer of the olfactory bulb and cortex ( Figs 7 and 8 ) . Detection of vRNA increased between 3 and 7 dpi originating within the glomerular cell layer and gradually expanding into the mitral and granule cell layers of the olfactory bulb ( Fig 7A ) . The first evidence of detectable infection of neuronal cell bodies occurred at 3 dpi in the olfactory bulb ( Fig 7B , yellow cells represent colocalization of green Neurotrace and red vRNA signal ) . Within the olfactory bulb , initial infection of neurons was contained to single cells within the glomerular layer , indicating limited viral dissemination detectable by this methodology during early infection ( Fig 7A ) . By 5 dpi , the neurons lining the mitral cell layer co-localized more frequently with vRNA and by 6–7 dpi , the entirety of the remaining neuronal population was positive for vRNA . Neurotrace and vRNA was found within Iba-1+ cells by 6–7 dpi , highlighting extensive neuronal death and phagocytosis of debris by the microglia ( Fig 7A and 7B ) . In the cortex , virus was primarily extra-neuronal until 5 dpi , after which virus-infected neurons were evident . By 7 dpi , the vRNA staining appeared fragmented indicating massive cell death ( Fig 8 ) . Overall , the frequency of Iba-1+ cells was elevated in both olfactory bulb and cortex at all points after infection compared to an uninfected brain ( note increased visualization of white microglia in Figs 7 and 8 ) , reflecting possible microgliosis in response to infection . By 4–7 dpi the Iba-1+ cell numbers visually decreased , and remaining Iba-1+ cells , particularly in the olfactory bulb , exhibited the larger , ameboid cell body with few projections compared to the ramified structure of quiescent microglia . These data are congruent with flow cytometry results in Fig 3D . A second immunofluorescence staining panel was used to visualize leukocyte infiltration within rat brains . Myeloperoxidase ( which identifies neutrophils ) , CD45 , and Iba-1 were used to phenotype leukocytes . Data from Fig 3 suggested a possible early influx of leukocytes at 1 dpi that was not associated with massive breakdown of the blood brain barrier [17] . Here , we confirmed early CD45+ cells in the glomerular layer of the olfactory bulb and the surface of the cortex at 1 dpi ( Fig 9A and 9B; Fig 10 ) ; this is congruent with the flow cytometry results in Fig 3 . By 5 dpi , extensive immune cell infiltration was found in both the olfactory bulb and cortex , which fits with our previous study that found breakdown of the brain vasculature at 5 dpi onward [17] . The early CD45+ cell infiltration at 1 dpi also occurs at the same time that we detected the presence of vRNA ( Fig 7 ) . Myeloperoxidase ( MPO ) is an antimicrobial enzyme expressed primarily by neutrophils and can serve as an effective marker for the presence of neutrophils in tissues . MPO+ cells were found in the cortex , but not olfactory bulb , as early as 1 dpi ( Fig 10 ) , with the number of MPO+ cells increasing from 4 dpi onwards . MPO+ cells were first detectable in the olfactory bulb at 5 dpi , corresponding to an increase in overall CD45+ cells ( Fig 9 ) . The arrival of MPO+ cells in both the olfactory bulb and cortex by 4–5 dpi coincided with the breakdown of brain vascular integrity [17] and visualization of amoeboid , non-ramified Iba-1+ cells ( likely a combination of primarily activated microglia with some infiltrating macrophages; Fig 3 ) . Taken together , our data suggest early leukocyte infiltration together with transient increased permeability may play a role in the pathogenesis of RVFV-induced encephalitis . Given the extent of neutrophil infiltration and the levels of inflammatory cytokines and chemokines found in the brain of AERO-infected rats , we hypothesize that neutrophils may play a pathogenic role in lethal RVF encephalitis . To prevent neutrophil migration into the CNS , we used a CXC chemokine receptor 2 ( CXCR2 ) antagonist , which has been shown to prevent neutrophil migration to the brain [25] . The chemokine Gro-KC in rats ( CXCL1; related to IL-8 in humans ) attracts neutrophils , utilizes CXCR2 as its receptor , and was found in high levels in the brains of rats dying from RVF encephalitis ( Fig 4B ) [19] . Rats were treated with the CXCR2 antagonist at the time of infection ( 0 dpi ) or at 3 dpi prior to neutrophil infiltration into the brain . Survival and time to euthanasia was not different between the infected , untreated controls and either treatment group ( Fig 11A ) . There were also no differences in clinical manifestations such as weight loss , temperature or neurological disease . Flow cytometry on brains from the rats at euthanasia showed a significant reduction in neutrophils in the brain of rats treated at 0 dpi and a partial reduction in those treated at 3 dpi ( Fig 11B–11E ) . Of the remaining cells in the brain , those expressing CD11b and RP-1 were found to be infected , as measured by intracellular antigen staining . Taken together this suggests that preventing neutrophil infiltration into the brain is not enough to alter the outcome of disease in Lewis rats infected with RVFV .
Due to very limited human autopsies samples , little is known about the pathology that occurs within the brain of humans that succumb to RVFV infection . One study found macrophages and lymphocytes in the brain of a patient that died of encephalitis [9] . The susceptibility of human macrophages to RVF infection and their role during in RVF infection in animal models is fairly well-defined in both in vitro as well as in vivo [26 , 27] . Limited studies have focused on the role neutrophil-mediated pathology during RVFV infection compared to macrophages . Polymorphonuclear cells were observed in infected calves , immunocompetent and immunosuppressed mice , young gerbils , and rats in the liver , spleen , and brain [21 , 28–32] . Documentation of neutrophils in these previous studies was accomplished primarily by H&E stained tissues . Neutrophils can have a paradoxical role during West Nile Virus infections [33] . For instance , neutrophils are permissive to infection and appear to serve as an early amplifier of virus , whereas late in infection , neutrophils have a protective role in viral clearance [34] . In a mouse model of St . Louis encephalitis , neutrophils were heavily recruited into the brains [35] . Lewis rats are a unique model for understanding RVF neuropathogenesis because of their susceptibility to AERO infection yet they are resistant to disease after SC injection . To our knowledge , this is the first study to directly compare the difference in virus infection and spread after both routes of infection in rats . In a previous study using BALB/c mice , both SC and AERO exposure resulted in lethal hepatic disease in 70–75% of the animals , with the remaining 25–30% developing encephalitis [15] . In the AERO-exposed mice , neurological signs and death occurred 1 day earlier than the SC-infected mice [15] . One may be tempted to hypothesize , as we did , that AERO infection provides a conduit for the virus to travel directly through the nasal neuroepithelium to the olfactory bulb , whereas SC injection of the virus would not result in virus entry into the brain , and hence the rats survive with no disease . The data presented here suggest that the hypothesis regarding SC infection is not correct . We repeatedly detected viral RNA in the brain after SC infection , implying that the difference in outcome between the two routes seems to be dependent on limited viral replication in the brain after SC infection . To support the detection of viral RNA in the brains of SC-infected rats , we also found changes in leukocyte populations within these brains , albeit much less dramatic than after AERO infection . Interestingly , an influx of T cells was detected in the rats that survived , suggesting a possible protective role for these cells during SC infection . A recent study in mice showed that depletion of CD4 or CD8 cells led to increases in the frequency of encephalitis [36] . How virus reaches the brain after SC infection , and how it is subsequently controlled , is not known and is currently under investigation . For alphaviruses , vRNA persists in the brains of infected mice for months after infection , and in some cases the virus is infectious [37 , 38] . The persistence of vRNA , and potentially infectious virus , in RVFV-infected rats has implications for a potential unrecognized reservoir in the central nervous system . In this study , we used complementary approaches of flow cytometry and fluorescence microscopy with in situ hybridization to longitudinally identify and quantify the leukocyte infiltration into the olfactory bulb and cerebral cortexes of RVFV-infected rats . Both methods identified an early small influx of neutrophils and other leukocytes at 1 dpi , followed by a more substantial increase from 5 dpi onwards . The CD45hi , CD45med , and neutrophil populations co-localized with viral antigen; however , we are not able to definitively say whether these cells are productively infected or are co-localizing with viral antigen due to phagocytosis of cell debris . Distinguishing resident microglia in the brain from infiltrating macrophages is possible using differential expression of CD45 , which is expressed at low levels on resting , resident microglia in a normal rat brain [23] . In contrast , high levels of CD45 are expressed on activated microglia and infiltrating peripheral macrophages . At 1 dpi , the AERO-infected rats have transient increases in total numbers of CD45med cells and neutrophils . This was visible with the increase in Iba-1+ cells within the brain microscopy images . This early influx in neutrophils and proliferation of microglia may be detrimental , possibly bringing the virus with it or initiating an inflammatory process . Later in infection , neutrophils , and to a lesser degree macrophages , infiltrate the brain in large numbers , concomitant with the opening of the blood brain barrier and signs of disease in the animals [17] . The late influx of neutrophils and macrophages in the brain corresponded with high levels of the chemokines Gro/KC , MCP-1 , MIP-1α , MIP-3α , IL-1β , and IL-1α in brain tissue . Four of these cytokines/chemokines ( IL-8/Gro/KC , MCP-1 , IL-1α , and MIP-1α ) were also elevated in the brains of African green monkeys lethally infected with RVFV by aerosol [20] . This panel of cytokines and chemokines would exacerbate neutrophilic and monocytic inflammation , and could also contribute to microglia activation and recruitment [39 , 40] . African green monkeys that survive inhalational RVFV infection have an early cytokine response in the serum that is absent in lethal infections [20] . We found here that sub-lethal SC-infected rats have an early Th2 and Th17-like cytokine response in the serum that is , again , absent during lethal AERO infection . Taken together , a robust cytokine response in the serum within the first few days of infection was associated with sub-lethal infection and survival . Lack of an effective serum cytokine response and inflammatory mediator production in the brain were associated with lethal infection . Given the influx of neutrophils that we observed , we blocked recruitment of neutrophils to determine the effect on survival . Treatment of rats with CXCR2 antagonist prevented neutrophil influx into the brains . Despite this , the rats still succumbed to disease . We surmise that by the time the brain vasculature is largely permeable at 5 dpi , the neuronal damage from virus destruction is likely too much for effective recovery [17 , 19] . In a mouse model of RVF encephalitis , the CNS damage caused by RVFV appears to be primarily virus-mediated rather than immune-mediated [36] . This study demonstrates that RVF encephalitis in rats is not mediated by neutrophils , but we are unable to dismiss the role of microglia and macrophages in immune-mediated CNS damage . Worldwide emergence and spread of viruses such as West Nile , Chikungunya , and Zika viruses put a spotlight on the threat that emerging mosquito-borne viruses can pose to humans . RVFV is most recognized for its ability to cause hemorrhagic fever in people . However , a substantial number of infected people develop neurological complications as a result of RVFV infection [8] . Encephalitis caused by RVFV is hard to prevent and overcome using traditional vaccines and therapeutics [11 , 13–15] . This study expands our understanding of the pathogenic mechanisms of RVF encephalitis and provides a framework for the rational design of therapeutic drugs that will prevent this devastating clinical outcome .
This work was approved by the University of Pittsburgh IACUC under protocol #17040334 and #17111713 . All animal work was conducted in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Resource Council . All animals were housed and fed in an Association for Assessment and Accreditation of Laboratory Animal Care ( AAALAC ) -accredited facility . IACUC-approved euthanasia criteria were based on weight loss , fever , and morbidity . All experiments with Rift Valley fever Virus were conducted in the Center for Vaccine Research ( CVR ) and the Regional Biosafety Laboratory ( RBL ) at the University of Pittsburgh following the safety procedures described previously [16] . The RBL is a registered BSL-3/ABSL-3 laboratory space with the CDC and USDA . The ZH501 strain of Rift Valley fever virus used in these experiments was generously provided by Barry Miller ( CDC , Fort Collins , Colorado ) and Stuart Nichol ( CDC , Atlanta , Georgia ) as described previously [16] . Vero E6 ( CRL-1586 , American Type Culture Collection ) cells were used to propagate virus following standard cell culture conditions in Dulbecco’s modified Eagle’s medium ( DMEM ) containing 2% or 10% fetal bovine serum ( FBS ) , 1% penicillin-streptomycin ( pen/strep ) , and 1% L-glutamine . HAPI ( highly aggressive proliferating immortalized ) rat microglia ( ATCC CRL-2815 ) were also cultured in standard DMEM . HMC-3 human microglia ( HMC-3; ATCC CRL-3304 ) were cultured using DMEM supplemented with 12% FBS and 1% pen/strep . SH-SY5Y neuroblastoma cells ( ATCC CRL-2266 ) were cultured using 1:1 mixture of DMEM and F12 media , supplemented with 10% FBS , 1% pen/strep , and 1% L-glutamine . SH-SY5Y cells were differentiated using 10uM retinoic acid in neurobasal media supplemented with B27 , with media change every 48 hours . For quantitation , virus was measured using previously described methods of viral plaque assay and taqman q-RT-PCR [19] . For virus isolation experiments , 100 ul of clarified cortex homogenate was added to Vero E6 cells in 6-well plates . After the adsorption period , the inoculum was not removed and 2 ml of virus growth media ( DMEM described above with 2% FBS ) was added on top . Plates were observed daily for CPE . At 5 dpi , all of the supernatant from each well was transferred to a T25 flask of confluent Vero E6 cells , and CPE was monitored for 7 days . After 7 days , the supernatant was harvested for measurement of vRNA by q-RT-PCR as described . All animal work conducted was reviewed and approved by the University of Pittsburgh IACUC . Female Lewis rats ( LEW/SsNHsd ) rats were obtained from Harlan Laboratories between 8–10 weeks of age . The data presented in this manuscript represent a compilation of samples from several independent serial sacrifice experiments . The doses used in these studies ( 3x104 pfu for AERO and 1x105 pfu for SC infection ) are the actual presented doses for AERO and SC groups , not the intended doses . The presented doses were determined by performing plaque assays on the material injected into the SC rats , and also sampling the air during the aerosol exposure and then performing plaque assay to calculate the presented dose [41] . The intended dose for each group was 1x105 pfu/rat , and we chose this dose because it does typically not result in death after SC infection yet it is high enough to be able to compare to AERO infection; this is also an SC challenge dose commonly used for RVFV challenge studies in mice [31 , 42] . We also chose to use high intended dose because we wanted to give the aerosol-infected rats a high enough dose to ensure simultaneous development of disease within the 7 day time frame in order for the serial euthanasia experiments to be more consistent since each time point represents a different group of animals . We underachieved the presented dose in the aerosol experiments , and it is not uncommon to be off on the presented dose during aerosol exposure due to inherent variability within the system [41] . For each experiment , 3–4 rats were euthanized per day from 1–6 or 7 dpi to collect tissues . Rats typically reach euthanasia criteria by 7 dpi after AERO exposure to this dose of RVFV . RVFV ZH501 aerosol infections were performed in a class III aerobiology cabinet as described previously [16] . Subcutaneous injections were performed in the right hind leg ( 500 ul total volume ) . The intended target dose for both infection routes was 1x105 pfu/rat . The presented dose , determined by plaque assays from aerosol sampling devices used during the aerosol exposure [41] , was 3x104 pfu/rat . The presented dose for SC exposed animals , as determine by plaque assay on the material injected into the animals , was 1x105 pfu/rat . After infection , temperature and weights were taken daily in addition to observation for any clinical signs of illness . Rats were euthanized daily from 1–6 or 7 dpi . Immediately before euthanasia , blood was drawn by cardiac puncture and saved for analysis including complete blood count blood chemistry using the Abaxis HM2 and VS2 , respectively . For CBC analysis , data from rats infected SC with 1x105 pfu/rat and euthanized at 10 dpi is included ( Fig 2 ) . For experiments presented in Figs 7–10 , rats were perfused with PBS followed by 4% paraformaldehyde ( PFA ) prior to organ collection for imaging analysis . SB-265610 ( Sigma Aldrich SML0421 ) was suspended in DMSO and diluted in sterile Dulbecco’s PBS on the day of injection . SB-265610 ( 2 mg/kg ) was administered interperitoneally once daily in a volume of 300 ul . Whole blood ( 50 ul ) was taken from each animal and directly stained with the antibodies diluted in FACS buffer for 15 minutes . Antibodies used were all from BD Biosciences unless otherwise indicated: CD45 ( OX-1 ) , HIS-48 ( His-48 ) , RP-1 ( RP-1 ) CD11b ( WT . 5 ) , CD3 ( 1FA ) , CD4 ( OX-35 ) , CD8 ( OX-8 ) , CD163 ( His-36 ) , CD68 ( ED1 ) , Iba-1 ( Abcam; EPR6136 ) , and RVFV monoclonal ( BEI; NR-43195 ) . 450uL of FACS lysis buffer was used to lyse red blood cells for 30 minutes . Samples were then washed twice with FACS buffer and fixed in 4% PFA . Gating strategy for whole blood samples is shown in S1 Fig . After perfusion of rats with saline , whole brains were removed immediately for cell isolation essentially as described [23] . Brains were divided into hemispheres , covered with digestion buffer consisting of modified HBSS without calcium and magnesium , 10mg/ml DNase I ( Sigma 10104159001 ) , 20mg/ml of collagenase ( Sigma C2674 ) and mechanically digested using a scalpel . The sample was then incubated at 37°C for 45 minutes on a continuous rocker . Every 15 minutes , the sample was mechanically triturated using a serological pipet . The resulting homogenate was then filtered through a 40 um cell strainer and washed twice with wash buffer , consisting of HBSS with 3% FBS and 10 mg/ml DNase I and centrifuged at 500 x g for 8 minutes at room temperature . The supernatant was removed and the remaining pellet was suspended in 80% stock isotonic Percoll ( SIP ) ( Sigma GE17-0891-01 ) made in HBSS solution . The suspension was subsequently overlaid with 10 ml of 38% SIP , 10 ml 21% SIP , followed by 5 ml HBSS with 3% FBS and centrifuged at 480 x gravity for 35 minutes , no brake . The third interface was removed , washed twice with modified HBSS containing 3% FBS and then suspended in 1 ml FACS buffer . Cells were counted using a hemocytometer and placed on ice . Cells suspended in FACS buffer were placed in a V-bottom 96-well plate and centrifuged for 500 x gravity for 4 minutes at 4°C . An Fc block was performed by adding 2uL of purified anti-CD32 ( BD Biosciences ) and 18uL of FACS buffer per sample for 20 minutes on ice in the dark . Cells were then washed twice with 200uL FACS buffer and stained with live/dead . Cells were washed with 200uL of FACS buffer and then stained antibody mix for 30 minutes on ice in the dark . Antibodies and clones are listed above . Samples that required intracellular stain were permeabilized and fixed using BD Cytofix/Cytoperm ( BD554714 ) and then washed with FACS perm-buffer . The stained samples were then washed twice with 200uL FACS buffer followed by fixation with 200uL of 4% PFA . Samples were run on a BD LSRII and analyzed using FlowJo 10 . 5 . 0 . Cell analysis began with a vital brain gate using FSC and SSC , followed by live/dead , then singlet inclusion using SSC-A and SSC-H . From there , CD45 expression levels were determined using SSC-A , and the gating strategy in S2 Fig was followed . 50uL of clarified rat brain cortex homogenate or rat serum was run on Bio-Plex Pro Rat Cytokine 23-plex assay ( BioRad #12005641 ) following the kits instructions . At the time of purchase of the kits , only 22 parameters were available . The 22 parameters measured were: G-CSF , GM-CSF , GRO/KC , IFN-γ , IL-1α , IL-1β , IL-2 , IL-4 , IL-5 , IL-6 , IL-7 , IL-10 , IL-12 ( p70 ) , IL-13 , IL-17A , IL-18 , M-CSF , MCP-1 , MIP-1α , MIP-3α , RANTES , TNF-α , VEGF . Samples were analyzed on Bio-Plex 200 system located within BSL-3 containment . Cytokines not shown in Fig 4 are shown in S1 and S2 Figs . For fixation of tissues and inactivation of virus , rats were perfused with PBS followed by 4% PFA . Brain tissue was extracted and submerged in 4% PFA for 3 hours at 4°C , followed by 30% sucrose and kept at 4°C for 1 week before flash freezing with 2-methylbutane and liquid nitrogen . Frozen samples were cryo-sectioned at 7um thickness . Antibodies used for IF include: goat anti-IBA1 ( Novus; NB100-1028 ) , Rabbit anti-MPO ( Abcam; ab9535 ) , mouse anti-CD45-647 ( BD Pharmigen; 565465 ) , neurotrace-640 ( Invitrogen; N21482 ) . Secondary antibodies include: donkey anti-goat Alexa Fluor 488 ( Invitrogen ) , Cy5 Affinipure donkey anti-mouse IgG ( Jackson ImmunoResearch ) , Cy3 Affinipure donkey anti-rabbit IgG ( Jackson ImmunoResearch ) . For visualization of viral RNA and cell surface markers: Slides were permeablized for 30 minutes using 0 . 1% TritonX100 + 1x PBS at RT . The protease step in RNAscope kit was omitted to preserve microglia and neuronal antigen . Slides were stained in slide box lined with wet paper towels and placed in an incubator at 37°C rather than RNAscope hybridization oven . RNAscope kit was , otherwise , used according to manufacturer’s instructions with RVFV ZH501 probe against NP gene ( Cat No . 496931 ) . Primary antibody for IBA1 or Neurotrace-640 were incubated for 1 hour at RT . Secondary antibody ( was incubated for 1 hour at RT . Hoescht ( Bis-benzamide ) was incubated for 1 minute to counterstain nuclei . Samples were mounted using a glycerol + PVA mixture . For visualization of immune cell infiltration using IF: Slides were permeabilized for 30 minutes using 0 . 1% TritonX100 + 1x PBS at RT . Slides were incubated with 5% normal donkey serum diluted with 0 . 5% BSA + 1x PBS to block nonspecific binding of the secondary antibodies for 45 minutes . Primary antibodies were incubated for 1 hour at 4°C . Secondary antibodies were incubated for 1 hour at RT . Hoescht ( Bis-benzamide ) was incubated for 1 minute to counterstain nuclei . Samples were mounted using a glycerol + PVA mixture . Slides were imaged using the Nikon A1 Confocal Microscope provided by the Center for Biologic Imaging . Images were contrasted using Adobe Photoshop and de-noised and analyzed using Nikon Elements . Statistical analyses were performed using GraphPad Prism software ( La Jolla , CA ) . For Figs 2 , 3 and 4 , S1 , and S2 , two-way analysis of variance ( ANOVA ) was performed , with the 2 factors being exposure route ( AERO vs SC ) and time ( 0–7 dpi ) . Dunnett’s multiple comparison test was also performed , which compared the mean value for each day post-infection of each exposure route to the mean of the pre-infection control sample . P values for each comparison were adjusted to account for multiple comparisons . On each graph , the # in the bottom right corner of the graph indicates the p-value for the comparison of SC vs AERO exposure route ( N . S . , not significant; # , P < 0 . 05; ## , P < 0 . 01; ### , P < 0 . 001; #### , P < 0 . 0001 ) . Asterisks above symbols indicate significant differences at a particular time point within each exposure route compared to uninfected samples ( * , P < 0 . 05; ** , P < 0 . 01; *** , P < 0 . 001; **** , P < 0 . 0001 ) as determined by Dunnett’s multiple-comparison tests . Asterisks are color coded by exposure route group . For Figs 5A and 11B , one-way ANOVA was used to determine statistical significance between the groups at each time point ( * , P < 0 . 05; ** , P < 0 . 01; *** , P < 0 . 001; **** , P < 0 . 0001 ) . For Fig 11A , Log-rank Mantel-Cox test was used to determine differences in survival with and without CXCR2 antagonist treatment . | Rift Valley fever is a disease of livestock and humans that occurs periodically in Africa and parts of the Middle East . People infected with Rift Valley fever virus can develop different clinical outcomes , including hemorrhagic fever or encephalitis . Understanding of the pathophysiological mechanisms of encephalitis has been a challenge due to inadequate animal models of neurological disease . We used a rat model of Rift Valley fever encephalitis to understand the mechanisms underlying lethal neurological disease compared to subclinical infection . The primary immune cell types that infiltrate the brains of rats with lethal encephalitis were neutrophils and macrophages . Prevention of neutrophil migration into the brains did not prevent disease . These results provide new insight into the contrast between lethal and subclinical disease in an immunocompetent rodent model of Rift Valley fever encephalitis . | [
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] | 2019 | Neutrophil and macrophage influx into the central nervous system are inflammatory components of lethal Rift Valley fever encephalitis in rats |
Interferon regulatory factor 8 ( IRF8 ) , also known as interferon consensus sequence-binding protein ( ICSBP ) , is a transcription factor of the IRF family . IRF8 plays a key role in normal B cell differentiation , a cellular process that is intrinsically associated with Epstein-Barr virus ( EBV ) reactivation . However , whether IRF8 regulates EBV lytic replication remains unknown . In this study , we utilized a CRISPR/Cas9 genomic editing approach to deplete IRF8 and found that IRF8 depletion dramatically inhibits the reactivation of EBV upon lytic induction . We demonstrated that IRF8 depletion suppresses the expression of a group of genes involved in apoptosis and thus inhibits apoptosis induction upon lytic induction by B cell receptor ( BCR ) stimulation or chemical induction . The protein levels of caspase-1 , caspase-3 and caspase-8 all dramatically decreased in IRF8-depleted cells , which led to reduced caspase activation and the stabilization of KAP1 , PAX5 and DNMT3A upon BCR stimulation . Interestingly , caspase inhibition blocked the degradation of KAP1 , PAX5 and DNMT3A , suppressed EBV lytic gene expression and viral DNA replication upon lytic induction , suggesting that the reduced caspase expression in IRF8-depleted cells contributes to the suppression of EBV lytic replication . We further demonstrated that IRF8 directly regulates CASP1 ( caspase-1 ) gene expression through targeting its gene promoter and knockdown of caspase-1 abrogates EBV reactivation upon lytic induction , partially through the stabilization of KAP1 . Together our study suggested that , by modulating the activation of caspases and the subsequent cleavage of KAP1 upon lytic induction , IRF8 plays a critical role in EBV lytic reactivation .
Epstein-Barr virus ( EBV ) , a ubiquitous human gammaherpesvirus , is associated with malignant diseases , including Burkitt’s lymphoma , Hodgkin’s lymphoma , nasopharyngeal carcinoma , and NK/T cell lymphoma [1] . The genome of EBV is approximately 170 kb in length and encodes more than 80 genes . EBV infects both B lymphocytes and some epithelial cells and the life cycle of EBV is divided into latent or lytic phases . In the lytic phase , EBV expresses all lytic genes and progeny virus particles are packaged and released from the cell [2] . The reactivation of EBV from latent to lytic phase can be triggered by expression of two viral immediate-early gene products , ZTA ( also called BZLF1 or Z ) and RTA ( also known as BRLF1 or R ) . A series of cellular factors have been shown to regulate ZTA and RTA gene expression and to affect ZTA/RTA transcriptional activity [3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16] . B cell receptor ( BCR ) activation is a philologically relevant stimulus for triggering EBV reactivation from latency since this occurs not only in tumor cell lines but also in freshly isolated B cells from patients [17 , 18] . The interferon regulatory factor ( IRF ) family members ( IRF1-9 ) are transcription factors for interferon ( IFN ) and IFN-inducible genes [19 , 20] . Members of the IRF family also play a vital role in regulation of immunity and oncogenesis [21] . Previous studies showed that several IRFs are implicated in the life cycles of herpesviruses , including EBV . For examples , IRF1 , IRF2 , IRF4 , IRF5 and IRF7 are involved in EBV latency and virus-mediated cell transformation [22 , 23 , 24 , 25 , 26] . IRF4 synergizes with RTA encoded by murine γ-herpesvirsus-68 to facilitate viral M1 gene expression [27] . IRF3 and IRF7-mediated antiviral responses are counteracted by EBV encoded proteins [28 , 29 , 30] . IRF8 , also known as IFN consensus sequence-binding protein ( ICSBP ) , is a unique transcription factor of the IRF family because it is expressed predominately in hematopoietic cells [31] . Similar to other IRFs , IRF8 contains a DNA binding domain ( DBD ) and interacts with other proteins ( such as PU . 1 , IRF1 , IRF2 or IRF4 ) through the IRF association domain ( IAD ) . In addition , IRF8 can be tyrosine phosphorylated [32 , 33 , 34 , 35] , SUMOylated [36] and ubiquitinated [37 , 38] . The DBD , IAD and post-translational modifications of IRF8 all contribute to its transcription-regulatory activities [36 , 39 , 40 , 41] . Phosphorylation and dephosphorylation can alter the function of IRF8 in innate immune responses and leukemia pathogenesis [34 , 42] . SUMO conjugation-deconjugation switches IRF8’s function as a repressor or a activator [36] . IRF8 is ubiquitinated by an E3 ligase TRIM21 , which alters IRF8’s ability in IL12p40 transcription [30 , 37] . Knockdown of IRF8 inhibits the growth of diffuse large B-cell lymphoma [43] . IRF8 is required for apoptotic induction in myeloid cells [44] . Recently , an important study established a role for IRF4 and IRF8 in EBV-mediated B-cell transformation [45] . EBV EBNA3C , which is expressed in cells of type III latency , interacts with and stabilizes IRF4 . EBNA3C coordinates with IRF4 to downregulate IRF8 , which is critical for apoptosis inhibition and thus the survival of EBV-transformed cells [45] . However , in EBV-positive B cells of type I latency , EBNA3C is not expressed and IRF4 protein level is very low while IRF8 is highly expressed [46] . Despite the high expression of IRF8 in B cells of type I EBV latency , the contribution of IRF8 to EBV lytic replication remains unknown . Driven by these facts , we explored the role of IRF8 in the EBV lytic cycle . We demonstrated that IRF8 positively regulates EBV lytic replication through regulating caspases expression and hence caspase activation upon lytic induction and caspase activation facilitates the degradation of cellular factors that limit EBV lytic replication .
The previous research on IRF8 and EBV latency [45] and the high expression of IRF8 in EBV-positive B cells of type I latency prompted us to test whether and how IRF8 regulates EBV lytic replication . Here we first utilized an Akata ( EBV+ ) cell line , a Burkitt’s lymphoma cell line of type I latency , as a model system to investigate the role of IRF8 in the EBV lytic cycle . Because Akata ( EBV+ ) cells express surface immunoglobulin receptors of the G ( κ ) class ( IgG ) and anti-IgG cross-linking mediated BCR activation can serve as a physiologically relevant stimulus for EBV lytic reactivation [18] , these cells are well-suited for investigating the contribution of cellular factors in EBV lytic replication [13 , 47] . To demonstrate whether IRF8 regulates EBV lytic replication , we utilized CRISPR/Cas9 technology to knockdown endogenous IRF8 in Akata ( EBV+ ) B cells . We designed two sgRNAs and used a lenti-viral system to establish two IRF8-depleted pool cell lines ( Fig 1A ) . To ensure the reproducibility of our results , at least three independent lentiviral infections were performed . The infection efficiency was approximately 20% and the experiments were performed after one to two weeks selection with puromycin when all living cells were puromycin-resistant . Compared with non-targeting control ( NC ) , the sgRNA sg1 partially knocked down the protein expression of IRF8 , while sg2 efficiently depleted IRF8 ( Fig 1B ) . To further confirm the correct targeting of IRF8 by CRISPR/Cas9 , we sequenced the genomic DNA spanning the CRISPR/Cas9 targeting region of the IRF8-sg1 and IRF8-sg2 cell lines and we found that 10 out of 22 clones for sg1 and 9 out of 14 clones for sg2 contain frame shifts ( S1 Fig ) . To evaluate the effects of IRF8 depletion on EBV lytic replication , we triggered EBV lytic replication by anti-IgG mediated BCR cross-linking . We found that the accumulation of the EBV lytic proteins ZTA and BGLF4 was suppressed in the two IRF8-depleted cell lines upon lytic induction and that the higher IRF8 knockdown efficiency correlated with lower ZTA and BGLF4 expression ( Fig 1C and 1D ) . We then examined the level of lytic RNA transcripts in these cell lines . As expected , knockdown of IRF8 dramatically suppressed the expression of immediate early ( ZTA and RTA ) and late ( BGLF2 ) genes ( Fig 1E ) . To test whether IRF8 plays a role in EBV replication , we measured both intracellular and extracellular EBV genome copies following lytic induction . We found that both intracellular ( Fig 1F ) and extracellular ( Fig 1G ) viral DNA copies were significantly reduced upon IRF8 depletion . These results suggested that IRF8 acts as a key positive regulator during EBV lytic reactivation . To further demonstrate that the observed phenotype was not due to off-target effects , we reconstituted IRF8 back into the IRF8-depleted ( sg2 ) cells . We found that IRF8 restoration facilitated EBV ZTA and RTA protein expression compared with IRF8-depleted cells upon IgG cross-linking ( S2A Fig , lanes 2–3 vs 5–6 ) . Moreover , EBV DNA replication was also dramatically enhanced upon IRF8 reconstitution ( S2B Fig , lanes 2–3 vs 5–6 ) . Together these results suggest that IRF8 promotes EBV replication upon lytic induction . As a transcription factor , IRF8 may also regulate EBV replication through altering cellular processes . To provide insight into IRF8-regulated cellular events , we performed RNA-Seq analysis for the control and IRF8-depleted cells generated from three different lentiviral transductions . Totally we identified 253 differentially expressed genes ( S1 Table ) . Among these genes , 196 genes were down-regulated and 57 genes were up-regulated upon IRF8 depletion ( Fig 2A ) . Gene Ontology ( GO ) analysis plus manual curation of these differentially regulated genes revealed that 19 genes involved in “positive regulation of apoptosis” were significantly enriched . Interestingly , all of these genes involved in apoptosis were down-regulated in IRF8-depleted cells ( Fig 2A , red dots and Fig 2B ) . To validate our RNA-seq results , we selected 8 genes and analyzed their expression by RT-qPCR for both IRF8-sg1 and IRF8-sg2 cells . The down-regulation was confirmed for all those genes tested , including caspase-1 ( CASP1 ) ( Figs 2B and S3A ) . Consistent with the reduced mRNA expression , caspase-1 protein level was reduced in IRF8-depleted cells ( Figs 2C and S3B , lane 1 vs 4 ) . The down-regulation of apoptosis related genes suggested that IRF8 depletion may suppress apoptosis induction during EBV lytic replication upon BCR activation . To test this possibility , we monitored the cleavage of PARP and global caspase substrates containing a cleavage motif [DE ( T/S/A ) D] . We found that IRF8 depletion suppressed protein cleavage upon BCR activation ( Figs 2C and S3B , lanes 2–3 vs 5–6 ) . IRF8 has been shown to positively regulate the apoptosis of myeloid cells and nonhematopoietic tumor cells [44 , 48 , 49 , 50] . The dramatic down-regulation of caspase-mediated protein cleavage upon IRF8 depletion suggested that IRF8 may regulate the activation of caspases . To test this possibility , we monitored the level of individual caspases and their cleaved products . Strikingly , we found that the IRF8 depletion markedly reduced the levels of caspase-3 and caspase-8 and consequently the generation of active cleaved products was also suppressed upon BCR activation . In contrast , the protein levels of caspase-2 , caspase-7 and caspase-9 and their cleavage were less affected by IRF8 depletion ( Figs 3A and S3C ) . In addition , the level of Bcl-2 , an anti-apoptosis protein , increased in IRF8-depleted cells ( Figs 3A and S3C , Bcl-2 blot , lanes 1–3 vs 4–6 ) , which further contributed to IRF8-dependent inhibition of apoptosis . Except for caspase-1 , the gene expression levels of other caspases , including caspase-3 and caspase-8 , were not regulated by IRF8 depletion according to our RNA-seq analysis ( S4 Fig and S1 Table ) , suggesting that IRF8 may control caspase-3 and caspase-8 protein levels through modulation of translation or protein stability rather than transcription . Because caspase activation upon apoptotic induction can facilitate EBV lytic reactivation in other EBV-positive cell lines [51 , 52] , we reasoned that IRF8 facilitates EBV reactivation in the Akata ( EBV+ ) cells through caspase activation . To test this hypothesis , we pretreated the Akata ( EBV+ ) cells with a pan-caspase inhibitor Z-VAD-FMK and then induced EBV lytic reactivation by anti-IgG cross-linking of the BCR . Caspase inhibition strongly suppressed the expression immediate-early ( ZTA and RTA ) , early ( BGLF4 ) and late ( BGLF2 ) gene expression ( Fig 3B ) . Consistently , the EBV ZTA and BGLF4 protein expression and viral DNA replication were also blocked by caspase inhibition ( Fig 3C ) . The switch from EBV latency to lytic reactivation is negatively regulated by a number of cellular factors [53] . Because caspase activation can lead to the cleavage of many cellular proteins [54 , 55 , 56] , we hypothesized that those factors normally suppressing EBV lytic replication are destabilized by caspase activation upon BCR stimulation . To test this hypothesis , we monitored the levels of several proteins , including KAP1 [12 , 57 , 58 , 59] , PAX5 [8 , 60 , 61 , 62] , DNMT3A [63] and STAT3[64 , 65 , 66 , 67 , 68] , whose functions have been shown to maintain herpesviruses latency and suppress lytic replication/reactivation . We found that the protein levels of KAP1 , PAX5 and DNMT3A , but not that of STAT3 , were dramatically reduced upon lytic induction ( Figs 3D and S3C , lanes 1–3 ) while IRF8 depletion suppressed the down-regulation of KAP1 , PAX5 and DNMT3A ( Figs 3D and S3C , lanes 4–6 ) . To further test whether caspase activation plays a role in the de-stabilization of KAP1 , PAX5 and DNMT3A , we monitored their protein levels in Akata ( EBV+ ) cells when caspases are inhibited and lytic replication is triggered by BCR stimulation . Interestingly , pretreatment of the cells with a pan-caspase inhibitor Z-VAD-FMK restored their expression ( Fig 3E ) . For KAP1 , in addition to the reduced protein level , we also noticed the generation of two potential cleaved fragments upon BCR activation , which is also blocked by caspase inhibition ( Fig 3E , KAP1 , longer exposure ) . Taken together , these results suggested caspase activation-mediated de-stabilization of cellular restriction factors contributes to EBV lytic replication . To demonstrate the effect of IRF8 in additional EBV-positive cell lines , we depleted IRF8 in two additional cell lines , P3HR-1 and an EBV transformed lymphoblastoid cell line ( LCL ) . We observed universal lower reactivation for EBV in IRF8-depleted cells treated with either gemcitabine , anti-IgM ( for LCL cells ) or TPA/sodium butyrate ( for P3HR-1 cells ) ( Fig 4 ) , reinforcing that IRF8 plays a key role in EBV reactivation . Based on our RNA-seq results , only CASP1 ( caspase-1 ) gene was regulated by IRF8 at the RNA level ( S4 Fig ) . Previous studies using ChIP-seq showed that IRF8 could bind to the promoter regions of both human and mouse CASP1 at a conserved consensus site , -40 to -31 bp upstream of the start codon of human CASP1 ( Fig 5A ) [69 , 70] . However , it is not clear whether IRF8 directly regulates CASP1 expression . We hypothesized that IRF8 , as a transcription activator , directly regulates CASP1 gene expression through binding to its promoter . To test our hypothesis , we constructed luciferase reporter plasmids , which contain the CASP1 promoter with or without the putative IRF8 binding site ( Fig 5B ) . The luciferase reporter assay showed that IRF8 activated the wild-type CASP1 promoter but not the truncated version without the IRF8 binding site ( Fig 5B ) . To confirm our results , we mutated the conserved IRF8 binding site and found that IRF8 failed to activate the mutated reporter ( Fig 5B ) . To further validate our results , we constructed a DNA-binding deficient IRF8 mutant ( K108E ) [71] and tested whether it can block the activation of CASP1 promoter . Compared with wild-type IRF8 , the DNA-binding deficient mutant ( K108E ) lost the ability to regulate the CASP1 promoter ( Fig 5C ) . In conclusion , our results demonstrated that IRF8 enhances CASP1 gene expression through regulation of its promoter . A previous study showed that IRF1 can also regulate CASP1 gene promoter [72] . Therefore , we tested whether IRF1 could cooperate with IRF8 to further enhance the CASP1 promoter activity . The luciferase reporter assay demonstrated that IRF1 synergized with IRF8 to further enhance CASP1 promoter activity ( Fig 5D ) . To further prove whether IRF8/IRF1 bind to CASP1 promoter in B cells , we performed ChIP experiments using chromatin prepared from EBV-postive Akata , LCL and P3HR-1 cells . Our results showed that IRF8/IRF1 indeed bind to the promoter region of CASP1 for all these cells ( S5A Fig ) , suggesting that they directly regulate CASP1 expression in vivo . To demonstrate physiological relevance of IRF8/IRF1 activation of CASP1 promoter observed in 293T cells , we performed luciferase assay using Akata cells . Similarly , we found that IRF8 and IRF1 triggered a strong activation of CASP1 promoter while the IRF8 DNA binding deficient mutant ( K108E ) failed to activate the promoter ( S5B Fig ) . Our RNA-seq analysis showed that both IRF1 and IRF8 are expressed in the Akata ( EBV+ ) cells , with IRF8 level approximately 6-fold higher than that of IRF1 ( S6 Fig ) . Based on the luciferase assay , IRF8 , together with its closely related family member IRF1 , plays an effective role on regulating CASP1 expression . The control of caspase-1 expression by IRF8 promoted us to test whether caspase-1 contributes to EBV reactivation upon lytic induction . To answer this question , we utilized a similar CRISPR/Cas9 approach to deplete endogenous CASP1 in Akata ( EBV+ ) B cells . To offset the potential off-target effect , we designed two sgRNAs to establish CASP1-depleted cell lines by three distinct lentiviral infections ( Fig 6A ) . To further confirm the correct targeting of CASP1 by CRISPR/Cas9 , we also sequenced the genomic DNA spanning the CRISPR/Cas9 targeting region of the CASP1-sg1 and CASP1-sg2 cell lines . The sequencing results showed that frame shifts were introduced in 8 out of 13 clones for CASP1-sg1 and 12 out of 14 clones for CASP1-sg2 ( S7 Fig ) . To evaluate the effects of caspase-1 depletion on EBV lytic reactivation , we triggered EBV reactivation by anti-IgG mediated BCR cross-linking . We found that the accumulation of the EBV lytic proteins ZTA and RTA was dramatically suppressed in the two CASP1-depleted cell lines upon BCR activation ( Fig 6B ) . We also examined the level of lytic RNA transcripts in these cell lines . As expected , knockdown of CASP1 dramatically suppressed the expression of immediate early ( ZTA and RTA ) and late ( BGLF2 ) genes ( Fig 6C ) . To test whether caspase-1 plays a role in EBV replication , we measured intracellular EBV genome copies following lytic induction . Compared with control , the intracellular viral DNA copies were significantly reduced upon caspase-1 depletion ( Fig 6D ) , suggesting that caspase-1 is required for EBV reactivation . To demonstrate the effect of caspase-1 in broader settings , we also depleted CASP1 in P3HR-1 and EBV transformed LCL cells . We found that CASP1-depletion suppresses EBV reactivation treated with either gemcitabine , anti-IgM ( for LCL ) or TPA/sodium butyrate ( for P3HR-1 ) ( Fig 7 ) , suggesting that IRF8/caspase-1 axis contributes to EBV reactivation upon lytic induction . IRF8 can affect the degradation of KAP1 , PAX5 and DNMT3A through caspase activation ( Figs 3D and S3C ) . To test whether caspase-1 could affect their degradation , we monitored the protein stability when caspase-1 was depleted and lytic reactivation was induced by BCR activation . Interestingly , we found that the degradation of KAP1 , but not PAX5 and DNMT3A , was blocked in caspase-1-depleted cells ( Fig 8A ) . Based on these results , we reasoned that KAP1 might be cleaved by caspase-1 . To prove this , we performed an in vitro cleavage assay using individual recombinant caspases and KAP1 . To facilitate the detection of cleaved KAP1 fragments , we utilized an N-terminally HA-tagged KAP1 construct and immunoprecipitated the KAP1 protein from transfected 293T cells using HA magnetic beads . HA-KAP1 was eluted for the in vitro cleavage assay . Anti-HA and anti-KAP1 antibodies recognize N- and C-terminal of KAP1 respectively ( Fig 8B ) , which facilitates the detection of cleaved fragments . Interestingly , we found that caspase-1 , as well as caspase-8 can cleave KAP1 in vitro ( Fig 8B ) . We also checked the expression of caspase-8 ( CASP8 ) and found that the caspase-8 protein level ( Fig 8A ) but not its mRNA level ( S8 Fig ) was also reduced in caspase-1-depleted cells . These results together suggested that KAP1 cleavage is regulated by caspase-1 and -8 in Akata ( EBV+ ) cells upon lytic induction . Because KAP1 depletion has been shown to facilitate EBV , Kaposi’s sarcoma-associated herpesvirus ( KSHV ) and human cytomegalovirus reactivation [12 , 57 , 58 , 59] , we reasoned that the cleavage of KAP1 by caspase-1 and -8 should promote viral reactivation . To prove our prediction , we further depleted KAP1 in CASP1-depleted ( sg1 ) Akata cells by CRISPR/Cas9 genomic editing approach . As expected , KAP1-depletion in CASP1-depleted cells restored EBV reactivation upon BCR activation ( Fig 9 ) . Taken together , our results suggested that KAP1 is one of the important downstream targets of caspase-1 critical for EBV reactivation .
In this study , we discovered that the cellular factor IRF8 facilitates EBV lytic replication by promoting caspase expression and their activation upon lytic inducition . The IRF family proteins have been shown to play an important role in immunity , cell growth , differentiation and oncogenesis [19] . In contrast to the positive role of IRF8 in EBV lytic replication observed in our study , most of the IRFs contribute to anti-viral immunity and block the infection or lytic reactivation of herpesviruses . For example , it was reported that IRF1 restricts gammaherpesvirus replication through IFN-mediated suppression of viral replication [73 , 74 , 75 , 76] . IRF2 also suppresses gammaherpesvirus replication and reactivation by inhibiting the M2 gene promoter [77] . Herpesviruses have evolved strategies to block IRF3 mediated anti-viral signaling [30 , 78] . IRF5 or IRF7-mediaed suppression of KSHV replication is counteracted by virally encoded proteins [79 , 80 , 81] . While IRF4 has been implicated in suppressing KSHV replication [82 , 83 , 84] , it has been shown that IRF4 promotes gammaherpesvirus-68 replication through enhancing viral promoter activation [27 , 85 , 86] . Our identification of IRF8 as a positive regulator for EBV reactivation provides another example of IRFs in promoting herpesvirus lytic replication . IRF8 is a unique member of the IRF family . It is highly expressed in B cells [87] and plays a critical role in B cell biology [88] . A recent study showed that IRF8 regulates EBV latency and the apoptosis of EBV-positive B cells [45] . However , the contribution of IRF8 to EBV lytic replication remained unclear prior to our study . Using a CRISPR/Cas9 genomic editing method , we for the first time demonstrated that IRF8 depletion dramatically suppresses the reactivation of EBV ( Figs 1 and 4 ) . IRF8 positively regulates apoptosis in different types of cells , including B cells [44 , 48 , 49 , 50 , 89] . Our RNA-seq and western blot analyses showed that IRF8 modulates caspase activation during EBV lytic replication ( Figs 2 and 3 ) . Especially , IRF8 binds to and enhances CASP1 gene promoter activity ( Fig 5 ) and caspase-1 expression is critical for EBV reactivation ( Figs 6 and 7 ) , partially through KAP1 cleavage ( Figs 8 and 9 ) . The regulation of caspase-1 by IRF8 may also contribute to subsequent BPLF1 cleavage , which has been shown to facilitate EBV DNA replication [90] . In addition , the cleavage of other cellular [56 , 91 , 92 , 93 , 94] or potentially viral proteins by caspase-1 and other caspases could also contribute to EBV reactivation . In addition to caspase cleavage of BPLF1 , caspase-3 was reported cleave LMP1 in Hela cells while the functional importance is not clear [95] . Using bioinformatic tools PeptideCutter and GraBCas [96 , 97] , we also predicted the potential caspase cleavage sites for EBV proteins and found that many other viral proteins , such as BCRF1/vIL10 , may also be potentially cleaved by caspases ( S2 Table ) . Further detailed studies are required to prove their cleavage and the subsequent functional importance during EBV reactivation . Several studies showed that EBV lytic reactivation is closely associated with apoptosis and that caspase activation promotes EBV lytic replication in EBV-transformed LCLs and EBV-infected gastric cancer ( AGS ) cells [51 , 52] . However , the underlying mechanisms for caspase activation in EBV lytic replication were not clear . Here we provide evidence that caspase activation-induces de-stabilization of cellular factors KAP1 , PAX5 and DNMT3A contributes to efficient EBV replication ( Fig 3 ) . KAP1 is a corepressor that inhibits the reactivation of multiple herpesviruses [12 , 57 , 58 , 98 , 99] . Although phosphorylation of KAP1 overcomes KAP1-mediated inhibition , our study suggested that caspase-1/-8-mediated cleavage provides another means to antagonize KAP1-mediated inhibition ( Fig 8 ) . PAX5 is a B-cell-specific transcription factor that promotes EBV latency and suppresses lytic reactivation [8 , 60 , 61 , 62] . A previous study suggested that the lytic triggers TPA and sodium butyrate facilitate PAX5 destabilization through down-regulation of its mRNA expression [8] and BCR stimulation of B cells also decreases the level of PAX5 mRNA [100] . Our demonstration of caspase activation in PAX5 degradation provides an additional layer of regulation of PAX5 during EBV lytic replication . The de novo DNA methyltransferase DNMT3A contribute to γ-herpesvirus latency by suppressing viral lytic gene promoters through methylation [63] . It is conceivable that the down-regulation of DNMT3A by caspase activation would facilitate viral lytic replication . Recent studies suggested that not only the decrease of IRF8 but also the increase of IRF4 is required for B cell differentiation , and that the IRF4/IRF8 ratios provide the differential signal for plasmablast versus germinal center plasma cell fate [70 , 88] . In Akata ( EBV+ ) B cells , the expression of IRF4 is very low revealed by RNA-Seq ( S6 Fig ) and IRF4 protein is not detectable by western blot analysis [46] . Therefore , in the absence of IRF4 , IRF8 depletion may not be sufficient to trigger B cell differentiation . Although IRF8 normally suppresses B cell differentiation to plasma cells [101] , a process that positively contributes to EBV reactivation [7] , the results of our current work and the studies of others support a model in which IRF8 facilitates the reactivation of EBV upon lytic induction ( Fig 10 ) . IRF8 plays a key role in maintaining caspase-1 expression , a cellular protease critical for EBV reactivation upon lytic induction . Caspase-1 activation can trigger the specific cleavage of EBV BPLF1 for efficient viral DNA replication [90] . The activation of caspase-1 and caspase-8 can lead to the cleavage and destabilization of KAP1 and thus enhanced EBV replication . As a positive regulator of interferon signaling , IRF8 might also function as an anti-viral factor [102 , 103 , 104] by promoting interferon signaling during primary EBV infection , which could then limit viral lytic infection and facilitate the establishment of latency . Future studies are required to examine this possibility . In summary , our study suggests that IRF8 positively regulates EBV lytic replication upon lytic induction . These findings provide valuable insights into our understanding of IRF8 and caspase activation in EBV lytic replication , which lays the foundation for developing novel therapeutic strategies against EBV-associated malignancies .
Akata ( EBV+ ) cells ( gifts from Diane Hayward , Johns Hopkins University ) were grown in RPMI 1640 media supplemented with 10% FBS ( Cat# 26140079 , Thermo Fisher Scientific ) in 5% CO2 at 37°C [105 , 106] . The P3HR-1 cell ( ATCC , HTB-62 ) was purchased from ATCC . The EBV-transformed lymphoblast cell lines ( LCL , GM11830 ) was purchased from the Coriell Institute for Medical Research ( Camden , NJ ) . The P3HR-1 cell was grown in RPMI 1640 media supplemented with 10% FBS . The LCL cell was cultured in RPMI 1640 media supplemented with 15% FBS . 293T cells ( a gift from Diane Hayward , Johns Hopkins University ) were grown in DMEM media supplemented with 10% FBS . The pan-caspase inhibitor ( Z-VAD-FMK , Cat# A1902 ) was purchased from ApexBio . Plasmid DNA was purified on miniprep columns according to the manufacturer’s protocol ( Qiagen ) . pCMV3-N-FLAG and pCMV3-N-FLAG-IRF8 were obtained from Sino biological . pcDNA3 . 1-V5-His and pSG5 were obtained from Invitrogen and Stratagene , respectively . T vector pMD19 was bought from Clontech . pSG5-HA-KAP1 expression vector ( pGL190 ) was a gift from Diane Hayward ( Johns Hopkins ) and contain the corresponding open reading frames in a derivative of pSG5 ( Stratagene ) [107] . The IRF1 ORF was cloned from Akata ( EBV+ ) cDNA into pMD19 ( Clontech ) by PCR using the following primer sets: forward ( 5’-ATGCCCATCACTCGGATGC-3’ ) and reverse ( 5’-CTACGGTGCACAGGGAATGG-3’ ) . IRF1 was then subcloned into pcDNA3 . 1-V5-His ( Invitrogen ) by using Gibson assembly and the following two primer sets: primer set-1 , forward ( 5’-CCAGTGTGGTGGAATTGCCCTTGCTATGCCCATCACTCGGATGCGC-3’ ) and reverse ( 5’-CATTTTACCAACAGTACCGGAATGCCAAGCTTCGGTGCACAGGGAATGGCCTG-3’ ) ; primer set-2 , forward ( 5’-CAGGCCATTCCCTGTGCACCGAAGCTTGGCATTCCGGTACTGTTGGTAAAATG-3’ ) and reverse ( 5’-GCGCATCCGAGTGATGGGCATAGCAAGGGCAATTCCACCACACTGG-3’ ) . The pGL2-CASP1p1 ( −488 to −8 relative to the CASP1 ORF ) and pGL2-CASP1p2 ( −488 to -66 ) luciferase reporter plasmids were constructed into the pGL2-basic vector ( Promega ) by using the Gibson assembly and the following two primer sets for pGL2-CASP1p1: primer set-1 , forward ( 5’-GCTCTTACGCGTGCTAGCTCGAGTGTGAAAAGAAGGACATTAAATAAGAA-3’ ) and reverse ( 5’-CAACAGTACCGGAATGCCAAGCTTCTCTCCTCCCTTCTTGTGTGAC-3’ ) ; primer set-2 , forward ( 5’-GTCACACAAGAAGGGAGGAGAGAAGCTTGGCATTCCGGTACTGTTG-3’ ) and reverse ( 5’-TTCTTATTTAATGTCCTTCTTTTCACACTCGAGCTAGCACGCGTAAGAGC-3’ ) ; and the following two primer sets for pGL2-CASP1p2: primer set-1 , forward ( 5’-GCTCTTACGCGTGCTAGCTCGAGTGTGAAAAGAAGGACATTAAATAAGAA-3’ ) and reverse ( 5’-CAACAGTACCGGAATGCCAAGCTTGGGCCTGTACATGTATTGGGAAATACTCAC-3’ ) ; primer set-2 , forward ( 5’-GTGAGTATTTCCCAATACATGTACAGGCCCAAGCTTGGCATTCCGGTACTGTTG-3’ ) and reverse ( 5’-TTCTTATTTAATGTCCTTCTTTTCACACTCGAGCTAGCACGCGTAAGAGC-3’ ) . Plasmids pCMV3-N-FLAG-IRF8 ( K108E ) and pGL2-CASP1p1-mut ( IRF8 binding site mutation ) were constructed by using QuikChange II site-directed mutagenesis kit ( Agilent Technologies , Santa Clara , CA , USA ) and the following primer sets: IRF8 ( K108E ) forward ( 5’-GGACATTTCCGAGCCATACGAGGTTTACCGAATTGTTCCTG-3’ ) and reverse ( 5’-CAGGAACAATTCGGTAAACCTCGTATGGCTCGGAAATGTCC-3’ ) ; CASP1p1-mut forward ( 5’-CCAAAAAGGAAGGCGAAGCATACTTTCAGTGGAAGTCACACAAGAAGGGAGGAGAGAAGCTTG -3’ ) and reverse ( 5’-CAAGCTTCTCTCCTCCCTTCTTGTGTGACTTCCACTGAAAGTATGCTTCGCCTTCCTTTTTGG -3’ ) DNA sequences in all these plasmids were authenticated by automatic sequencing . To deplete IRF8 or CASP1 , two different sgRNAs targeting human IRF8 or CASP1 were designed and cloned into lentiCRISPR v2 vector ( a gift from Feng Zhang; Addgene plasmid # 52961 ) [108] . Packaging 293T cells were transfected with IRF8 or CASP1 sgRNAs or negative controls ( non-targeting sgRNA-NC ) and helper vectors ( pMD2 . G and psPAX2; gifts from Didier Trono; Addgene plasmid #s 12259 and 12260 ) using Lipofectamine 2000 reagent ( Cat# 11668019 , Life Technologies ) . Medium containing lentiviral particles and 8 μg/mL polybrene ( Sigma-Aldrich , St . Louis ) was used to infect Akata ( EBV+ ) cells . Infected cells were selected in medium containing 2 μg/mL puromycin . To deplete KAP1 , two different sgRNAs targeting human KAP1 were designed and cloned into lentiCRISPR v2-Blast vector ( a gift from Mohan Babu , Addgene plasmid #83480 ) . Packaging 293T cells were transfected with KAP1 sgRNAs or negative controls ( non-targeting sgRNA-NC ) and helper vectors ( pMD2 . G and psPAX2 ) using Lipofectamine 2000 reagent . Medium containing lentiviral particles and 8 μg/mL polybrene were used to infect caspase-1 knockout cell lines . Infected cells were selected in medium containing 10 μg/mL blasticidin . The target guides sequences are as follows: IRF8-sg1: forward ( 5’-CACCGATTGACAGTAGCATGTATCC-3’ ) and reverse ( 5’-AAACGGATACATGCTACTGTCAATC-3’ ) ; IRF8-sg2: forward ( 5’-CACCGCGGAAATGTCCAGTTGGGAC-3’ ) and reverse ( 5’-AAACGTCCCAACTGGACATTTCCGC-3’ ) ; CASP1-sg1: forward ( 5’-CACCGGACAGTATTCCTAGAAGAAC-3’ ) and reverse ( 5’-AAACGTTCTTCTAGGAATACTGTCC-3’ ) ; CASP1-sg2: forward ( 5’-CACCGTTATCCGTTCCATGGGTGA-3’ ) and reverse ( 5’-AAACTCACCCATGGAACGGATAAC-3’ ) ; sgRNA-NC: forward ( 5’-CACCGTGAGGATCATGTCGAGCGCC-3’ ) and reverse ( 5’-AAACGGCGCTCGACATGATCCTCAC-3’ ) ; KAP1-sg1: forward ( 5’-CACCGGCGGGTGAAGTACACCAAGG-3’ ) and reverse ( 5’-AAACCCTTGGTGTACTTCACCCGCC-3’ ) ; KAP1-sg2: forward ( 5’-CACCGAGTCTCGGGATGGTGAACGT-3’ ) and reverse ( 5’-AAACACGTTCACCATCCCGAGACTC-3’ ) . IRF8 or CASP1 knockdown efficiency was confirmed using western blot analysis and Sanger sequencing . In details , the PAM region ( containing the target site of sgRNA ) was amplified from DNA mixture extracted from three biological IRF8-sg1 , IRF8-sg2 , CASP1-sg1 and CASP1-sg2 pool cells , respectively by using Wizard Genomic DNA Purification Kit ( Fisher ) . The primer sets used for cloning are as follows: IRF8-sg1: forward ( 5’-AATGGTGGTCGGCGGCTTC-3’ ) and reverse ( 5’-AATGGAGGCATCCACTTCCTGATT-3’ ) ; IRF8-sg2: forward ( 5’-GCCTGGGCAGTTTTTAAAGGGAAG-3’ ) and reverse ( 5’-TCGGTAAACTTTGTATGGCTCGGAAA-3’ ) ; CASP1-sg1: forward ( 5’-TCAATTCTGTTCCCCCTTTTCAAT-3’ ) and reverse ( 5’-AGGCTTGTGCTGCATGACTCTTAT-3’ ) ; CASP1-sg2: forward ( 5’-TGGGCTATTTCTGCTTCATTACTTT-3’ ) and reverse ( 5’-CCTTTCGGAATAACGGAGTCAATC-3’ ) . The PCR amplicons were subcloned into pMD19 vectors ( Clontech ) and more than 10 clones were randomly chosen for sequencing . Total RNA from three biological replicates ( cells derived from three distinct lentivrial transductions ) was extracted using ISOLATE II RNA Mini Kit ( Bioline ) . The library construction , cluster generation and HiSeq ( Illumina ) sequencing were performed with by the Genomics Sequencing Core of the Department of Environmental Health ( University of Cincinnati ) following the previous reported methods [109] . Raw fastq data were analyzed by using Galaxy ( https://usegalaxy . org/ ) . Human genome ( hg38 ) was used as the reference genome . Differential gene expression between IRF8-depleted ( IRF8-sg2 ) and control ( NC ) cells was analyzed by using DESeq2 [110] . The differentially expressed genes were selected based on a false-discovery rate–adjusted q-value ( q< 0 . 05 ) . Genes with more than 2-fold change were selected for further analysis . RNA-seq raw data have been submitted to National Center for Biotechnology Information ( NCBI ) Sequence Read Archive ( SRA; accession numbers: SRP107862 ) with access URL https://www . ncbi . nlm . nih . gov/Traces/study/ ? acc=SRP107862 . 2x107 Akata ( EBV+ ) , LCL and P3HR-1 cells were cross-linked individually in 1% ( w/v ) formaldehyde ( Sigma ) for 5 min at room temperature and the cross-linking reaction was quenched by addition of glycine to a final concentration of 0 . 125M . Cells were washed twice with cold PBS and lysed in 1 ml of cell lysis buffer ( 10 mM Tris-HCl [pH 8 . 0] , 10 mM NaCl , 0 . 2% [v/v] NP40 , 10 mM Sodium butyrate , 50 μg/ml PMSF ) with fresh added complete protease inhibitor on ice for 10 min . After centrifuge at 2 , 500 rpm at 4°C for 5 min , the supernatant was discarded and the nuclei were resuspended in 1 . 2 ml nuclei lysis buffer ( 50 mM Tris-HCl [pH 8 . 1] , 10 mM EDTA , 1% [w/v] SDS , 10 mM Sodium butyrate , 50 μg/ml PMSF ) with fresh added complete protease inhibitor on ice for 10 min . Then sonication was performed with a Diagenode Bioruptor 300 . After extract clearing by centrifugation , supernatants were diluted 1:10 in dilution buffer ( 20 mM Tris-HCl [pH 8 . 1] , 150 mM NaCl , 2 mM EDTA , 1% [v/v] Triton X-100 , 0 . 01% [w/v] SDS , 10 mM Sodium butyrate 50 μg/ml PMSF ) with fresh added complete protease inhibitor . Aliquots of each input chromatin lysate were reserved for PCR analysis . 1 ml of diluted chromatin lysate was incubated with ChIP-grade antibodies with rotation at 4°C overnight . Primary antibodies used were anti-IRF8 ( Santa Cruz , Cat # sc-6058X ) , normal goat IgG ( Santa Cruz , Cat # sc-2028 ) , anti-IRF1 ( abcam , Cat # ab26109 ) , and normal rabbit IgG ( Santa Cruz , Cat # sc-2027 ) . 25 μl Protein A/G magnetic beads ( life technologies , 10002D and 10004D ) were added to each 1 ml ChIP and incubated for 2 hour at 4°C with rotation . Next , magnetic beads were pelleted with magnetic separation rack and washed once with cold low salt wash buffer ( 20 mM Tris-HCl [pH8 . 1] , 2 mM EDTA , 150 mMNaCl , 1% [v/v] Triton X-100 , 0 . 1% [w/v] SDS ) , once with high salt wash buffer ( identical to low salt wash buffer , except 500 mM NaCl ) , once with LiCl wash buffer ( 10 mM Tris-HCl [pH8 . 1] , 1 mM EDTA , 0 . 25 M LiCl , 1% [v/v] NP40 , 1% Deoxycholic acid ) , and finally twice with TE buffer ( 10 mM Tris-HCl [pH8 . 1] , 1 mM EDTA ) . Samples were then resuspended in 150 μl of elution buffer ( 0 . 1 M NaHCO3 , 1% [w/v] SDS ) and rotated for 20 min at room temperature . Two rounds of elution of protein-DNA complexes were pooled . Reversal of cross-linking was accomplished by incubation of pooled eluates at 65°C for 4 hours after addition of NaCl to final concentration of 200mM and 100 ug/ml Proteinase K . DNA was purified by phenol-chloroform extraction followed by isopropanol-sodium acetate precipitation and then resuspended in 100 μl nuclease-free water and quantified using regular PCR . Purified input chromatin lysate was used in PCR reactions for standardization . ChIP primers used to amplify the CASP1 promoter are: forward ( 5’-TACACTACCTGATGCAGGCTA-3’ ) and reverse ( 5’-TGAAACTGAAAGTATGCTTCG-3’ ) . Total RNA was extracted using ISOLATE II RNA Mini Kit ( Bioline ) . Reverse transcription was carried out by using High Capacity cDNA Reverse Transcription Kit ( Invitrogen ) . Quantitative PCR ( qPCR ) was performed using an ABI Prism 7000 Sequence Detector with SYBR Green . The PCR reactions were set up in a 96-well optical plate in duplicate by adding the following reagents into each well: 2 μl of cDNA , 10 μl of SYBR Green PCR Master Mix ( Applied Biosystems , Foster City , CA , USA ) ; the final concentrations of primers were 0 . 3 μmol/L in a final volume of 20 μl . The PCR amplification protocol was initiated at 50°C for 2 min followed by 10 min at 95°C and 40 PCR cycles consisting of 15 seconds at 95°C followed by 60°C for 1 min . All samples were tested with the reference gene β-actin for data normalization to correct for variations in RNA quality and quantity . The specificity of amplification of targets with high Ct values was confirmed by analysis of the temperature dissociation curves . Primers used for measuring gene transcriptional level: RTA and β-actin primers were described previously [13]; ZTA primers are forward 5’-AGGCCAGCTCACTGCCTATC-3’ and reverse 5’-TGATTCTGGGTTATGTCTGA-3’; BGLF2 primers are forward 5’-ATCTGGCACCTGTCCTTGTC-3’ and reverse5’-GGGACCTCTTTCCCATTAGC-3’; BGLF4 primers are forward 5’-GGCAATAGAGGCGATAGAGC-3’ and reverse 5’-TGGTCCTGACTGATTATGGG-3’; CASP1 primers are forward 5’-ATAGCTGGGTTGTCCTGCAC-3’ and reverse 5’-GCCAAATTTGCATCACATACA-3’; AIM2 primers are forward 5’-TAGCGCCTCACGTGTGTTAG-3’ and reverse 5’-TTGAAGCGTGTTGATCTTCG-3’; IFNB1 primers are forward 5’-CAGGAGAGCAATTTGGAGGA-3’ and reverse 5’-CTTTCGAAGCCTTTGCTCTG-3’; SLAMF7 primers are forward 5’-GAACCGACCAGCTCTTTCAC-3’ and reverse 5’-AATATGGCTGGTTCCCCAAC-3’; SULF1 primers are forward 5’-ATCCTGGTTGAATAATCAATCTCT-3’ and reverse 5’-ATGCAGGTTCTTCAAGGCAG-3’; TNFSF10 primers are forward 5’-AGCAATGCCACTTTTGGAGT-3’ and reverse 5’-TTCACAGTGCTCCTGCAGTC-3’; MX1 primers are forward 5’-GATGATCAAAGGGATGTGGC-3’ and reverse 5’-AGCTCGGCAACAGACTCTTC-3’; DAPL1 primers are forward 5’-TGCCCTGAATGACGCACTG-3’ and reverse 5’-GTGGGTTTTTGATGCGCCAT-3’; CASP8 primers are forward 5’-TGTCCAGTTGTTCCCCAATA-3’ and reverse 5’-GGTCACTTGAACCTTGGGAA-3’ . The pLX304 vector was a gift from David Root ( Addgene plasmid # 25890 ) . The V5-tagged pLX304-IRF8 was purchased from DNASU Plasmid Repository . To prepare lentiviruses , 293T cells were transfected with empty vector or pLX304 containing the gene of IRF8 and the help vectors ( pMD2 . G and psPAX2 ) using Lipofectamine 2000 reagent . The supernatants were harvested at 48 h after transfection . The medium containing lentiviral particles and 8 μg/mL polybrene were used to infect IRF8-depleted ( sg2 ) cell lines . Infected cells were selected in medium containing 10 μg/mL blasticidin . Luciferase assay was performed as previously described [16] . Briefly , 293T cells were co-transfected with the firefly luciferase reporter vectors along with IRF8 ( WT or K108E mutant ) , IRF1 , and renilla expression plasmids using Lipofectamine 2000 reagent ( Cat# 11668019 , Life Technologies ) . The Akata ( EBV+ ) cell was transfected using electroporation method . For plasmid transfection , 10 μg each of plasmid were mixed with 5x106 cells in a 4-mm cuvette . Electroporation was performed at 970 μF and 0 . 2 V with a Gene pulser Xcell system ( Bio-Rad ) . The cells were transferred to new plates contain 10 ml pre-warmed fresh medium . At thirty-six hours post-transfection , cell extracts were prepared and assayed with the dual-luciferase assay kit from Promega ( Cat #E1960 , Madison , WI , USA ) . Each condition was performed in triplicate . Akata ( EBV+ ) cells were treated with 50 μg/ml of goat anti-human IgG ( MP Biomedicals ) for 24 and 48 h to induce the EBV lytic cycle . For caspase inhibition assay , Akata ( EBV+ ) cells were untreated or pretreated with pan-caspase inhibitor for 1 hr and then treated with anti-IgG ( 1:200 , Cat# 55087 , MP Biomedicals ) for additional 48 hrs . EBV reactivation in P3HR-1 cells was triggered by addition of TPA ( 20 ng/ml ) and sodium butyrate ( 3 mM; Millipore , Cat# 19–137 ) . The EBV lytic replication in LCL cells was induced by addition of gemcitabine ( 1 μg/mL; Fisher Scientific , Cat# NC9325685 ) . To induce the BCR activation , the LCL cells were treated with anti-IgM antibody ( 20 μg/mL , Cat# 2020–01 , Southern Biotech ) for 0 to 48 hrs . To measure EBV replication , intracellular viral DNA and virion-associated DNA present in culture supernatant were determined by qPCR analysis [13] . Total genomic DNA was extracted by using Wizard Genomic DNA Purification Kit ( Promega , Madison , WI , USA ) . For extracellular viral DNA extraction , the supernatant ( 120 μl ) was treated with 4 μl RQ1 DNase ( Promega ) for 1 h at 37°C , and reactions were stopped by adding 20 μl of stop buffer and incubation at 65°C for 10 min; 12 . 5 μl proteinase K ( 20 mg/ml , Invitrogen ) and 25 μl 10% ( wt/vol ) SDS then were added to the reaction mixtures , which were incubated for 1 h at 65°C . DNA was purified by phenol-chloroform extraction followed by isopropanol-sodium acetate precipitation and then resuspended in 100 μl nuclease-free water . qPCR was performed as mentioned above . Relative levels of viral DNA were normalized to supernatant viral DNA without lytic induction . The BALF5 primers used for quantitating EBV copy numbers were described previously [13 , 105] . The reference gene β-actin was used for data normalization . In vitro cleavage assay was performed as previously described [94] . Briefly , HA-tagged KAP1 was immunoprecipitated from transfected 293T cells using HA magnetic beads . The beads-bound HA-KAP1 and individual active caspases ( active human caspases group IV; ApexBio , Cat# K2060 ) were incubated in caspase assay buffer ( 50 mM HEPES , pH7 . 2 , 50 mM NaCl , 0 . 1% Chaps , 10 mM EDTA , 5% Glycerol and 10mM DTT ) at 37°C for 2 hrs . Reactions were stopped by boiling in 2× SDS sample buffer and samples were analyzed by western blot . Cell lysates were harvested in lysis buffer including protease inhibitors ( Roche ) as described previously[106] . Protein concentration was determined using the Bradford assay ( Biorad ) , and proteins were separated in SDS 4–20% polyacrylamide gels and then transferred onto a PVDF membrane . Membranes were blocked in TBS containing 5% milk , and 0 . 1% Tween 20 solution . Membranes were then incubated in the following primary antibodies: mouse anti-ZTA ( Argene , Cat # 11–007 , 1:5 , 000 ) , mouse anti-RTA ( Argene , 1:1 , 000 ) , mouse anti-BGLF4 antibody ( 1:1 , 000 ) [111] , anti-β-actin ( Sigma , Cat # A5441 , 1:5 , 000 ) , anti-IRF8 ( CST , Cat #5628 , 1:1 , 000 ) , anti-PARP ( CST , Cat #9532 , 1:1 , 000 ) , anti-Cleaved PARP ( CST , Cat #5625 , 1:1 , 000 ) , anti-Cleaved Caspase Substrates ( CST , Cat #8698 , 1:1 , 000 ) , anti-Caspase-1 ( CST , Cat #3866 , 1:1 , 000 ) , anti-Caspase-2 ( CST , Cat #2224 , 1:1 , 000 ) , anti-Caspase-3 ( Santa Cruz , Cat #sc-7148 , 1:1 , 000 ) , anti-Cleaved Caspase-3 ( CST , Cat #9664 , 1:1 , 000 ) , anti-Caspase-7 ( CST , Cat #12827 , 1:1 , 000 ) , anti-Cleaved Caspase-7 ( CST , Cat #8438 , 1:1 , 000 ) , anti-Caspase-8 ( CST , Cat #9746 , 1:1 , 000 ) , anti-Cleaved Caspase-8 ( CST , Cat #9496 , 1:1 , 000 ) , anti-Caspase-9 ( CST , Cat #9508 , 1:1 , 000 ) , anti-Bcl-2 ( Bethyl , Cat #A303-675A , 1:1 , 000 ) , anti-KAP1 ( CST , Cat #4123 , 1:1 , 000 ) , anti-PAX5 ( CST , Cat #8970 , 1:1 , 000 ) , anti-DNMT3A ( Bethyl , Cat #A304-278A , 1:1 , 000 ) , anti-STAT3 ( CST , Cat #9139 , 1:1 , 000 ) , and anti-HA ( CST , Cat #14031S , 1:1 , 000 ) . The secondary antibodies used were horseradish peroxidase ( HRP ) -labeled goat anti-mouse antibody ( Fisher Scientific , 1:5 , 000 ) and HRP-labeled anti-rabbit antibody ( Fisher scientific , 1:5 , 000 ) . Potential caspase cleavage sites were searched for all the EBV protein sequences using PeptideCutter ( http://web . expasy . org/peptide_cutter/ ) and the GraBCas software [96 , 97] . All numerical data were presented as mean ± standard deviation of triplicate assays . The statistical significances were determined using Student’s two-tail t-test , where p<0 . 05 was considered statistically significant . | Infection with Epstein-Barr virus ( EBV ) is closely associated with human cancers of both B cell and epithelial cell origin . The EBV life cycle is tightly regulated by both viral and cellular factors . Here , we demonstrate that interferon regulatory factor 8 ( IRF8 ) is required for EBV lytic replication . Mechanistically , IRF8 directly regulates caspase-1 expression and hence caspase activation upon B cell receptor ( BCR ) stimulation and chemical induction , which leads to the cleavage and de-stabilization of several host factors suppressing lytic replication , including KAP1 . Caspase-1 depletion blocks EBV reactivation while KAP1 depletion facilitates reactivation in caspase-1 depleted cells . These results together establish a IRF8/caspase-1/KAP1 axis important for EBV reactivation . | [
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] | 2018 | Interferon regulatory factor 8 regulates caspase-1 expression to facilitate Epstein-Barr virus reactivation in response to B cell receptor stimulation and chemical induction |
Echocardiographic screening for detection of latent RHD has shown potential as a strategy to decrease the burden of disease . However , further research is needed to determine optimal implementation strategies . RHD results from a complex interplay between environment and host susceptibility . Family members share both and relatives of children with latent RHD may represent a high-risk group . The objective of this study was to use echocardiographic family screening to determine the relative risk of RHD among first-degree relatives of children with latent RHD compared to the risk in first-degree relatives of healthy peers . Previous school-based screening data were used to identify RHD positive children and RHD negative peers . All first-degree relatives ≥ 5 years were invited for echocardiography screening ( 2012 World Heart Federation Criteria ) . Sixty RHD positive cases ( 30 borderline/30 definite RHD ) and 67 RHD negative cases were recruited . A total of 455/667 ( 68% ) family members were screened . Definite RHD was more common in childhood siblings of RHD positive compared to RHD negative ( p = 0 . 05 ) . Children with any RHD were 4 . 5 times as likely to have a sibling with definite RHD , a risk that increased to 5 . 6 times when considering only cases with definite RHD . Mothers of RHD positive and RHD negative cases had an unexpectedly high rate of latent RHD ( 9 . 3% ) . Siblings of RHD positive cases with RHD are more likely to have definite RHD and the relative risk is highest if the index case has definite RHD . Future screening programs should consider implementation of sibling screening following detection of an RHD positive child . Larger screening studies of adults are needed , as data on prevalence of latent RHD outside of childhood are sparse . Future studies should prioritize implementation research to answer questions of how RHD screening can best be integrated into existing healthcare structures , ensuring practical and sustainable screening programs .
Rheumatic heart disease ( RHD ) , the long-term consequence of acute rheumatic fever ( ARF ) , is the result of a complex interplay between host and environment . Endemic areas are consistently marked by poverty , poor sanitation , and limited access to primary healthcare [1] . These factors increase the incidence of group A β-hemolytic streptococcal ( GAS ) carriage , infection , and transmission . Repeated , untreated GAS infections create the substrate for development of ARF , a systemic immune system over-reaction that results , for many , in RHD [2] . However , environmental exposure is only one component of RHD susceptibility . Even in the presence of endemic GAS and poor primary prevention ( penicillin for acute streptococcal pharyngitis ) not all children are equally at risk . ARF follows only 3–6% of cases of GAS and only 40% of children with ARF develop chronic RHD [3] . Historically , RHD was noted to cluster in families , and a meta-analysis of twin studies showed a pooled concordance risk for ARF of 44% in monozygotic twins and 12% in dizygotic twins , giving an estimated heritability of 60%[4] . The majority of these data were captured from observational studies of ARF , and pre-dated routine echocardiography [5] . In many low-resource settings today , presentation with ARF has become rare even as echocardiographic screening of school-aged children has revealed a large burden of latent RHD ( RHD apparent on echocardiography that has not previously come to clinical attention ) . Given what is known about genetic susceptibility and a shared environment , it is reasonable to assume that family members of children with latent RHD may themselves be at greater risk of latent RHD . However contemporary echocardiographic screening of families living in RHD endemic areas has not been reported . The objective of this study was to use echocardiographic family screening to determine the relative risk of RHD among first-degree relatives of children with latent RHD compared to the risk in first-degree relatives of healthy peers .
We utilized a cross-sectional family design to compare the risk of RHD among first-degree family members of primary school children previously identified with latent RHD compared to the first-degree family members of age/gender matched children with normal echocardiograms . The study occurred over a 3-month period from February-April , 2015 . Informed consent was obtained from all participants at least 18 years of age , and informed assent and parental permission was obtained for those between 5–17 years . Approval for this study was granted from the Institutional Review Boards at Children’s National Health System , Washington DC , Makerere University School of Medicine , Kampala , Uganda , and the Ugandan National Council of Science and Technology . RHD positive index cases included children with borderline or definite RHD ( 2012 WHF criteria ) , identified through previous echocardiographic school screening programs in the Gulu District of Northern Uganda in 2014 . [6] These children are followed clinically at the Gulu Regional Referral Hospital , Gulu , Uganda . RHD negative index cases were recruited from screen-negative peers who were similar in age and gender and attending the same schools ( reflecting the same general socioeconomic status ) . All RHD positive and RHD negative index children underwent repeated echocardiographic evaluation at time of study enrollment to ensure their RHD status had not changed since first screen in 2014 . The parents/guardians of RHD positive and RHD negative index children were approached to invite them , and all first-degree relatives ( ≥5 years of age ) in the family , to undergo echocardiographic screening to evaluate for the presence of latent RHD . Children without at least one parent alive/available were excluded . Following family recruitment , a list of all first-degree family members ( at least 5 years of age ) –living or deceased was captured . For living family members , age , gender , and known history of ARF/RHD were recorded . For family members who were deceased , attempts were made to understand the cause of death . For those family members who were alive but unavailable for screening , the reason for absence was recorded . Each participating family member underwent a focused transthoracic echocardiogram performed by a pediatric cardiologist ( TA ) with expertise in RHD . A standard acquisition protocol in the parasternal long , parasternal short , and apical 4- and 5-chamber views focused on assessment of the mitral and aortic valves . Additional views were obtained when needed . All images were obtained using fully functional standard portable echocardiographic equipment ( GE , VIVID Q , Milwaukee , WI ) ( Fig 1 ) . Studies were transferred through a secure telemedicine system to PACS ( Philips Xcelera , Best , Netherlands ) for offline review . Three reviewers ( AB , CS , AT ) , blinded to the RHD/- status of the index child reviewed studies and classified them according to the 2012 WHF criteria ( S1 Table ) ( normal , borderline RHD , definite RHD , or other for subjects ≤20 years of age and normal , definite RHD , or other for subjects >20 years of age ) [7] . All positive studies were confirmed by a second reviewer and , in cases of disagreement , a third reviewer determined the final classification . Demographic information is presented by number and percentage , and where applicable with standard deviation . Continuous variables were compared using Student’s t-test . Fisher’s exact tests were used to evaluate the exact probability under the null hypothesis of observing results as or more extreme based on comparisons of differences in categorical variables between study groups . Poisson Regression was used to estimate the average risk and relative risk of RHD positivity in first-degree family members of RHD positive and RHD negative index children . The method of Poisson Regression was chosen because it appropriately handles outcomes based on counts , including low frequency counts , that generally do not meet criteria for tests requiring the data to meet the parametric assumption and appropriately accounts for the natural clustering of family data . Prevalence rates of RHD among mothers vs . fathers vs . siblings are presented as percentages and compared using model z-statistics . Relative risk was also presented according to the presence of borderline vs . definite RHD in index children . Agreement between reviewers was calculated with the Kappa statistic . Greatest emphasis was placed on results that achieved statistical significance at the p<0 . 05 level , but substantive differences that achieved borderline significance were also described .
The index group consisted of 61 RHD positive children ( 30 with definite RHD and 31 with borderline RHD ) and 67 RHD negative children ( Table 1 ) , generating a complete list of 320 ( 5 . 3/child ) and 347 ( 5 . 2/child ) first-degree family members of RHD positive and RHD negative index subjects , respectively , p = 0 . 22 . During enrollment , 1 child ( borderline RHD ) was excluded from participation when no biological parent could attend screening–leaving 60 RHD positive index cases and 67 RHD negative index cases . Of the 667 identified first-degree relatives , 455 ( 68 . 2% ) attended screening including 107 mothers ( 83 . 5% ) , 48 fathers ( 37 . 8% ) , and 300 siblings ( 72 . 6% ) ( Table 2 ) . Fathers ( 24/127 , 19% ) were more likely to be deceased than mothers ( 3/127 , 2 . 4% , p<0 . 01 ) , with the reasons for paternal death including HIV/AIDS ( 6 ) , accidental trauma ( 5 ) , other illness ( 5 ) , the LRA conflict ( 3 ) , and other/unknown ( 5 ) . Fathers who were alive were also less likely to be available for screening ( 55/103 , 53% unavailable ) than mothers ( 17/124 , 14% unavailable , p<0 . 01 ) . Siblings of RHD negative cases were less available to participate in screening ( p = 0 . 03 ) . A breakdown of reasons for all family members who were alive but unavailable and those who are deceased are listed ( Table 3 ) . No absent family members were reported to have cardiovascular symptoms and no causes of death were known to be attributable to cardiac disease . The prevalence of all latent RHD was similar in first-degree relatives of RHD positive and RHD negative cases 9 . 8% vs . 9 . 0% ( 23/235 screened vs . 20/220 screened , p = 0 . 87 ) . Similarly there was no difference between prevalence of definite latent RHD between groups ( Cases: 11/235 , 4 . 3% vs . Controls: 9/220 , 4 . 1% , p = 1 . 00 ) . Definite RHD was more likely to be found in mothers , with 9 . 3% ( 10/107 screened ) having echocardiographic evidence of definite RHD , compared to fathers 0% ( 0/48 screened , p = 0 . 03 ) , and siblings 3 . 3% ( 10/300 screened , p = 0 . 02 ) . Borderline RHD , a category reserved only for those ≤20 years of age , was similar prevalence between siblings of RHD positive vs . RHD negative ( 7 . 7% vs . 8 . 1% , p = 1 . 00 ) . However , definite RHD was more common among siblings of RHD positive cases ( 5 . 2% vs . 1 . 4% , p = 0 . 11 ) , but only reached borderline significance . There were 7 families ( 4 cases , 3 controls ) where 2 or more first-degree relatives were found to be RHD positive ( Fig 2 ) . There was no increased familial , or sibling risk of RHD in the first-degree relatives of RHD positive cases ( borderline & definite RHD ) vs . RHD negative cases . However , RHD positive cases had a 4 . 5 times greater chance of having a sibling with definite RHD ( p = 0 . 05 ) and this risk increased to 5 . 6 times greater chance if you limited the comparison to RHD positive cases with definite RHD ( n = 30 , p = 0 . 03 ) ( Table 4 ) . There was 97% agreement between reviewers 1 and 2 ( κ = 0 . 86 , 95% CI 0 . 78–0 . 93 ) , with 13 cases of non-agreement adjudicated by the third reviewer . All cases of non-agreement were between the diagnoses of “borderline RHD” or “normal” with 100% agreement on the diagnosis of definite RHD .
In conclusion , siblings of RHD positive cases with any RHD are more likely to have definite RHD and the relative risk is highest if the index case has definite RHD . Future screening programs should consider implementation of sibling screening following detection of an RHD positive index case . Follow-up of this cohort is needed to determine if latent RHD that exists in more than one family member is more likely to persist and progress . Future studies should prioritize implementation research to answer questions of how RHD screening can best be integrated into existing healthcare structures , ensuring practical and sustainable screening programs . | Rheumatic heart disease ( RHD ) affects at least 33 million people , most of who live in low-resource environments . RHD is a cumulative process and there exists a latent period between early valve damage and presentation with symptoms . Echocardiographic screening ( ultrasound of the heart ) has proven highly sensitive for latent RHD detection , but implementation research is needed to effectively develop sustainable public health strategies . Critical to this research is determining whom to screen . As family members have both a shared environment and shared genetic susceptibility , they may represent a high-risk group that could be targeted once a case of RHD is identified . We conducted an echocardiographic family screening study to determine the risk of RHD in families with and without an RHD positive child and found that siblings of children with latent RHD are more likely to have latent RHD themselves . Our data suggest that siblings may represent a particularly high-risk group that could be targeted for echocardiographic screening . Future studies are needed to answer questions of how RHD screening can best be integrated into existing healthcare structures , ensuring practical and sustainable RHD screening programs . | [
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] | 2016 | Targeted Echocardiographic Screening for Latent Rheumatic Heart Disease in Northern Uganda: Evaluating Familial Risk Following Identification of an Index Case |
Single-cell RNA-sequencing ( scRNA-seq ) provides new opportunities to gain a mechanistic understanding of many biological processes . Current approaches for single cell clustering are often sensitive to the input parameters and have difficulty dealing with cell types with different densities . Here , we present Panoramic View ( PanoView ) , an iterative method integrated with a novel density-based clustering , Ordering Local Maximum by Convex hull ( OLMC ) , that uses a heuristic approach to estimate the required parameters based on the input data structures . In each iteration , PanoView will identify the most confident cell clusters and repeat the clustering with the remaining cells in a new PCA space . Without adjusting any parameter in PanoView , we demonstrated that PanoView was able to detect major and rare cell types simultaneously and outperformed other existing methods in both simulated datasets and published single-cell RNA-sequencing datasets . Finally , we conducted scRNA-Seq analysis of embryonic mouse hypothalamus , and PanoView was able to reveal known cell types and several rare cell subpopulations .
Single-cell RNA-sequencing ( scRNA-seq ) has attracted great attention in recent years . Unlike traditional bulk RNA-seq analysis , scRNA-seq provides access to cell-to-cell variability at the single-cell level . This allows defining individual cell types , and subtypes , among a population containing multiple types of cells , and also makes possible following how individual cell types change over time or after being exposed to various perturbations [1–4] . Classifying single cells based on their expression profile similarity is the basis for scRNA-seq analysis . A variety of clustering approaches have been developed and applied to scRNA-seq analysis such as hierarchical clustering [5–7] , K-means clustering [8–11] , SNN-Cliq [12] , pcaReduce [13] , SC3 [14] , Seurat [3 , 15] , SCANPY [16] , RCA [17] , and dropClust [18] . There are also algorithms , like RaceID/RaceID2 [4 , 19] and GiniClust [20] , were developed specifically to identify rare cell types . Nevertheless , one challenge is that clustering results are often highly sensitive to input parameters , and sometimes the required parameters are not intuitive to users ( S1 Table ) . For example , DBSCAN [21] is a clustering that required two parameters to classify clusters based on the densities of subpopulations , and has been applied in some scRNA-seq studies [3 , 22] . However , it is difficult for users to pick proper required parameters without the aid of other computer programs and different parameters can lead to different clustering results ( S1 Fig and S2 Fig ) . Furthermore , it is also challenging for density-based clustering algorithms to properly handle clusters with different densities [23] . This can often be the case for single cell clustering because different cell types can exhibit different levels of variation in similarity among the cluster members . To address these issues , we have developed Panoramic View ( PanoView ) , which utilizes an iterative approach that searches cell types in an evolving principal component analysis ( PCA ) space . The strategy is that we identify the cell cluster with the most confidence in each iteration and repeat the clustering algorithm with the remaining cells in a new PCA space ( Fig 1A ) . We define the most confident cluster as the “mature” subpopulation that has the lowest variance in the current PCA space . To cluster cells in a given PCA space , we have developed a novel density-based algorithm , namely Ordering Local Maximum by Convex hull ( OLMC ) ( Fig 1B–1D ) , that uses a heuristic approach to estimate the required parameters based on the input data structures ( see Methods ) .
To evaluate the performance of PanoView , we first tested 1 , 200 simulated data with varying configuration parameters ( e . g . numbers of clusters and standard deviation of the members within clusters ) . The performance of the clustering was evaluated using the Adjusted Rand Index ( ARI ) , which measures the similarity between the cell membership produced by a chosen method and the ground truth [24] . We compared the performance of PanoView with 9 existing methods , including pcaReduce [13] , SC3 [14] , Seurat [15] , SCANPY [16] , RCA [17] , K-means without prior dimensional reduction , PCA followed by DBSCAN , PCA followed by K-means , and t-SNE followed by K-means . The results showed that PanoView and SCANPY outperformed other benchmarking methods in all datasets tested using default parameters . Although we input the correct number of clusters for K-means and pcaReduce , their performance decreased in the datasets with a large number of clusters ( K-means , t-SNE +Km , PCA+Km , pcaReduce in Fig 2A ) . For DBSCAN , we tuned the required parameters until they reached optimal performance in datasets with n = 3 and 4 ( PCA+DB in Fig 2A ) . However , its performance dropped significantly when n>10 . We also observed a similar outcome in Seurat , whose performance dramatically dropped for n>17 . It is worthy to note that these methods could achieve much better performance if we tune the parameters for each dataset . In this study , we only used the default parameters for all the methods and evaluated the robustness of the methods with different datasets . SC3 and RCA with default parameters did not produce usable clustering result for the simulated datasets . We applied PanoView to 11 published scRNA-seq datasets , ranging in size from 90 cells to 20 , 921 cells ( S2 Table ) . We used the reported clustering results as the ground truth for the calculation of ARI , assuming that the authors optimized their analysis correctly with the expertise in the research topics . Based on the overall performance of eight tested methods , we divided them into two tiers by the median value of 0 . 5 in ARI ( Fig 2B ) . The median values of ARI in the first tier are 0 . 766 ( PanoView ) , 0 . 614 ( SC3 ) , 0 . 535 ( RCA ) , and 0 . 505 ( Seurat ) . For the second tier , the median values are 0 . 483 ( SCANPY ) , 0 . 411 ( pcaRecue ) , 0 . 327 ( PCA+DB ) , 0 . 325 ( Kmeans ) , 0 . 255 ( PCA+Km ) , 0 . 318 ( t-SNE +Km ) . This difference in tiers was not surprising , as the methods in the first tier were specifically designed for single-cell analysis . Though SCANPY and pcaReduce were also developed for the analysis of single cells , they did not show good performance in this study . In the first tier , four methods seem to have relatively similar performance . However , there is a noticeable difference in the datasets that exceed 3 , 000 cells . Fig 2C shows that for these larger datasets , PanoView outperformed the other methods by a significant margin , so that the median value of ARI was 0 . 729 and the rest of methods were 0 . 488 ( RCA ) , 0 . 411 ( SC3 ) , 0 . 298 ( SCANPY ) , 0 . 447 ( Seurat ) , 0 . 305 ( pcaReduce ) , 0 . 282 ( t-SNE +Km ) , 0 . 378 ( PCA+DB ) , 0 . 245 ( Kmeans ) , 0 . 185 ( PCA+Km ) . We also observed that PanoView displayed relatively less variation . For smaller datasets , PanoView ( median: 0 . 766 ) still ranked first among all methods tested ( Fig 2D ) . The result of ARI values for all methods is provided in S3 Table . The observed difference in performance between PanoView and other methods is statistically significant . S5 Fig shows that PanoView performed statistically better than six methods that include RCA , pcaReduce , t-SNE+Km , PCA+DB , Kmeans , and PCA+Km . When we further evaluated the datasets that contain more than 3 , 000 cells in S5 ( B ) Fig , PanoView’s performance was better than eight methods except for RCA . In the case of datasets that have fewer than 3 , 000 cells , PanoView performed significantly better than three methods ( RCA , PCA+DB , PCA+Km ) . We also examined the computational cost of PanoView in the real scRNA-seq datasets . It is not surprising that data analysis takes longer when datasets contain more cells ( Fig 3 ) . We also compared the computational cost with other methods , which generated reasonable clustering results . It is obvious that PanoView is not the fastest algorithm . SCANPY , Seurat and RCA are faster than PanoView . It is interesting that SC3 and pcaReduce are slower than PanoView and they failed to generate clustering results for the largest dataset . PannoView produced the results using default parameters . We investigated whether the default parameters produced the optimal results . We have 8 variables in the PanoView , including Zscore , Gini , Bc , Bg , Maxbb , CellNumber , GeneLow , Fclust_height ( see Methods for details ) . If we provided 3 values for each variable , including one default value , we have 6 , 561 different combinations of these parameters . Since it takes too long to use all potential combinations , we executed PanoView with 500 randomly picked combinations on the 10 scRNA-seq datasets ( To save the computational time , we didn’t include the Campbell et al dataset for this analysis ) . Based on the sampling results from the 500 combinations , we found that the default parameter set could produce overall good clustering results across the 10 datasets , ranking in the top 98 . 2 percentile among the 500 parameter sets ( Fig 4A and 4B ) . The similar observation was made for each individual dataset ( Fig 4C ) , although the default parameters performed better in some datasets than others . The 500 clustering results are provided in S4 Table . To evaluate the ability to identify rare cell types , we first applied PanoView to 260 simulated datasets and benchmarked it with Seurat , GiniClust , RaceID2 , and SCANPY . GiniClust and RaceID2 are two single-cell methods that were specifically designed for detecting rare cell types . We used recovery rate and false positive rate to evaluate the performance of detecting rare cell types ( table in Fig 5 ) . PanoView had the best performance that it correctly recovered the rare cell subpopulation in 87 . 31% of datasets . Although GiniClust recovered 66 . 54% of datasets , there were 85 datasets contained false-positive rare clusters , resulting in a false-positive rate of 32 . 69% . In the case of PanoView , only 6 datasets had false-positive rare clusters , resulting in a false-positive rate of 2 . 3% . Seurat had 3 false-positive rare clusters , resulting in a false-positive rate of 1 . 15% . We used one simulated dataset to illustrate the accuracy between methods ( Fig 4B–4F ) . PanoView is the only method that perfectly identified rare cell populations and major cell populations . GiniClust did recover the rare cell populations; however , it also produced false positive cells that were scattered in the three other major clusters . Seurat and SCANPY also showed poor performance in identifying rare cell types . Specifically , Seurat divided the one rare cell type into three clusters , while SCANPY grouped rare cells into one major cluster . RaceID2 did not produce a usable clustering result for this chosen dataset . In addition to simulated datasets , we also used Patel dataset to examine the performance of detecting rare cells ( S4 Fig ) . GiniClust reported that it successfully detected one rare cell type in this dataset [20] , which consists of 9 cells in glioblastoma tumors . These cells were also discovered by the original study showing highly expressed oligodendrocyte genes [6] . In our result ( S4 Fig ) , PanoView identified a cluster ( cluster #2 ) that includes 7 cells , which are corresponding to the rare cells in the original study . SCANPY reported a cluster with 9 cells , among which 8 were the rare cells . SC3 identified a cluster with 10 cells , among which 8 were the rare cells . Seurat assigned 9 rare cells to a major cluster , which has 88 cells in total . A similar outcome was also observed in RCA and pcaReduce that both algorithms merged the rare cells to a major cluster . RaceID2 recovered 8 rare cells from a cluster with 9 cells; however , it also produced many much smaller clusters than the other methods . These results indicated that PanoView not only recovers most rare cells but also produces reasonable clusters representing the heterogeneity in glioblastoma tumors cells . Finally , we applied PanoView to a newly generated scRNA-seq dataset of 959 cells obtained from embryonic day 16 ( E16 ) mouse hypothalamus . The mammalian hypothalamus , which is the central regulator of a broad range of physiological processes and behavioral states , is highly complex at the cellular level [25–27] . Cell subtypes in the developing hypothalamus are very poorly characterized . PanoView identified a total of 11 clusters ( Fig 6A ) , the majority of which consisted of radial glia , neurogenic and gliogenic progenitor cells , immature neurons , as expected . A considerable number of non-neuronal cells were also profiled , including pericytes , endothelial cells , erythrocytes , and macrophages . We selected 12 marker genes to show the specific expression level across 11 clusters ( Fig 6B ) . Four rare cell clusters were also identified , which consisted of a myeloid-like cell type that likely consists of pericyte precursors [28] , tissue-resident microglia , infiltrating monocytes , and an unidentified vascular cell type . With the exception of the last cell type , which likely represents a previously uncharacterized subtype of endothelial or pericyte precursor cell , the other three rare cell types represent cells that are known to be found in the embryonic mouse brain . In this study , we have described the development and performance of PanoView to identify cell subpopulations in single-cell gene expression datasets . Without any tuning of the parameters , PanoView produced reasonable clustering results in 1 , 200 simulated data and 11 published scRNA-seq datasets . Furthermore , without any adjustment , PanoView was able to identify rare cell types in both simulated data and scRNA-seq datasets . The robust performance of PanoView may be the result of both searching cell clusters one by one in the evolving PCA space and improved density-based clustering . Note that it is possible that other clustering methods may show improved performance once we fine-tune their parameters with the input from experienced experts . We believe that PanoView can offer reliable performance with moderate computational cost and can be applied to diverse types of scRNA-seq dataset . The clustering of single cells will automatically identify cell specificity . After the identification of cell types , we are also able to determine the marker genes that show specific expression in each cell type ( e . g . Fig 6B ) . We believe that the cell atlas and the corresponding marker genes will be a valuable resource to study various biological processes .
All experimental procedures were pre-approved by the Institutional Animal Care and Use Committee of the Johns Hopkins University School of Medicine . The key of PanoView is to iteratively search clusters in different sets of variable genes . Our algorithm first performs PCA reduction based on a set of variable genes ( defined below ) . By choosing the first three principal components which explain the largest variance across all cells , PanoView then applies a novel density-based clustering approach , ordering local maximum by convex hull ( OLMC ) , to cluster cells into multiple groups . These groups are evaluated by their variances and the Gini index in the current gene space . PanoView then identifies the best “mature” cluster that is the one with the lowest variance , and the rest of the cells will be put into the next iteration . A new set of variable genes is determined with the remaining cells and the same procedure ( PCA reduction and OLMC ) is repeated . The iteration of PanoView is terminated when no more cluster can be produced , or Gini index reaches a threshold . Next , PanoView produces a hierarchal dendrogram for all generated clusters and merges similar clusters based on the cluster-to-cluster distance . A pseudo-code is provided as the following to detail as to how PanoView works: Algorithm: PanoView Input: expression matrix Einput Output: cluster set M 1: Let Ei = Einput , i = 1 2: while there are variable genes in Ei 3: Generate cluster set Ci by OLMC in 3D PCA 4: Calculate σmin2 , Gini for clusters in Ci 5: if any of Gini > 0 . 05 6: select the mature cluster mi with minimum σmin2 , mi⊆Ci 7: remaining cluster set Ri = Ci−mi 8: Ei+1 = Ei−Ri 9: i = i+1 10: calculate variable genes in Ei+1 11: else if all of Gini < 0 . 05 12: output cluster set M = Ci+m1+⋯+mi 13: stop iteration 14: Generate hierarchal dendrogram for clusters in M 15: Merge nearby clusters if differential cluster-cluster distance < 20% 16: Output hierarchal dendrogram for revised M We adopt the procedure described in Macosko et al to find variable genes [3] . First , all genes are grouped into 20 bins based on their average expression levels . Second , the ratio of variance and mean for genes in each bin is calculated . Third , z-normalization is performed using the ratio of variance and mean in each bin and using the z-score as a threshold to obtain a set of variable genes . The default value of z-score is 1 . 5 ( Zscore = 1 . 5 ) . We also exclude the lower expressed genes whose average expression is less than 0 . 5 ( Genelow = 0 . 5 ) . This selection of variable genes is carried out during each iteration of PanoView . For clustering single cells , we developed ordering local maximum by convex hull ( OLMC ) , a density-based clustering , to identify local maximums in three-dimensional gene space . First , we compute the pairwise Euclidean distance of cells . The distances were grouped into Bc bins ( default value = 20 ) with equally distance interval . The Rc is the bin interval of the histogram that represents the calculated distribution based on the input dataset . Second , we applied the k-nearest neighbors algorithm implemented in Scikit [29] to compute the number of neighbors within distance Rc for each cell . The cells are then ordered based on the number of neighbors , with each cell annotated as Pi , where i is the ranking index from 1 to the total number of cells . P1 represents the global maximum in the space . Third , the cells are equally grouped into Bg bins based on the distance to P1 . The cells in the first bin are considered as the first group G1 , and a convex hull H1 that compose of a set of vertices is constructed . Third , we search for the next local maximum density . Assuming Pm is the first one from the remaining ranked cells , we first define RPmH1 as the distance to the nearest vertices of H1 and R¯H1 is the average of pairwise distance for the vertices of convex hull H1 . If RPmH1<R¯H1 , Pm will be added into the group G1 , and corresponding convex hull H1 is updated ( i . e . expanding ) , suggesting Pm is not a local maximum . If RPmH1>R¯H1 , the new local maximum Pm is located and the corresponding convex hull H2 is constructed based on the distance to Pm . The searching for the next local maximum would be ended if the number of remaining cells is not sufficient to construct a convex hull . Once every local maximum density is located , assign every cell to the nearest local maximum densities . To sum up , the key of OLMC algorithm is to first find where the global maximum density is and use convex hull to locate the next local maximum . To illustrate OLMC , a toy model consisting of 500 random points is provided ( Fig 1B–1D ) . In Fig 1B , each number represents the number of neighbors within Rc = 0 . 5 . The histograms in 1C represent the distance to local maximums and are built by Bg = 10 . The number of 27 in Fig 1B is where the highest density is . The first convex hull ( the cyan in Fig 1D ) is constructed by the points within the first bar ( Fig 1C ) of the distance histogram . After removing the points in the cyan convex hull , the next point with the highest density is where number of 23 is , and the second convex hull is constructed by the points in the first bar ( in green ) of the second histogram that is calculated by distance distribution to the point of 23 , a local maximum density . Followed by the same procedure , the next local maximum ( point of 22 in yellow ) is located and the third convex hull is built . In the end , OLMC identifies the locations of three local maximums , and assign rest of the points to the nearest local maximums . In PanoView , the goal is to find as many clusters as possible during the iterations . Therefore , we adopted a heuristic approach to optimize the bin size Bg that controls the histogram of distance to local maximums for constructing convex hulls . We generated a simulated data of 500 2D points to illustrate the optimization ( S3 Fig ) . By incrementally increase the bin size by 5 , OLMC would reach a saturated state that no more local maximums can be located . We carry out the optimization until the saturated state or the bin size of 100 ( Maxbb = 20 ) Due to the computational efficiency , this optimization is only activated when the number of cells during iterations is smaller than CellNumber = 1000 . Otherwise , the default Bg = 20 . One crucial step in PanoView is to evaluate the clusters produced by OLMC for locating the “mature” cluster during each iteration . The idea is to use Gini index to evaluate the inequality of clusters . PanoView first calculates the pairwise correlation distance xi , j for every cell within each cluster using xi , j=1− ( vi−v¯i ) ∙ ( vj−v¯j ) ‖ ( vi−v¯i ) ‖2‖ ( vj−v¯j ) ‖2 where vi , vj are n-dimensional vectors and v¯i , v¯j are the means of the elements of vector vi , vj , respectively [30] . The algorithm then calculates the variance σ2 of distances xi , j for each cluster and ranked the clusters in the descending order . PanoView then calculates the Gini index Gi ( i = 2 , to n ) , for the top i clusters . Here n is the total number of clusters in this iteration . The Gini index [31] was defined as Gini=∑i=1n∑j=1n|σi2−σj2|2n2μ where σi2 , σj2 are the variances in a population of variances , n is the number of variances , and μ is the mean of a population of variances . If there is a Gini smaller than the threshold of 0 . 05 , PanoView will keep the cluster with the minimum variance ( i . e . the “mature” cluster ) and put the rest of cells into the next iteration . We used Scikit’s sample generator [29] with default parameters except the number of clusters and standard deviation within each cluster . These datasets served as the ground truths to evaluate the ability to identify cell subpopulations for chosen computational methods . Each simulated dataset consists of 500 cells and 20 , 000 genes , with expression values in the range of 0 to 10 , 000 . The cells are equally divided into numbers of clusters based on randomly generated n centers ( 3≤n≤22 ) . In each cluster , cells are dispersed around the center of the cluster with a given standard deviation ( SD = 0 . 5 , 1 , 2 ) . For each n , we generated 20 random configurations ( i . e . datasets ) . In total , we generated 1 , 200 different random datasets . For evaluating the ability to identify rare cell-types , we followed the same procedure to generate simulated datasets . The number of clusters ranged from 3 to 15 , and the standard derivation of each cluster was 1 . In each dataset , we randomly picked one cluster and removed 90% of the cells from that cluster . This cluster was defined as the rare cell subpopulation . In other words , the size of the rare cluster is about 0 . 6% to 3% of the total population . We also varied the random state of the generator by 20 random numbers to have a total of 260 random datasets . The command line to generate the simulated datasets in python’s Scikit is “make_blobs ( n_samples = 500 , n_features = 20000 , centers = None , cluster_std = 1 . 0 , center_box = ( -10 . 0 , 10 . 0 ) , shuffle = True , random_state = None ) ” . The python code for generating simulated datasets are available at PanoView’s Github repository . We used the following 11 scRNA-seq datasets in our study . Yan et al profiled transcriptomes of human preimplantation embryos and human embryonic at different passages [32] ( GSE36552 ) . Goolam et al profiled transcriptomes of mouse preimplantation development from zygote to late blastocyst [33] ( E-MTAB-3321 ) . Deng et al used scRNA-seq to study the allelic expression of mouse preimplantation embryos of mixed background ( CAST/EiJ × C57BL/6J ) from zygote to late blastocyst [34] ( GSE45719 ) . Pollen et al used low-coverage scRNA-seq to study the development of the cerebral cortex in hiPSCs [35] ( SRP041736 ) . Patel et al reported expression profiles of single glioblastoma cells from 5 individual tumors [6] ( GSE57872 ) . Usoskin et al used single-cell transcriptome analysis to study cell types of mouse neurons [36] ( GSE59739 ) . Villani used scRNA-seq to classify dendritic and monocyte populations from human blood [37] ( GSE94820 ) . Zeisel used scRNA-seq to study the transcriptome of mouse somatosensory cortex S1 and hippocampus CA1 [2] ( GSE60361 ) . Tirosh et al used scRNA-seq to study genotypic and phenotypic states of melanoma tumors from 19 patients [38] ( GSE72056 , GSE77940 ) . Baron et al used inDrop technique to profile the transcriptomes of human and mouse pancreatic cells [5] ( GSE84133 ) . Campbell et al used Drop-seq to study transcriptomes of mouse arcuate nucleus and median eminence [39] ( GSE93374 ) . For parameters in pcaReduce , we used the default setup ( nbt = 1 , q = 30 , method = “s” ) . For key parameters in Seurat , we used model . use = “negbinom” , pcs . compute = 30 , weight . by . var = FALSE , dims . use = 1:10 , do . fast = T , reduction . type = "pca" , dims . use = 1:10 . For key parameters in SCANPY , we used counts_per_cell_after = 1e4 , min_mean = 0 . 0125 , max_mean = 3 , min_disp = 0 . 5 , max_value = 10 , n_neighbors = 10 , n_pcs = 40 . For RCA , we used the default setup . For SC3 , we used the default setup and sc3_estimate_k as the final clustering output . In the Baron dataset , SC3 only reported the clustering result for 5 , 000 random cells due to the activation of SVM . We had to use these reported 5 , 000 cells to calculate the ARI value . For DBSCAN , we first did PCA reduction with Scikit’s default setup and adjusted epsilon and minPts based on the visualization of PCA space . We also used Scikit’s default setup for executing Kmeans ( n_clusters = k , init = 'random' ) and t-SNE ( n_components = 2 , random_state = 1 , init = 'random' , n_iter = 1000 ) . For benchmarking RaceID2 in our simulated datasets , we used the default setup from the manual and did not pass the step of findoutliers . Therefore , we used @cluster$kpart as the final clustering result . For benchmarking GiniClust in our simulated datasets , we used the default parameters from the manual except for Gini . pvalue_cutoff . We adjusted it from 0 . 0001 to 0 . 005 because the default value of 0 . 0001 did not produce useable clustering results . We used recovery rate and false positive rate to evaluate the performance of clustering methods on detecting rare cell types . In each simulated dataset , we always have one rare cell cluster and n ( n = 2 to 14 ) major cell clusters . If the rare cell cluster was perfectly detected with the correct number of cells within the cluster , we considered that the algorithms recovered the rare cell type . On the other hand , if cells from a major cluster were grouped into multiple clusters and at least one of the sub-cluster had the size less than 10% of the major cluster , we considered that the algorithm generated a false positive rare cell type . Timed pregnant mice ( Charles River Laboratories , MA , USA ) were housed in a climate-controlled pathogen-free facility , on a 14 hour-10 hour light/dark cycle ( 07:00 lights on-19:00 lights off ) . All experimental procedures were pre-approved by the Institutional Animal Care and Use Committee of the Johns Hopkins University School of Medicine . Hypothalamic tissue dissected from embryonic day ( E ) 16 . 5 C57BL/6 mouse embryos under a dissecting microscope in cold 1x HBSS ( Thermo Fisher Scientific , MA , USA ) . A total of 6 embryos were dissected . Dissected tissues were incubated in papain solution ( Worthington , NJ , USA ) at 37’C for 15 minutes . Papain activity was stopped as following manufacturer’s protocol , and fire-polished Pasteur pipette was used to gently pipette tissues up and down to dissociate tissues into single cells . Dissociated cells were filtered through 40 uM strainer and washed once in Neurobasal media ( Thermo Fisher Scientific ) , and cells were resuspended in Neurobasal media with 1% bovine serum albumin . Approximately 17 , 000 live cells were loaded per sample in order to capture transcripts from roughly 10 , 000 cells . Estimations of cellular concentration and live cells in suspension was made through Trypan Blue staining and use of the Countess II cell counter ( ThermoFisher ) . Single cell RNA capture and library preparations were performed according to manufacturer’s instructions . using 10x Genomics Chromium Single Cell system ( 10x Genomics , CA , USA ) using the v1 chemistry , following manufacturer’s instructions and sequenced on Illumina MiSeq system ( Illumina , CA , USA ) . Sequencing results were processed through the Cell Ranger pipeline ( 10x Genomics ) with default parameters to generate count matrices for subsequent analysis . The total number of single cells is 959 , and the total number of reads is 15 , 365 , 879 . The mean reads per cell is 16 , 022 , and total genes detected is 15 , 223 . The median number of genes per cell is 617 . PanoView is available as a Python module at https://github . com/mhu10/scPanoView . To run a clustering analysis with default parameters in PanoView , we run two command lines , RunSearching ( GeneLow = ‘default’ , Zscore = ‘default’ ) and OutputResult ( fclust_height = ‘default’ ) . The complete user manual is provided at Github repository . | One of the important tasks in analyzing single-cell transcriptomics data is to classify cell subpopulations . Most computational methods require users to input parameters and sometimes the proper parameters are not intuitive to users . Hence , a robust but easy-to-use method is of great interest . We proposed PanoView algorithm that utilizes an iterative approach to search cell clusters in an evolving three-dimension PCA space . The goal is to identify the cell cluster with the most confidence in each iteration and repeat the clustering algorithm with the remaining cells in a new PCA space . To cluster cells in a given PCA space , we also developed OLMC clustering to deal with clusters with varying densities . We examined the performance of PanoView in comparison to other existing methods using ten published single-cell datasets and simulated datasets as the ground truth . The results showed that PanoView is an easy-to-use and reliable tool and can be applied to diverse types of single-cell RNA-sequencing datasets . | [
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] | 2019 | PanoView: An iterative clustering method for single-cell RNA sequencing data |
The specificity of the antibody response against Zika virus ( ZIKV ) is not well-characterized . This is due , in part , to the antigenic similarity between ZIKV and closely related dengue virus ( DENV ) serotypes . Since these and other similar viruses co-circulate , are spread by the same mosquito species , and can cause similar acute clinical syndromes , it is difficult to disentangle ZIKV-specific antibody responses from responses to closely-related arboviruses in humans . Here we use high-density peptide microarrays to profile anti-ZIKV antibody reactivity in pregnant and non-pregnant macaque monkeys with known exposure histories and compare these results to reactivity following DENV infection . We also compare cross-reactive binding of ZIKV-immune sera to the full proteomes of 28 arboviruses . We independently confirm a purported ZIKV-specific IgG antibody response targeting ZIKV nonstructural protein 2B ( NS2B ) that was recently reported in ZIKV-infected people and we show that antibody reactivity in pregnant animals can be detected as late as 127 days post-infection ( dpi ) . However , we also show that these responses wane over time , sometimes rapidly , and in one case the response was elicited following DENV infection in a previously ZIKV-exposed animal . These results suggest epidemiologic studies assessing seroprevalence of ZIKV immunity using linear epitope-based strategies will remain challenging to interpret due to susceptibility to false positive results . However , the method used here demonstrates the potential for rapid profiling of proteome-wide antibody responses to a myriad of neglected diseases simultaneously and may be especially useful for distinguishing antibody reactivity among closely related pathogens .
Serologic assays designed to detect Zika virus ( ZIKV ) infection suffer from cross-reactivity with antibodies to closely related dengue virus ( DENV ) , due to the high level of amino acid sequence identity ( average ~55% ) and structural similarity [1–4] between the two viruses . Humoral cross-reactivity with other similar arboviruses has been reported as well [1–2] . Serologic assays have been developed to detect past ZIKV infection , reporting sensitivity varying from 37% to 97% and specificity varying from 20% to 90% [5–8] . Most of these assays detect antibodies to the ZIKV envelope protein or nonstructural protein 1 ( NS1 ) [7 , 9–11] and in one case , nonstructural protein 5 ( NS5 ) [12] . A recent publication by Mishra et al . employed a high-density peptide microarray to identify antibodies to linear ZIKV epitopes lacking cross-reactivity with other flaviviruses [13] . This group identified an IgG immunoreactive peptide sequence in the ZIKV nonstructural protein 2B ( NS2B ) which induced little antibody binding in serum from ZIKV-naive people and was bound in early convalescence in most cases of symptomatic ZIKV infection [13] . This group did note seropositivity in a ZIKV-naive , DENV-immune individual and in one individual with no known flavivirus infection history . Because ZIKV , DENV , and other arboviruses are similar in structure and acute clinical syndrome , are spread by the same mosquito vectors [14] , and are co-endemic [15–16] , it is difficult to identify people who have unequivocally been exposed to ZIKV only , adding uncertainty to efforts to profile ZIKV-specific antibody responses in humans . In contrast , macaques raised in indoor colonies can be infected specifically with ZIKV , DENV , or other pathogens . Macaque models of ZIKV infection provide a close approximation of human ZIKV infection in regards to natural history [17–20] , tissue tropism [17–18 , 21–22] , and transmission [18 , 23–26] . Importantly , macaques infected with ZIKV during pregnancy provide insight into the pathogenesis of congenital ZIKV infection [18–19 , 22–23 , 27–30] . Since the strain , dose , and timing of macaque model ZIKV infection is exactly known , the kinetics and specificity of humoral immune responses can be profiled in macaques with better resolution than is possible in cross-sectional human studies . The peptide microarray technology we use in this study allows for one serum sample to be assayed against six million unique 16-residue peptides , or for 12 samples to each be assayed against 392 , 000 peptides , on a single chip ( Roche Sequencing Solutions , Madison , WI ) . The technology has been used in proteome-wide epitope mapping [31] , profiling of antibody responses in autoimmune disease [32] , profiling venom toxin epitopes [33] , determining functions of cellular enzymes [34] , de novo binding sequence discovery [35] , epitope validation following phage display screening [36] , and screening for tick-borne disease seroprevalence [37] . We previously used this tool to examine antibody responses in simian pegivirus ( SPgV ) and simian immunodeficiency virus ( SIV ) infections [38] . As mentioned above , a recent publication explored use of this technology in profiling human antibody responses against flaviviruses [13] . This linear peptide microarray technology has advantages over previous assays through its capacity to screen for reactivity to a large number of pathogens while simultaneously mapping reactive epitopes precisely , and it has the distinct advantage of allowing detection of unexpected epitopes due to its capacity to assay the entirety of a virus’s proteome . Here , we used high-density peptide microarrays to map macaque IgG epitopes in full-length ZIKV and DENV polyproteins and to compare cross-reactivity to 27 other arboviruses . Our study takes advantage of this technology’s capacity to assess binding to linear epitopes throughout a virus’ entire proteome to identify an epitope in ZIKV NS2B , a protein made intracellularly which embeds in the host cell’s endoplasmic reticulum and thus would not be expected to induce strong antibody responses . We also demonstrate the potential of this technology , through its ability to survey binding throughout many whole viral proteomes simultaneously , to differentiate seroreactivity to an infecting virus from cross-reactivity against a great variety of other similar viruses . These unique aspects of this recently developed peptide microarray technology highlight its capacity to efficiently screen for and identify previously unknown epitopes in a large number of neglected disease-causing pathogens simultaneously and to distinguish infection histories of NTDs , potentially impacting the development of future diagnostics and vaccines .
Animal demographics , inoculation strain , dose , and route , serum sample collection timelines , and array design used for each animal are described in Table 1 . Gestational details and outcomes for pregnant animals are described in Table 2 . Additional details on the study histories of the animals in this study can be found at https://go . wisc . edu/b726s1 . All but one of the animals used in this study were born at the WNPRC indoor colonies . Animal H2 was born at the Caribbean Primate Research Center and tested negative for flavivirus exposure ( specifically , for ZIKV and DENV exposure ) using PRNTs prior to being admitted to the WNPRC colony . All monkeys were cared for by the staff at the Wisconsin National Primate Research Center ( WNPRC ) in accordance with the regulations and guidelines outlined in the Animal Welfare Act and the Guide for the Care and Use of Laboratory Animals and the recommendations of the Weatherall report ( https://royalsociety . org/topics-policy/publications/2006/weatherall-report/ ) . Per WNPRC standard operating procedures for animals assigned to protocols involving the experimental inoculation of an infectious pathogen , environmental enhancement included constant visual , auditory , and olfactory contact with conspecifics , the provision of feeding devices which inspire foraging behavior , the provision and rotation of novel manipulanda ( e . g . , Kong toys , nylabones , etc . ) , and enclosure furniture ( i . e . , perches , shelves ) . Per Animal Welfare Regulations ( Title 9 , Chapter 1 , Subchapter A , Parts 1–4 , Section 3 . 80 Primary enclosures ) the animals were housed in a nonhuman primate Group 3 enclosure with at least 4 . 3 square feet of floor space and at least 30 inches of height . This study was approved by the University of Wisconsin-Madison Graduate School Institutional Animal Care and Use Committee ( animal protocol numbers G005401 and G005443 ) . SIVmac239 ( GenBank accession: M33262 ) stock was prepared by the WNPRC Virology Services Unit . Vero cells were transfected with the SIVmac239 plasmid . Infectious supernatant was then transferred onto rhesus PBMC . The stock was not passaged before collecting and freezing . ZIKV strain H/PF/2013 ( GenBank accession: KJ776791 ) was obtained from Xavier de Lamballerie ( European Virus Archive , Marseille , France ) and passage history is described in Dudley et al . [17] . ZIKV strain MR766 , ZIKV strain PRVABC59 , and DENV-2 strain New Guinea C were generously provided by Brandy Russell ( CDC , Ft . Collins , CO ) . ZIKV strain MR766 passage history has been described in Aliota et al . [39] . A molecularly-barcoded version of ZIKV strain PRVABC59 ( Zika virus/H . sapiens-tc/PUR/2015/PRVABC59; GenBank accession: KU501215 ) was constructed as described in Aliota et al . [40] . DENV-2 strain New Guinea C ( GenBank accession: FJ390389 ) , originally isolated from a human in New Guinea , underwent 17 rounds of amplification on cells and/or suckling mice followed by a single round of amplification on C6/36 cells; virus stocks were prepared by inoculation onto a confluent monolayer of C6/36 mosquito cells . DENV-3 strain Sleman/78 was obtained from the NIH; virus stocks were prepared by a single passage on C6/36 cells . Full-length ZIKV and DENV polyprotein sequences were extracted from the National Center for Biotechnology Information ( NCBI ) database into Geneious Pro 9 . 1 . 8 ( Biomatters , Ltd . , Auckland , New Zealand ) . These sequences included the ZIKV and DENV polyprotein sequences described above ( see “Virus stocks” ) , as well as DENV-1 strain VR-1254 ( GenBank accession: EU848545 ) and DENV-4 strain VID-V2055 ( GenBank accession: KF955510 ) . These amino acid sequences were aligned using the Geneious alignment algorithm as implemented in Geneious Pro 9 . 1 . 8 using default parameters ( global alignment with free end gaps , cost matrix: Blosum62 ) . Viral protein sequences were selected and submitted to Roche Sequencing Solutions ( Madison , WI ) for development into a peptide microarray as part of an early access program . Sequences included three ZIKV polyproteins ( an Asian strain , ZIKV-FP , GenBank accession: KJ776791 . 2; an African strain , ZIKV-MR766 , GenBank accession: KU720415 . 1; and an American strain , ZIKV-PR , GenBank accession: KU501215 . 1 ) , four DENV polyproteins ( DENV-1 , GenBank accession: EU848545 . 1; DENV-2 , GenBank accession: KM204118 . 1; DENV-3 , GenBank accession: M93130 . 1; and DENV-4 , GenBank accession: KF955510 . 1 ) , and one SIVmac239 env protein ( GenBank accession: AAA47637 . 1 ) , which were used for most analyses in this study . Sequences used for cumulative distribution function ( CDF ) plots ( see Fig 3 ) and analysis include sequences for mosquito-borne viruses found in Africa and known to infect humans [41] , as well as one Japanese encephalitis virus strain ( GenBank accession: KX945367 . 1 ) . Accession numbers used to represent each viral protein are listed in the supplemental material ( S1 Table ) . Proteins were tiled as non-redundant 16 amino acid peptides , overlapping by 12 or 15 amino acids . The array designs are publicly available at https://go . wisc . edu/b726s1 . The peptide sequences were synthesized in situ with a Roche Sequencing Solutions Maskless Array Synthesizer ( MAS ) by light-directed solid-phase peptide synthesis using an amino-functionalized support ( Geiner Bio-One ) coupled with a 6-aminohexanoic acid linker and amino acid derivatives carrying a photosensitive 2- ( 2-nitrophenyl ) propyloxycarbonyl ( NPPOC ) protection group ( Orgentis Chemicals ) . Unique peptides were synthesized in random positions on the array to minimize impact of positional bias . Each array is comprised of twelve subarrays , where each subarray can process one sample and each subarray contains up to 392 , 318 unique peptide sequences . Macaque serum samples were diluted 1:100 in binding buffer ( 0 . 01M Tris-Cl , pH 7 . 4 , 1% alkali-soluble casein , 0 . 05% Tween-20 ) . Diluted sample aliquots and binding buffer-only negative controls were bound to arrays overnight for 16–20 h at 4°C . After binding , the arrays were washed 3x in wash buffer ( 1x TBS , 0 . 05% Tween-20 ) , 10 min per wash . Primary sample binding was detected via 8F1-biotin mouse anti-primate IgG ( NIH Nonhuman Primate Reagent Resource ) secondary antibody . The secondary antibody was diluted 1:10 , 000 ( final concentration 0 . 1 ng/µl ) in secondary binding buffer ( 1x TBS , 1% alkali-soluble casein , 0 . 05% Tween-20 ) and incubated with arrays for 3 h at room temperature , then washed 3x in wash buffer ( 10 min per wash ) and 30 sec in reagent-grade water . The secondary antibody was labeled with Cy5-Streptavidin ( GE Healthcare; 5 ng/µl in 0 . 5x TBS , 1% alkali-soluble casein , 0 . 05% Tween-20 ) for 1 h at room temperature , then the array was washed 2x for 1 min in 1x TBS , and washed once for 30 sec in reagent-grade water . Fluorescent signal of the secondary antibody was detected by scanning at 635 nm at 2 µm resolution and 25% gain , using an MS200 microarray scanner ( Roche NimbleGen ) . The datafiles and analysis code for figures are available from https://go . wisc . edu/b726s1 . A processed dataset is also available at this link to allow for greater ease in searching for specific sequences . All figures in this analysis use the log base 2 of the raw fluorescence signal intensity values ( measured using arbitrary units , A . U . ) . For each sample , each unique peptide was assayed and processed once; then results from peptides redundant to multiple proteomes ( i . e . were present in more than one strain represented ) were restored to each protein . Raw fluorescence intensity signal results from primary antibodies binding to peptides on the array , which have been labeled with a secondary antibody with a fluorescent tag . The amount of fluorescence signal is influenced by both the titer and affinity of primary antibodies binding to each peptide sequence . For cumulative distribution function ( CDF ) plots , fluorescence signal intensities were log base 2 transformed and background reactivity in the blank ( binding buffer only ) control sample was subtracted for each peptide . The fold change from 0 dpi was calculated by subtracting reactivity at 0 dpi from reactivity at 28 dpi . To reduce instrument-related variance , the data was then filtered by taking the minimum intensity of two consecutive peptides with 1 amino acid offset , thereby reducing peptide outliers by ensuring measured reactivity occurs in multiple consecutive peptides . To confirm the validity of our findings from this recently-developed peptide microarray platform , we assessed its performance against the humoral response produced by infection with simian immunodeficiency virus ( SIV ) , which has been well-characterized by conventional methods such as enzyme-linked immunosorbent assays ( ELISAs ) , enzyme-linked immunosorbent spot assays ( ELISPOTs ) , epitope-prediction methods , or other protein arrays . We synthesized linear 16-mer peptides , overlapping by 12 amino acids , representing the SIVmac239 envelope protein ( env ) and analyzed serum from two Mauritian cynomolgus macaques for SIV-specific IgG reactivity before and approximately 125 days after SIVmac239 infection ( Table 1 ) . ( We have previously plotted data procured from peptide array assays of these samples [38] while investigating the antibody response to SIV in the context of simian pegivirus infection; here we show the same data using the updated , improved data processing pipeline described above . ) Post-infection samples showed fluorescence intensity as high as 1 , 000 times the intensity in pre-infection samples ( S1 Fig ) . Regions of higher-fold increases in fluorescence intensity corresponded to previously defined variable domains of env which are known antibody targets , the variable loop regions , as well as others corresponding to known epitopes [42 , 43] . Taken together , these results validate epitope definition on the peptide microarray platform and show this platform to be capable of high-resolution virus-specific IgG epitope identification using the analytic methods utilized here . Statistical analyses were performed using R ( R Core Team 2018 ) . Statistical significance of the change in signal intensity versus no change from pre-infection levels for each peptide was calculated using a two-tailed log-ratio t-test . For CDF plot analyses , statistical significance of the differences between virus species was determined using pooled t-tests .
We sought to determine antibody binding , or reactivity , to the ZIKV polyprotein following ZIKV infection . We tiled 16-residue ( 16-mer ) peptides overlapping by 15 amino acids representing different ZIKV polyproteins and evaluated the antibody binding of serum samples from animals with recent ZIKV-FP ( animals B1 , D1 , and D2 ) or ZIKV-MR766 ( animal C1 ) infections ( Table 1 ) . Animals in both groups had demonstrated neutralizing antibody responses at 28 dpi , measured by 90% plaque reduction neutralization tests ( PRNT90 ) as described previously [17 , 24 , 39] . Peptides were defined as reactive if the signal intensity was greater by any amount after infection with a cognate strain ( e . g . , increased signal intensity against ZIKV peptides in an animal infected with ZIKV ) than it was before infection . Peptides were defined as cross-reactive if the signal intensity was greater by any amount after infection with a noncognate strain ( e . g . , increased signal intensity against ZIKV peptides in an animal infected with DENV ) . True epitopes were expected to induce reactivity greater than pre-infection reactivity by a statistically significant amount , and this statistical significance was expected to be seen in multiple overlapping peptides , since an antibody would be expected to bind multiple peptides with overlapping sequences . Statistical significance of the change in signal intensity versus no change was calculated using a two-tailed log-ratio t-test , and regions were only considered epitopes when there was a statistically significant increase in intensity in a post-infection sample relative to intensity in a pre-infection sample in three or more consecutive peptides . Reactivity was most commonly observed in three regions of the flavivirus polyprotein: envelope protein , NS2B , and nonstructural protein 3 ( NS3 ) . Therefore , most of the analysis in this paper is limited to these regions . Some antibody binding was seen in other regions of the polyprotein ( for example , NS1 , NS5 ) , but this binding was scattered and inconsistent between animals ( reactivity of all animals throughout the entire ZIKV polyprotein can be found in the supplemental material ) . Antibody binding to peptides from the envelope protein was seen in all four animals at 28 dpi; antibody binding in the NS3 region was seen in three out of four animals ( Fig 1; reactivity throughout the entire ZIKV polyprotein can be seen in S2 Fig ) . The four animals exhibited similar responses against an Asian ZIKV strain , ZIKV-FP ( Fig 1 ) , as against an African strain and an American strain ( ZIKV-MR766 and ZIKV-PR respectively , S3 Fig ) . All four animals exhibited antibody binding to the ZIKV NS2B epitope similar to that documented in humans [13] . Though other reactive epitopes were identified in other proteins in multiple animals , this epitope was the only epitope in our study for which all ZIKV-infected animals showed reactivity . All ten ZIKV-infected animals in this study were used to determine statistical significance of this epitope in order to avoid making statistical inferences using very small sample sizes [44] . Area under the curve ( AUC ) values and corresponding receiver operating characteristic ( ROC ) curves were calculated ( S4 Fig ) to identify ten peptides at positions 1427–1436 in the polyprotein ( for a total of 25 amino acids , sequence RAGDITWEKDAEVTGNSPRLDVALD ) as the best-performing epitope for which a statistically significant change from 0 dpi was observed , hereafter referred to as NS2B1427-1451RD25 ( AUC of 0 . 9375 , 95% confidence interval of 0 . 89065 to 0 . 9375 ) . Using the mean signal intensity across the ten peptides , the change of signal intensity from 0 dpi to 21–28 dpi was statistically significant versus no change by a two-tailed log-ratio t-test ( p-value = 0 . 000501 < 0 . 05 , df = 9 ) . This epitope is slightly longer than that found by Mishra et al . ( nine 12-mer peptides , for a total of 20 amino acids , sequence DITWEKDAEVTGNSPRLDVA ) [13] . DENV polyproteins share an average of 55% sequence identity with ZIKV polyproteins [1 , 2] , and the region of DENV NS2B corresponding to the immunoreactive ZIKV NS2B1427-1451RD25 epitope shares an average of 41% identity ( Fig 2A ) . To examine cross-reactivity , we analyzed the antibody binding of samples from the ZIKV-convalescent animals against DENV polyproteins represented on the array ( Fig 2B–2E ) . Cross-reactivity was apparent , with antibodies from the ZIKV-convalescent/DENV-naive animals recognizing regions of DENV polyproteins . All four animals showed some cross-reactivity against the DENV envelope protein and DENV NS3 . Animals exhibited comparable cross-reactivities to all four DENV serotypes , with the highest single instance of cross-reactivity observed against a DENV-3 epitope in the NS3 region . No significant cross-reactivity against the DENV NS2B protein was observed for these or any ZIKV-infected animals in this study ( p-value = 0 . 548 , df = 9 ) . Given this array’s capacity to screen for antibody binding to peptides representing many different virus proteomes at once , we also assessed cross-reactivity against the 27 other arboviruses ( for a total of 28 arboviruses ) represented . We plotted the fold change in reactivity from 0 to 28 dpi for each peptide in each virus’s proteome using cumulative distribution function ( CDF ) plots ( Fig 3 ) . CDF plots were used to determine whether the sum of reactivity across a viral proteome could distinguish reactivity to the infecting pathogen ( in this case , ZIKV ) from cross-reactivity to a variety of other similar or dissimilar pathogens ( in this case , 27 other arboviruses ) . Cross-reactivity in peptides in other arboviruses was observed , but it was rare compared with the reactivity seen in the ZIKV peptides . The greatest degree of cross-reactivity occurred among flaviviruses , in particular Ntaya virus , Spondweni virus , Bagaza virus , and DENV-3 ( Fig 3C ) . Pooled t-tests showed significant differences between reactivity against ZIKV strains and other viruses for each of the four animals ( Table 3 ) . In animal B1 , reactivity against ZIKV was significantly different from cross-reactivity against all other arboviruses ( p-values ranging from <0 . 0001 to 0 . 0006 ) . Animal C1’s reactivity against ZIKV was significantly different ( p-values <0 . 05 ) for all viruses assayed except Babanki virus , Banzi virus , DENV-4 , Uganda S virus , and yellow fever virus . D1 showed reactivity against ZIKV that was significantly different from reactivity against all other viruses except Spondweni virus . D2 showed more significant cross-reactivity with other arboviruses; in D2 , ZIKV reactivity differed significantly from reactivity to all other viruses except Bwamba virus , Chikungunya virus , DENV-1 , Middelburg virus , Ndumu virus , Rift Valley fever virus , Spondweni virus , and Uganda S virus . Of note , D2 did also exhibit the smallest increase in fold change from 0 to 28 dpi in reactivity against ZIKV; this higher likelihood of cross-reactivity may be attributable to the minimal overall amount of reactivity present . Reactivity for the two ZIKV strains compared , one African strain ( ZIKV-MR766 , GenBank accession: NC_012532 . 1 ) and one Asian/American strain ( GenBank accession: NC_035889 . 1 ) was not significantly different for any animal ( p-values ranging from 0 . 62 to 0 . 88 ) . Given the importance of determining an accurate ZIKV infection history in pregnancy , we sought to characterize the gestational anti-ZIKV antibody response . We used the peptide microarray to evaluate serum samples from six pregnant animals . Animals were inoculated with ZIKV at 35–47 days post-conception ( gestational date , gd ) ( Table 2 ) . Two animals ( G1 and G2 ) had no history of flavivirus exposure and were inoculated with ZIKV-FP at 36–38 gd . Three more flavivirus-naive animals ( H1 , H2 , and H3 ) were infected with ZIKV-PR at 45–47 gd . One animal ( I1 ) had a history of exposure to DENV-3 nine months prior to inoculation with a barcoded clone of ZIKV-PR at 35 gd [40] . Serum samples collected approximately one week post-infection and at two to six week intervals thereafter were analyzed against ZIKV polyproteins represented on the peptide array ( Fig 4 ) . All six pregnant animals exhibited anti-NS2B1427-1451RD25 reactivity by the early convalescent phase ( 21–29 dpi ) , though time of initial appearance and duration of the response varied between animals . All pregnant animals showed a similar pattern of anti-ZIKV reactivity , with some differences in time to peak reactivity and duration of detectable reactivity . In G1 , elevated baseline intensity in the ZIKV NS2B1427-1451RD25 region was present prior to inoculation with ZIKV-FP . Reactivity peaked in the acute phase ( 7 dpi ) and subsequently decreased but remained above pre-infection levels through 127 dpi , after G1 had given birth . In G2 , reactivity was not appreciable until the early convalescent phase ( 21 dpi ) and peaked at 35 dpi , remaining elevated relative to pre-infection levels through the latest time point analyzed ( 113 dpi ) . Animals H1 and H3 showed elevated pre-infection intensity against NS2B1427-1451RD25 . All three animals in cohort H showed reactivity by 21 dpi . H1 and H2 continued to exhibit increased reactivity through the latest time point measured ( 70 dpi ) , while H3 had peak reactivity at 21 dpi and decreased after . I1 , an animal nine months post-DENV-3 infection , showed a pattern of reactivity similar to that in other animals , with anti-NS2B1427-1451RD25 IgG reactivity first appearing at 8 dpi and peaking at 29 dpi at a level 3 . 6 times pre-infection reactivity ( Fig 4 ) . Reactivity remained close to peak reactivity through 78 dpi . All pregnant animals’ cross-reactivity against DENV polyproteins mirrored that seen in non-pregnant animals ( S6 Fig ) . Binding of antibodies throughout the entire ZIKV-FP polyprotein can be found in the supplemental material ( S7 Fig ) . Previous assays have struggled to distinguish DENV serologic responses from ZIKV serologic responses [5–8] . We investigated whether the peptide microarray technology , and specifically reactivity patterns using the ZIKV NS2B1427-1451RD25 epitope , could distinguish DENV from ZIKV infections . Three animals ( cohort F ) had been challenged twice with ZIKV-FP 12 months prior and 9 . 5 months prior [17]; we collected serum from these animals , infected them with DENV-2 , and collected serum 28 days after . These samples were analyzed against 16-mer peptides , with amino acid overlap of 12 , representing DENV-2 and ZIKV-FP ( Fig 5 ) . Binding of antibodies throughout the entire DENV-2 and ZIKV-FP polyproteins can be found in the supplemental material ( S8 Fig ) . These animals showed reactivity against all four DENV polyproteins in regions representing the DENV envelope protein , DENV NS3 , and others ( Fig 5A ) and cross-reactivity against corresponding regions of the ZIKV polyprotein ( Fig 5B ) . One animal ( F3 ) out of the three showed significant reactivity to the NS2B1427-1451RD25 epitope , though this reactivity was slightly outside the area of typical NS2B1427-1451RD25 reactivity ( peptides 1421–1444 rather than 1427–1451 ) . Another ( F1 ) showed elevated pre-DENV infection intensity in NS2B1427-1451RD25 that did not change following DENV infection , possibly as a result of the animal’s prior ZIKV exposure . Animal F2 showed no detectable NS2B1427-1451RD25 reactivity before or after exposure .
We describe the antibody binding of the anti-ZIKV IgG response in non-pregnant and pregnant rhesus macaques and compare this to the anti-DENV response . Using a recently developed high-density peptide microarray we show that macaques infected with ZIKV produce IgG antibodies which bind throughout the ZIKV polyprotein , including conserved antibody binding to an epitope in ZIKV NS2B , NS2B1427-1451RD25 , which is apparent regardless of the ZIKV strain used for infection . We establish that cross-reactivity exists between anti-ZIKV and anti-DENV antibodies for the ZIKV and DENV polyproteins , and we show this technology can be used to differentiate anti-ZIKV reactivity from cross-reactivity to many other arboviruses . Additionally , we show the anti-NS2B1427-1451RD25 IgG response is susceptible to false positives in the context of DENV infection and may be susceptible to false-positives in flavivirus-immune individuals . Thus , while this epitope may be broadly useful for serosurveillance , it should be used with caution in the diagnosis of individual infections . As has been seen in previous assays [2 , 10 , 12–13 , 45–48] , we observed antibody cross-reactivity between ZIKV- and DENV-immune sera , though reactivity to the ZIKV NS2B1427-1451RD25 epitope was observed in all cases of recent ZIKV infection ( 10 out of 10 ZIKV-infected animals ) , and in only one out of three cases of recent DENV infection in animals with history of ZIKV exposure . Reactivity to the NS2B epitope was conserved whether the infecting strain was African , Asian , or American in origin . All ZIKV-infected animals produced anti-ZIKV IgG against the NS2B1427-1451RD25 epitope , though reactivity was sometimes small in magnitude ( as in animal D2 ) or was measurable for only a short duration ( as in animal H3 ) . The lack of uniformity of the anti-ZIKV IgG response is especially relevant since all ZIKV-exposed animals could be followed , in contrast to studies in humans where there may be a selection bias for individuals with symptomatic ZIKV , which is thought to account for only approximately half of ZIKV infections [13 , 49] . Though anti-NS2B1427-1451RD25 reactivity was consistently detectable in early convalescence , it decayed in all but one case , that of a pregnant animal with previous DENV exposure , during the time period assessed . These findings corroborate findings in humans , in which symptomatic ZIKV infection was strongly associated with detectable anti-NS2B antibodies in the early convalescent phase ( 96% ) , but was less likely six months post-infection ( 44% ) [13] . These results demonstrate the need for further investigation into the longevity and kinetics of the anti-ZIKV humoral response . Given that no other purported ZIKV-specific epitopes have been identified to date , these results also call into question how useful current serological methods may be in differentiating past ZIKV exposure from exposure to other flaviviruses . Additionally , one animal ( F3 ) with a history of previous ZIKV infections showed reactivity against the ZIKV NS2B1427-1451RD25 epitope following experimental DENV infection , indicating that a history of ZIKV infection or a recent DENV infection has potential to confound results using this epitope . Thus , while this epitope appears to be more ZIKV-specific than most , its utility in guiding development of diagnostics will likely be limited . The ability of the peptide array to differentiate seroreactivity against ZIKV from cross-reactivity to other viruses and to show cross-reactivity to 27 other mosquito-borne arboviruses suggests this technology , with additional optimization , could be useful for determining the etiology of fever of unknown origin and other non-specific symptoms in areas where mosquito-borne diseases are common . All ZIKV-infected animals showed the greatest fold change from 0 dpi ( equal to the log2 differences from 0 dpi ) in reactivity against ZIKV proteomes . Though these differences in fold change did not always reach significance for all strains in all animals , the tendency to show the greatest reactivity in ZIKV strains , even in comparisons against very closely-related flaviviruses , for ZIKV-infected animals demonstrates the potential of this technology in guiding diagnostic development in the future . This assay detected anti-NS2B1427-1451RD25 reactivity in all pregnant macaques exposed to ZIKV . Production of IgG antibodies has relevance to both mother and fetus , since maternal IgG crosses the placenta and transport of IgG across the placental barrier increases throughout the course of pregnancy [50] . It can be presumed the anti-ZIKV IgG produced by these animals also reached their fetuses , but whether these anti- NS2B1427-1451RD25 antibodies provide protection , contribute to the pathogenesis of ZIKV disease and ZIKV congenital effects , or are irrelevant in ZIKV pathology is currently unknown . Though we did not note any variation in outcomes with differences in antibody responses , it is possible deviations in antibody responses during pregnancy could help explain differences in outcomes following gestational ZIKV infection . Several pregnant animals also showed elevated pre-infection intensity at the NS2B1427-1451RD25 epitope . This phenomenon may be due to innate immunodominance of the NS2B1427-1451RD25 epitope , or it may be due to molecular mimicry , though we have not found this epitope present in any other pathogen . These findings merit further and more thorough investigation than this current study can provide . The peptide array technology used in this study has several limitations . The assay’s utility could be increased by the addition of quantitative capacities . We currently use a 1:100 antibody dilution since we have found this to produce an optimal signal:noise ratio , but it is possible serial dilutions could allow for measurement of quantitative results . Greater confidence in this assay’s results could be derived from assessing its ability to identify the binding of well-characterized monoclonal antibodies . Once validated in this way , the array could then be used to determine the specificity of new monoclonal antibodies as they are discovered . Additionally , our study defined a positive response as an increase from an animal’s pre-infection intensity; human patients usually cannot give pre-infection samples and must rely upon controls determined from humans having no known history of exposure to certain pathogens . The development of such a control would raise the specificity of the assay at the expense of sensitivity , and thus would risk missing some true positive results when definitive pre-infection samples from the same individual are not available . The peptide array approach is also limited due to its reliance on continuous linear epitopes . Many previously documented ZIKV epitopes are discontinuous conformational epitopes [51–57] . It is also possible that this array may miss some immunodominant responses or other clinically important immune responses . For example , antibody binding to the NS1 protein has been observed and is frequently described in other studies [7 , 9–11] , but binding to NS1 was scattered and inconsistent using the peptide microarrays . Other epitope discovery methods will likely remain superior in defining discontinuous conformational epitopes and immunodominant responses , but this technology is useful in identifying immunoreactive regions not previously considered as potential epitopes . Given that conformational epitopes are often cross-reactive between flaviviruses [52 , 58] this assay’s ability to detect only linear epitopes may make it more beneficial in diagnostic development . Past work from our laboratory , including results from some of the animals whose sera was analyzed here , has shown anti-ZIKV neutralizing antibody titers measured by PRNT90 do not drop off but remain elevated as late as 64 dpi [17] . The discordance between levels of anti-NS2B1427-1451RD25 IgG and neutralizing antibody titers may indicate the anti-NS2B1427-1451RD25 antibodies do not play a role in protection against future infections , which may explain the drop-off observed in macaques and in humans . In the future , this technology could be expanded for use in profiling antibody responses to many other pathogens . This tool was able to detect known and previously unknown epitopes throughout the ZIKV proteome , including epitopes in unexpected regions such as NS2B . This approach could be applied to other NTDs to advance diagnostic and vaccine development . The array used in this study simultaneously evaluates antibody responses against the entire proteomes of every mosquito-borne virus known to infect humans in Africa . Building off what we have learned through this and other peptide array analyses , we intend to use this array to survey antibody reactivity in African populations , through which we may identify previously unknown epitopes for some of the rare pathogens represented on the array . Additionally , we plan to use this assay to evaluate and compare both IgM and IgG responses in these analyses , which may help elucidate the kinetics of the immediate and long-term antibody response to pathogens . In summary , this work in macaques demonstrates the capacity of a recently developed peptide microarray to profile the binding of distinct anti-ZIKV and anti-DENV IgG antibody responses in experimental infections . Our work shows the anti-NS2B1427-1451RD25 IgG response is characterized by relatively rapid decay and is susceptible to confounding , mirroring results seen in humans . The peptide microarray technology used shows particular promise in evaluating full-proteome antibody binding for a large number of pathogens efficiently and may be especially useful for neglected tropical diseases for which diagnostics are rudimentary or non-existent . | ZIKV has emerged as a vector-borne pathogen capable of causing serious illness in infected adults and congenital birth defects . The vulnerability of communities to future ZIKV outbreaks will depend , in part , on the prevalence and longevity of protective immunity , thought to be mediated principally by antibodies . We currently lack diagnostic assays able to differentiate ZIKV-specific antibodies from antibodies produced following infection with closely related DENV , and we do not know how long anti-ZIKV responses are detectable . Here we profile antibodies recognizing linear epitopes throughout the entire ZIKV polyprotein , and we profile cross-reactivity with the proteomes of other co-endemic arboviruses . We show that while ZIKV-specific antibody binding can be detected , these responses are generally weak and ephemeral , and false positives may arise through DENV infection . This may complicate efforts to discern ZIKV infection and to determine ZIKV seroprevalence using linear epitope-based assays . The method used in this study , however , has promise as a tool for profiling antibody responses for a broad array of neglected tropical diseases and other pathogens and in distinguishing serology of closely-related viruses . | [
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] | 2018 | Antibody responses to Zika virus proteins in pregnant and non-pregnant macaques |
We developed a highly sensitive assay to detect transcription errors in vivo . The assay is based on suppression of a missense mutation in the active site tyrosine in the Cre recombinase . Because Cre acts as tetramer , background from translation errors are negligible . Functional Cre resulting from rare transcription errors that restore the tyrosine codon can be detected by Cre-dependent rearrangement of reporter genes . Hence , transient transcription errors are captured as stable genetic changes . We used this Cre-based reporter to screen for mutations of Saccharomyces cerevisiae RPB1 ( RPO21 ) that increase the level of misincorporation during transcription . The mutations are in three domains of Rpb1 , the trigger loop , the bridge helix , and in sites involved in binding to TFIIS . Biochemical characterization demonstrates that these variants have elevated misincorporation , and/or ability to extend mispaired bases , or defects in TFIIS mediated editing .
Accurate transcription is an essential step in accessing the genetic information stored in genes . In eukaryotes , transcription of DNA into mRNA is carried out by RNA polymerase II ( Pol II ) , an enzyme comprised of 12 subunits . While there has been extensive research on core Pol II , including biochemical and detailed structural information [1]–[7] , less is known about how the accuracy of transcription is controlled . The net misincorporation rate is estimated to be about one per 105 bases [8] , [9] . This reflects initial misincorporation by Pol II and subsequent editing mechanisms , some intrinsic to the core polymerase and others facilitated by transcription factors . Direct screens for mutations that reduce the fidelity of transcription have been difficult due to the transient nature of the errors and the relatively high rate of translation errors , particularly at nonsense codons , that can mask transcription errors [8] , [10]–[12] . Here we report a novel approach to identifying mutations that increase transcription errors in vivo . Rpb1 and Rpb2 are the two largest Pol II subunits with several structural and functional domains that are implicated in transcription fidelity maintenance . Rpb1 contains the active site for nucleotide addition , and , together with Rpb2 , forms a substrate-binding site and a deep channel accommodating template DNA and a 9–10 bp RNA-DNA hybrid [13] . Mutations in the RNA-DNA hybrid binding cleft or near the substrate binding site cause increased occurrence of insertions and deletions during transcription through homopolymeric tracts [14]–[16] . A mutation that appeared to reduce the accuracy of transcription was identified in rpoB , the gene coding for second largest subunit of RNA polymerase in Escherichia . coli , among rifampicin resistant mutants [8] , [17] . The molecular mechanism of fidelity maintenance disrupted by this mutation remains to be established . However , several mechanisms by which Rpb1 regulates fidelity have been elucidated . Important structural elements surrounding the Pol II active site include the Rpb1 bridge helix , separating the active site from the downstream DNA binding channel , and the trigger loop , a mobile element of Rpb1 , which undergoes dramatic conformational changes during each NTP addition [7] , [18] . The trigger loop opens allowing for Pol II translocation and NTP entry to the active site , and closes , interacting with the substrate NTP and promoting catalysis . Mutations in the trigger loop that increase incorporation of non-complementary substrates and dNTPs and thus decrease Pol II fidelity in vitro have been identified from secondary screens of Pol II mutants [3] , [19] , [20] . Rpb1 interacts with non-essential Pol II subunit Rpb9 , which is implicated in transcription fidelity maintenance [11] , [21]–[24] . It is likely that Rpb9 prevents misincorporation indirectly , by attenuating the trigger loop closing [23] . Rpb9 also has been shown to prevent extension of the misincorporated base [24] . Transcription elongation factor TFIIS interacts with Pol II Rpb1 and is implicated in fidelity control at post-incorporation stage [12] , [25] , [26] . Indeed , it has been demonstrated that in vitro TFIIS preferentially promotes cleavage of the mismatched 3′end of nascent RNA [27] . The interpretation of phenotypic changes associated with alterations in RNA polymerase is complicated by a mix of direct and indirect changes . RNA polymerase mutations can change the transcriptome by altering the initiation differentially at promoters , by changing elongation rates , which in turn can alter splicing efficiency , and by altering termination [28] , [29] . To focus on the identification of transcription fidelity mutants , we combined a primary genetic screen for transcription errors with a biochemical assays to identify the nature of the transcription fidelity defect . In summary , mutations in Rpb1 trigger loop rendering Pol II error-prone , as well as mutations in TFIIS binding site and deletions of RPB9 and DST1 ( the gene encoding TFIIS ) are demonstrated to reduce the fidelity of transcription in vivo .
Assays of transcription fidelity based on nonsense or missense suppression are problematic in part due to the high background caused by translational errors [10]–[12] , [30] . In the approach reported here , we rely on a requirement for an active tetramer to reduce the contribution of translation errors on the background . In addition , previous approaches have required a continual production of transcription errors to produce the monitored phenotype . In our approach , transient transcription errors can result in a stable genetic change . The system involves three parts , 1 ) a missense mutation in the active site tyrosine of Cre recombinase , 2 ) a Cre-dependent recombination reporter substrate with a very low Cre-independent rate of recombination and 3 ) promoters that give low level expression of the mutant cre allele . These three aspects of the system are discussed separately below . Cre functions as a homotetramer , recognizing two 34 bp DNA sequences termed loxP and promoting recombination of their flanking DNAs [31] , [32] . Depending on the orientation of the two loxP sites , the flanking DNA is either inverted ( intrachromosomal antiparallel ) , excised ( intrachromosomal direct ) , or exchanged ( interchromosomal ) [33] . The active site tyrosine ( Y324 ) of Cre recombinase is essential for its activity [34] . All four subunits of the tetramer become covalently attached to strands of the DNA via those tyrosine 324 side chains during the recombination reaction . Chimeric enzymes assembled from mutant and WT subunits are catalytically inactive [35]–[39] . Translation errors that produce a WT monomer will not result in active Cre , whereas a transcription error that restores the WT codon can be translated into multiple WT subunits and assembled into an active Cre tetramer . The experiments presented here focus on the Y324C allele . This TAT → TGT mutation requires Pol II to misincorporate an adenosine opposite a cytosine in the template strand in order to suppress the cre-Y324C defect ( Figure 1A ) . This G → A transcription error is among the most common mistakes made by E . coli RNAP in vitro and in vivo [40] and by S . cerevisiae [19] . We created a reporter for Cre activity based on HIS3 into which we placed an artificial intron [41] carrying a loxP site , HIS3-AI2lox ( Figure 1B , construct ( ii ) ) . A Cre activatable derivative , his3-AI2floxMX , was made by insertion of a kanMX cassette ( Figure 1B , construct ( iii ) ) [42] , [43] . However , the Cre-independent His+ background from this reporter was too high ( ∼2×10−6 His+ among total cells ) . We created a HIS3 based Cre reporter system with very low Cre-independent background by placing the downstream loxP site , splice acceptor and C-terminal portion of a his3-AI2floxMX reporter in an inverted orientation at a position 3 kb distal of HIS3 beyond the DED1 gene ( Figure 1B , construct ( iv ) ) . The N-terminal portion of his3-AIlox is at the normal chromosome XV position for HIS3 and is marked by hygMX , while the C-terminal portion of his3-AIlox was marked with a zeoMX cassette . Cells with this inverted lox reporter , designated his3-AI2floxINV , are His− , hygromycin resistant and zeomycin resistant . If Cre is active , it can cause inversion of the interval between the two loxP sites to generate the functional HIS3-AI2lox gene ( Figure 1B , construct ( v ) ) . These cells are His+ , hygromycin resistant and zeomycin resistant . The frequency of Cre-independent His+ cells among total cells with this system is <10−6 ( Figure 2C ) . In the experiments described here it was anticipated that the mutant Cre-Y324C protein should act as a dominant inhibitor of wild type Cre protein . That is , assembly of mutant subunits into the tetramer will block its function . Therefore , we expected that it is important to have very low levels of expression in order to favor assembly of tetramers from translation of one mRNA . This condition promotes the detection of transcription errors that restore the Tyr codon in the cre-Y324C transcript . We used two approaches to have low levels of transcription ( Figure 1A ) . First we placed the cre gene under the control of the GAL1 promoter but grew the cells in the presence of glucose . Under these glucose repressed conditions , expression was expected to be rare . In the second approach , we placed the cre-Y324C allele under the control of the HO promoter so that it would be expressed only in that half of the cell population that had already divided once before [44] , [45] . Our initial experiments used the PGAL1-cre-Y324C expression system as the transcription error substrate ( inserted into the BUD5 gene ) and the his3-AI2floxINV Cre activity reporter . For cells with a WT Pol II ( GRY3739 ) the frequency of His+ cells among the total population is similar in the absence of Cre or with the PGAL1-cre-Y324C construct ( Figure 2A&C ) . In this assay , patches of cells grown on rich media ( YPD ) were replica plated onto synthetic complete medium lacking histidine . The starting strains cannot grow , but rare His+ cells within the patch can grow into small colonies or papillae . The PGAL1-cre-Y324C strain lacking TFIIS ( dst1Δ GRY3742 ) has an elevated level of His+ cells ( Figure 2A&C ) that is not observed when the cre gene is absent . We interpret the elevated level of papillation in the TFIIS defective strain as a reflection of transient Cre activity caused by uncorrected G → A errors during transcription in the mutant cre-Y324C gene that restore the UAU tyrosine codon in the mRNA ( Figure 1A ) . To demonstrate that the His+ cells were not a result of an elevated reversion rate for the cre-Y324C mutation in TFIIS defective cells , 11 independent His+ cells from the dst1 strain were crossed to a cell carrying an ade6-AI2floxkanMX reporter and shown to be still defective for Cre recombinase activity . In addition , the cre gene sequenced from 12 more His+ colonies still carried the cre-Y324C mutation . To determine whether the increase in His+ cells might be the result of elevated Cre-independent recombination between the lox sites in TFIIS defective strains , we compared the frequency of His+ cells in the absence of the cre gene and observed that WT and dst1 strains gave similar levels . These results confirm that TFIIS has a role in vivo in editing RNA errors and promoting transcription fidelity . RPB9 has been identified as a nonessential subunit of Pol II that promotes accurate start site selection , efficient elongation , contributes to transcription fidelity [11] , [23] , [46]–[50] and regulates mismatch extension [24] . Consistent with a role for the Rpb9 subunit in promoting transcription fidelity in vivo , we find that a null allele of RPB9 , rpb9-Δ0 ( GRY3743 ) , shows an elevated His+ papillation rate in the his3-AI2floxINV assay ( Figure 2A&C ) . In order to test a collection of rpb1 mutations , we created a strain ( GRY2855 ) with the PGAL1-cre-Y324C substrate , the his3-AI2floxINV reporter and the rpb1-natMX null allele complemented by RPB1 on a URA3 selectable plasmid ( pJDI220 ) . We made rpb1 variants on a LEU2 based plasmid ( pJS757 ) and substituted the mutant alleles for the RPB1 wild type allele by transforming in the LEU2 plasmids and selecting for loss of the URA3 plasmid with 5-FOA which selects against Ura+ cells [51] . Cells with the rpb1-E1230K ( rpo21-24 ) mutation ( pJS932 ) , which blocks the ability of TFIIS to bind to Pol II [52] , show an elevated number of His+ papillae ( Figure 2A&C ) . This is consistent with the results presented above for the TFIIS defective strain ( dst1Δ0 ) . We previously described rpb1-E1103G ( pJS781 ) as causing increased misincorporation during transcription [19] . That allele was also among those identified as having elevated misincorporation rates in vitro [3] . When put into the his3-AI2floxINV reporter strain with cre-Y324C under the control of the GAL1 promoter , it showed a modest increase in His+ papillation ( Figure 2A&C ) . To use the his3-AI2floxINV reporter as an effective screen for new rpb1 mutations that reduce fidelity , we addressed the problem of how to get widespread but low level expression of the cre-Y324C gene . The ideal condition would be the one that produced one transcript per cell . The GAL1 promoter in the presence of glucose is repressed [53] , but low levels of transcription in a population probably reflects some cells with transcripts and most cells with none . The promoter for the HO gene is under complex regulation so that it is only expressed late in the G1 phase of the cell cycle , only in cells that have the a or α mating phenotypes ( not a/α “diploid” cells ) , and only in cells that have divided at least once before , so called mother cells [44] , [45] . We placed the cre-Y324C gene under the control of the HO promoter at its normal position on chromosome IV . Only half of the cells ( mothers ) in the population will be expressing PHO-cre-Y324C , and half of those will be expressing it for the first time . We reasoned that this would create a condition where rare transcripts that have an error that restores the tyrosine codon would produce active Cre recombinase that would not be in competition with the inactive monomers for the assembly of active Cre tetramer . To make it easy to introduce rpb1 variants into this system , we made a yeast strain ( GRY3258 ) with the PHO-cre-Y324C substrate , the his3-AI2floxINV reporter , and the rpb1-natMX deletion complemented by RPB1 on a URA3 2-micron based plasmid ( pJS725 ) . As above , this makes it possible to substitute in rpb1 variants on a LEU2 based vector by plasmid shuffling , selecting against the URA3 RPB1 with 5-FOA [51] . Figure 2B illustrates the clear distinction between RPB1 and the transcription fidelity mutant rpb1-E1103G in the number of His+ papillae with the his3-AIloxINV reporter and the PHO-cre-Y324C substrate . The increase is dependent on the cre-Y324C gene . Similarly , rpb1-E1230K , which blocks TFIIS function , gives a clearly elevated signal in this assay . To identify additional rpb1 alleles that cause reduced transcription fidelity in vivo , we screened a mutagenized pool of a LEU2 CEN based plasmid carrying RPB1 ( pJS757 ) . The pool was transformed into GRY3258 selecting Leu+ and colonies picked and arrayed as patches . The patches were replica plated to FOA plates to select against the URA3 RPB1 plasmid . From the FOA plates the patches were replica plated to SC-His media to detect patches with elevated levels of Cre-mediated His+ papillae . Mutant candidates were struck for single colonies , and retested as patches . The LEU2 based plasmid from those that repeated the elevated level of His+ papillae was recovered into E . coli and retransformed into GRY3258 to confirm that the mutation causing the elevated Cre activity was on the plasmid . Those that passed that test were sequenced to identify the rpb1 mutation responsible for the transcription infidelity phenotype . In all , over 12 , 000 transformants were tested from which eight rpb1 variants were identified . These included re-isolating rpb1-E1103G , plus seven new alleles: rpb1-G823S , -A1076T , -A1076V , -M1079I ( T1548I ) , -K1132E , -T1141I ( G888D , I1237T ) , and -S1229F . The phenotype of the rpb1-T1141I ( G888D , I1237T ) variant was shown to be a consequence of the T1141I substitution by testing variants with each of the separate mutations . Patches demonstrating the phenotypes of these variants are shown in Figure 2B . In addition , we show results for an allele rpb1-T1113P , isolated from a screen for alleles that elevate transcription slippage [15] . Quantification of the increase in transcription errors was accomplished by measuring the frequency of His+ cells as determined by growth on medium lacking histidine ( SC-His ) normalized to growth on rich media . The mean frequency from 8 or more cultures was determined for each strain and shows that the mutations identified by our screen increase the frequency of cells with the His+ phenotype 7–50 fold compared to the wild type strain ( Figure 2C ) . In the in vivo screen , increase of the frequency of His+ papillae by the mutations in RPB1 can be indirect . For instance , it could be caused by the increase of cre expression because of an increase in initiation by the mutant Pol II . It is noteworthy that the His+ frequency is much higher in the PHO-cre system than in the PGAL1-cre system for the rpb1-E1103G allele . In contrast the His+ frequencies for the rpb1-E1230K allele are similar in the two systems . Whether this reflects a differential level of sensitivity for these promoters to these defects has not been determined . Furthermore , a higher net frequency of error-containing RNA may be caused not only by the higher frequency of misincorporation ( as in the rpb-E1103G mutant ) , but also by higher efficiency of mismatch extension and/or on lower efficiency of RNA editing ( like in a DST1-deficient strain or in the rpb1-E1230K mutant , defective in TFIIS binding ) [52] . Below we describe the results of three in vitro tests designed to address the biochemical basis for the low-fidelity phenotype of the alleles identified in the genetic screen: 1 ) the ability of Pol II to select cognate NTP , 2 ) the capacity to extend a mismatch , and 3 ) the ability to remove misincorporated NMP by TFIIS-mediated editing . To determine whether any of the new alleles of rpb1 have direct impact on cognate NTP selection , we tested in vitro the level of misincorporation errors by the Pol II variants . Misincorporation rates and transcription fidelity may depend on a sequence context [4] . Therefore , we employed a DNA corresponding to the region surrounding codon 324 ( TGT ) in the cre-Y324C gene as the template for the assembly of the promoter- and factor-independent Pol II elongation complexes [54] used in these fidelity assays . The elongation complex ( U10 ) was stalled before incorporating AMP and the frequency of GMP to AMP transition error was directly measured using a “competition” assay for transcription fidelity [20] , which provides fidelity values nearly identical to those obtained by conventional fidelity assay for the wild type and mutant variants of Pol II [20] , [55] . A similar assay has been described for T7 DNA polymerase [56] . The competition assay employs differential mobility in denaturing polyacrylamide gels of short RNA species of the same length , but different composition to distinguish cognate from misincorporation events . To determine the frequency of misincorporation , U10 ( schematically depicted in Figure 3A ) was incubated with a mix of GTP in a low ( 20 nM ) concentration and different higher ( 0 . 5 , 0 . 75 and 1 . 5 mM ) concentrations of ATP . In these conditions , the reaction products of both cognate ( GMP ) and non-cognate ( AMP ) incorporation were separated ( Figure 3B , lanes 3–13 ) and quantified ( Figure 3C ) . To determine the misincorporation frequency of AMP in place of GMP in the presence of equal concentrations of cognate and non-cognate substrates , the ratio of non-cognate to cognate products was normalized to ( divided by ) the ratio of non-cognate ( ATP ) to cognate ( GTP ) substrate concentrations . The resulting misincorporation frequency was similar for different concentrations of ATP tested suggesting that it faithfully reflects fidelity of substrate selection in this position , independent of the substrate concentration . This assay is particularly useful way to qualitatively compare the relative misincorporation of various alleles . It is clear that Pol II carrying the rpb1-E1103G mutation misincorporates more frequently than wild type Pol II ( Figure 3B , lane 8 ) , consistent with its previously reported defect in NTP selection [19] . The rpb1-A1076T , A1076V , and T1113P substitutions also noticeably increase the frequency of misincorporation ( lanes 5 , 6 , and 9 ) . The RPB1-A1076 residue is located in the trigger loop , a mobile element of the catalytic subunit implicated in transcription fidelity maintenance by genetic and biochemical analyses [3] , [19] . In contrast , mutations located in the TFIIS-binding domain ( rpb1-K1132E , rpb1-T1141I and rpb1-S1229F ) and one mutation in the trigger loop ( rpb1-M1079I ) do not appear to change GMP to AMP transition frequency in vitro . Next , we tested whether the newly identified rpb1 alleles alter the ability of Pol II to extend the mismatch by incubating the complex with 1 mM non-complementary ATP and 0 . 5 mM next cognate UTP to allow misincorporation and mismatch extension . Under these conditions , wild type Pol II does not easily extend the A11 mismatch and pauses at the U12 and A13 positions ( Figure 4A , lane 3 ) . Apparently , the mismatch continues to present an obstacle to efficient transcript elongation , consistent with the recent report by Knippa and Peterson [24] . Inefficient mismatch extension , similar to wild type Pol II was observed in the Pol II variants carrying mutations in the TFIIS binding site ( rpb1-K1132E , rpb1-T1141I , rpb1-S1229F and rpb1-E1230K ) ( Figure 4A , lanes 10–13 ) . In contrast , mutations in the residues located in the trigger loop ( rpb1-A1076T , rpb1-A1076V and rpb1-M1079I ) or next to the base of the trigger loop ( rpb1-E1103G and rpb1-T1113P ) significantly promote mismatch extension . The experimental setup described above was chosen because it best reflects the situation in vivo when misincorporation occurs in the presence of the next ( cognate ) NTPs , and the newly formed mismatch can be immediately extended . When the mismatch is pre-formed before the next cognate substrate is provided , Pol II has more time to backtrack , which might artificially decrease the fraction ( if backtracking is irreversible ) or the rate ( if backtracking is reversible ) of the mismatch extension . However , if misincorporation is much slower than mismatch extension , the true rate of the latter is difficult to assess in this particular experimental setup . Therefore , mismatch extension by M1079I and E1103G Pol II variants has been assayed in a different setup , when misincorporation was allowed to proceed for 10 min before UTP was added to extend the mismatch ( Figure 4C ) . Quantitative analyses of these data ( Figure 4D ) confirm our conclusion that mutations in the trigger loop promote mismatch extension . The enhanced mismatch extension by rpb1-M1079I mutant , which does not display increased frequency of misincorporation , provides an explanation for the identification of this allele as error-prone in the in vivo screen . Evidently , relatively fast mismatch extension interferes with the post-incorporation error removal by TFIIS-mediated cleavage or the proteolytic degradation of irreversibly arrested Pol II , thus increasing the fraction of the full-length transcripts containing the error . The in vivo and in vitro properties of Pol II carrying the rpb1-M1079I substitution provide direct experimental evidence that recognition of incorporated mismatches by core Pol II significantly contributes to fidelity maintenance . The effect of the newly identified mutations on interaction of Pol II with TFIIS has been tested by treating the A*11 elongation complex carrying the 3′-end mismatch with TFIIS , and observing the extent of 3′RNA cleavage ( Figure 5 ) . The 3′ mismatched AMP and the complementary penultimate UMP are removed after one minute incubation with TFIIS in the major fraction of the wild type complexes , resulting in appearance of a 9-nt RNA ( C9 ) . Note that the C9 product was barely detectable in the initial A*11 elongation complexes ( lane 3 in Fig . 5 A and B ) . The shorter RNA cleavage products ( A8 , A7 , and G6 ) are also detected , especially after incubation with higher concentration ( 600 nM ) TFIIS ( Fig . 5B , lane 4 ) . The shorter RNA cleavage products ( A8 , A7 , and G6 ) are also detected , especially after incubation with higher concentration ( 600 nM ) TFIIS ( Figure 5B , lane 4 ) . The appearance of the 5′ cleavage products as short as 6 nt is somewhat unexpected , considering that the RNA-DNA hybrid in Pol II elongation complex is 8-bp long [57] . Nevertheless , we use appearance of the short cleavage products , along with the major C9 product , to judge the efficiency of TFIIS-induced RNA cleavage . As expected , substitutions in the TFIIS binding site ( rpb1-S1229F and rpb1-E1230K ) dramatically decreased Pol II susceptibility to TFIIS-induced mismatch removal . The C9 cleavage product appears only when the elongation complexes are treated with the higher concentration ( 600 nM ) TFIIS , and no shorter products are detected ( compare lane 4 with lanes 13 and 14 in Figure 5A&B , ) . A less pronounced , but still substantial decrease in the sensitivity to TFIIS is observed for rpb1-G823S , K1132E , and rpb1-T1141I mutants ( lanes 5 , 11 , and 12 ) . It is likely that K1132 and T1141 substitutions directly reduce binding of TFIIS . The G823S substitution in the bridge helix may alter TFIIS binding , but alternatively could be involved in TFIIS-induced transcript cleavage , and/or affect Pol II backtracking . The effect of T1141I substitution was weaker than the effects of the other three substitutions in the TFIIS binding site ( note the presence of the short cleavage products in Figure 5B , lane 11 ) . It is interesting that Rpb1-G823S , which shows a decreased sensitivity to TFIIS similar to Rpb1-K1132E substitution , also slightly promotes misincorporation and mismatch extension in vitro ( Figures 3 and 4 ) . All other mutants tested for susceptibility to TFIIS were similar to wild type Pol II ( Note the A8 , A7 and G6 products in Figure 5B , lanes 4 and 6–10 ) .
The random mutagenesis of the entire RPB1 ( RPO21 ) gene yielded three groups of amino acid residues that are highly clustered in the X-ray structure of Pol II [18] . The rpb1-A1076T/V , rpb1-M1079I , and rpb1-E1103G mutations alter the trigger loop , a domain of Pol II that closes over the active site and has been demonstrated to influence fidelity in vitro [3] , [19] . The rpb1-T1113P mutation targets a residue in the immediate vicinity of E1103 ( Figure 6A ) . The rpb1-G823S allele ( Figure 6B , right panel ) alters the bridge helix , a domain that interacts with the active site and with the trigger loop . Substitutions in the bridge helix of E . coli RNA polymerase have been demonstrated to reduce the fidelity of transcription in vitro [59] . Notably , the changes identified in this work directly target the flexible hinge regions of the trigger loop and the bridge helix that were identified by molecular dynamics simulations based on X-ray crystallography and confirmed by mutational analysis of yeast Pol II [20] . The hinges , H1 and H2 in the trigger loop and H3 and H4 in the bridge helix , according to the nomenclature from [20] ( Figure 6C ) undergo conformational changes associated with NTP binding , sequestration , catalysis and translocation . The trigger loop and bridge helix residues forming the hinges have been implicated in transcription control [19] , [55] , [59] , [60] . Another cluster of mutations alters the TFIIS binding site ( Figure 4A , residues shown in red ) [61] . The rpb1-S1229F mutation likely reflects a defect in the interaction of Rpb1 and TFIIS , similar to the well characterized rpb1-E1230K allele [52] . The rpb1-K1132E and rpb1-T1141I substitutions also alter positions close to where TFIIS binds [61] . These mutations may impair TFIIS-dependent error editing by decreasing TFIIS binding , similar to mutations of E1230 and S1229 . Alternatively , they might affect the backtracking capabilities of Pol II , a mechanism related to Pol II translocation and likely affected by the G823S substitution . The precise characterization of TFIIS cleavage mechanisms affected by mutations identified here is beyond the scope of this work . Most importantly , our results represent a direct demonstration of proofreading function of TFIIS in living cells . Although there is firm evidence that TFIIS plays a major role in correction of transcription errors in vitro , several attempts to demonstrate the similar activity in vivo were inconclusive [10] , [11] . Our results are consistent with those by Koyama and co-workers showing a major contribution of TFIIS to Pol II fidelity in yeast [12] , [21] . Our in vivo approach combined with the biochemical in vitro validation revealed at least three intrinsic and one factor-dependent mechanism for faithful transcription in living cells . The TFIIS-dependent mechanism has been discussed above . The first intrinsic mechanism includes regulation of the trigger loop movement . Interaction of Rpb1 E1103 residue with the H2 hinge ( residues 1095–1099 ) of the trigger loop has been previously proposed to delay the trigger loop closure thus slowing down transcription elongation and supporting fidelity maintenance [3] , [19] , [23] , [62] . The observation that rpb1-T1113P substitution renders transcription error-prone indicates that the T1113 residue plays the same or similar role as E1103 . Notably , the recent molecular dynamic simulations of the Pol II trigger loop opening and closure revealed the potential interaction of T1113 with the trigger loop predicting that substitutions of T1113 residue should increase transcription elongation rate [63] . Our work provides direct proof that the mechanism dependent on E1103 and T1113 interaction with the trigger loop acts in vivo . The second potential mechanism includes H1 hinge of the trigger loop ( Rpb1-A1076/M1079 ) and H4 hinge of the bridge helix ( Rpb1-G823 ) that may crosstalk through the adjacent L1081 ( wedging ) residue of the trigger loop [64] ( Figure 6B&C ) . Because conformational changes of the bridge helix and the trigger loop are implicated in translocation [64]–[66] our identification of error-prone mutants in the mobile hinges of these two structural elements suggests a possible connection of the Pol II translocation cycle and cognate NTP selection . The mechanism of this link remains to be established . The third intrinsic mechanism revealed by our work does not immediately follow from the extensive in vitro studies of transcription fidelity . It involves inhibition of the mismatch extension with the next cognate NMP . This mechanism , apparently mediated by the trigger loop and bridge helix , promotes Pol II pausing or arrest after misincorporation . Our finding that several mutations selected in the Cre-based genetic screen promote mismatch extension in vitro strongly argues that slow extension of a mismatch in the nascent RNA plays a major role in faithful transcription in living cells by allowing correction to occur . The rpb1-M1079I allele identified here appears of special interest , because it does not affect NTP selection by Pol II , but clearly promotes mismatch extension . Because the net frequency of in vivo transcription error occurrence correlates with the propensity of E . coli RNA polymerase to backtrack within a given sequence context [58] , we are currently investigating the effect of rpb1-M1079I substitution on the mismatch-induced transcription arrest . The slow mismatch extension may enable correction of the error by TFIIS-mediated transcript cleavage [27] . The arrest may also provide time for elimination of the flawed transcript by ubiquitin-mediated proteolytic degradation of Pol II [67] . One can imagine rpb1 alleles that impair accuracy in nucleotide selection , but , due to a reduced transcription elongation rate [3] , [20] , [60] provide increased opportunity to detect and remove misincorporated NMPs . Thus , slow elongation that results in poor mismatch extension could reduce production of the full-length error-containing Cre mRNA , counter-acting the defect in substrate selection . Accordingly , faster elongation might further decrease overall fidelity of the mutants with impaired NTP selectivity , such as rpb1-A1076T , A1076V , E1103G and T1113P [19] . In conclusion , we developed a reliable experimental approach to monitor transcription fidelity in vivo . Using this tool we will characterize the role of other core Pol II subunits , as well as known transcription elongation factors , such as TFIIF , Spt4/5 and Spt6 in transcription fidelity maintenance . This methodology will allow for isolation of mutants affecting transcription fidelity and thus will promote identification of new genes and mechanisms related to the accuracy of transcription . These experiments also highlight the complications associated with assigning a specific phenotype solely to the fidelity of transcription . The rpb1-E1103G mutation increases the transcription error rate . When combined with a defect in TFIIS ( dst1Δ ) , which corrects transcription misincorporation errors , the double mutant is dead . It is tempting to conclude that the death is the direct result of an error catastrophe of too many transcription errors resulting in too many incorrect RNAs and defective proteins encoded by them . However , TFIIS also has a role in transcription initiation at some promoters and the lethality of the double mutant could reflect some more complicated interplay of the properties of the defective RNA polymerase and the changes in the transcriptome caused by the TFIIS defect . Similarly , it was possible that an increase in the frequency of His+ cells in our genetic assay reflected changes in the expression level of the cre reporter genes caused by a change in the transcriptome unrelated to reduced fidelity . A recent survey of changes in the yeast transcriptome caused by RNA polymerase variants further emphasizes this biological feature [28] . They found changes in transcription start sites , altered relative transcript levels , and changes in splicing efficiency . Thus , it was important to include a biochemical characterization of the mutant polymerases to see if there is a fidelity defect . We characterized misincorporation , mispaired base extension , and mispaired base removal and found defects in one or more of these processes in each of the mutants . These mutants provide an opportunity to elucidate the cellular consequences of error prone transcription . The work described here is a step to understanding the biological role of faithful information transfer from DNA to RNA .
See Table 1 . pJS757 is a LEU2-based CEN vector carrying the RPB1 ORF , as well as 594 bases upstream and 501 bases downstream of the ORF [16] . pJS725 and pJDI220 are URA3-based 2-micron circle plasmids with the same RPB1 insertion as pJS757 . RPB1 was randomly mutagenized by passing a pool of plasmid pJS757 twice through the mutator ( mutS mutD mutT ) E . coli strain XL-1 Red ( Stratagene ) . The yeast strains are related to the BY4741 and BY4742 [68] See Table 1 . The cre gene used in these experiments has a seven amino acid nuclear localization site from the large SV40 T-antigen added at the N-terminus [69] . The PGAL1-cre gene was made by fusing the NLS-cre ORF to the PGAL1 promoter inserted into the BUD5 gene at an autochthonous EcoR1 site . The PHO-cre gene was made by overlap PCR and integrated at the normal position for HO . The insertions were made by selecting for replacement of URA3 , previously inserted at those locations . Direct repeat of loxP: The his3-AI2floxkanMX reporter ( Figure 1B , construct ( iii ) ) has an artificial intron inserted into HIS3 at an MscI site in codon 70 . The 1710 base insertion includes two loxP sites in direct orientation flanking the kanMX cassette . kanMX is in the same orientation as HIS3 so that the terminator blocks transcription through the rest of HIS3 resulting in cells that are His− . The Cre recombinase can remove the 1502 bases including kanMX plus one loxP resulting in a spliceable intron ( HIS3-AI2lox Figure 1B , ( ii ) ) and cells that are His+ . The ade6-AI2floxkanMX reporter has the same artificial intron inserted after the tenth codon of ADE6 causing cells to be ade6− , but Cre recombinase can remove kanMX and make a functional ADE6-AI2lox gene . Inverted repeat of loxP: The his3-AI2floxINV substrate ( Figure 1B , ( iv ) ) was constructed on chromosome XV at the HIS3 locus and surrounding region . This reporter contains the N-terminal portion of HIS3-AI2 and the splice donor part of the artificial intron ending at the loxP site and is marked by hygromycin resistance ( hygMX ) . A lox site , the splice acceptor portion of the intron and the C-terminal portion of the HIS3-AI2 , marked by zeomycin resistance ( zeoMX ) , was inserted in inverted orientation 682 bases downstream of the GEP3 gene ( 2 . 8 kb beyond HIS3 ) . Cre-directed recombination inverts the floxed DNA ( including the DED1 gene ) creating the functional HIS3-AI2lox gene ( Figure 1B-v ) . Hygromycin ( hygMX ) is from pAG32 [70] and Zeocin ( zeoMX ) is from pHybLex/Zeo ( Invitrogen ) . Pol II variants carrying wild type or mutant Rpb1 were introduced into a protease-deficient yeast strain GRY3175 by plasmid shuffle . Hexahistidine-tagged Rpb3 [57] was used to pull down Pol II from the whole cell lysate essentially as described [54] . Specifically , cells from 3–4 ml of stationary ( 2–3 days ) culture were pelleted , washed once with cold water and resuspended in lysis buffer ( 150 mM Tris–acetate , pH 7 . 9 , 50 mM potassium acetate , 5 mM MgCl2 , 10 µM ZnCl2 , 2 mM 2-mercaptoethanol , 0 . 5 mM EDTA and protease inhibitors ) . The cells were disrupted using a Precellys homogenizer according to manufacturer's instructions , the lysate was removed from the glass beads , and KCl was added to 1M final concentration . The debris was precipitated for 15 min at 14 , 000 rpm in Eppendorf table-top microcentrifuge at 4°C . The supernatant was added to 50 µl of Ni-NTA agarose pre-washed with transcription buffer ( TB ) containing 20 mM Tris-HCl , pH 7 . 9 , 5 mM MgCl2 , 10 µM ZnCl2 , 2 mM 2-mercaptoethanol and 1000 mM KCl ( TB1000 ) . Pol II was immobilized on the beads for 30–50 min at 4°C , and the beads were extensively washed with TB1000 and TB40 ( TB with 40 mM KCl ) . The elongation complex was assembled and purified with the immobilized Pol II exactly as described [54] using the following oligonucleotides: Cre RNA C9: 5′ GUC AUG AAC 3′ ( phosphorylated with T4 polynucleotide kinase in the presence of γ-P32-labeled ATP ) ; NDS-Cre-Cys ( Non Transcribed DNA Strand ) 5′GGCTGGACCAATGTAAATATTGTCATGAAC TGTATCCGTAA CCTGGATAGTGAAACA 3′; and TDS-Cre-Cys ( Transcribed DNA Strand ) which is an exact complement of NDS ( Cre-Cys ) . All NTPs used for walking and misincorporation assays were additionally purified [19] . The elongation complex containing 10-nt RNA ( U10 ) was obtained by 5 min incubation of the assembled and purified complex with 5 µM UTP and washed 4 times with 1 ml of TB40 . For the TFIIS sensitivity assay , mismatched A11 elongation complex was obtained by 5 min incubation of U10 with 1 mM ATP , purified by 4 washes with TB40 , eluted from the beads with 100 mM imidazole in the presence of 0 . 2 mg/ml acetylated BSA , diluted 10-fold with TB40 to decrease imidazole concentration and concentrated using Microcon AmiconUltra ( Millipore ) concentrator to 30 µl . Reactions were stopped by addition of equal volume of gel loading buffer containing 10 M urea and 50 mM EDTA . The reaction products were resolved in 20% polyacrylamide gels ( 19∶1 ) in the presence of 1× TBE and 7M urea . To resolve the two 11-nt products of cognate GMP and mismatched AMP incorporation in the competition fidelity assay , the 4-mm thick , 20×40 cm gels were used , and electrophoresis has been performed in 1× TBE at constant power of 65 W until the bromphenol blue tracing dye was within 3 cm of the bottom of the gel . For other experiments the shorter 20×20 cm gels were used and the electrophoresis was performed at 50 W constant power . | Mistakes made during the synthesis of messenger RNAs have been difficult to detect , both because mRNAs can be short lived , and because the translation of mRNAs into proteins has a much higher error rate that masks transcription errors . We present here a highly sensitive genetic screen that detects transcription errors and use it to identify mutations that increase the error rate of RNA polymerase II . The screen incorporates a new principle that allows transient transcription errors to cause permanent genetic changes . The screen is based on suppression of a missense mutation ( cre-Y324C ) in the active site of the Cre recombinase . Infrequent and transient transcription errors that restore the original codon for Y324 cause the Cre-dependent activation of a reporter gene . Background from translation errors is negligible because Cre acts as a tetramer in which all four subunits require the active site tyrosine . Transcription errors as low as ∼10−6 can be detected . We identify rpb1 mutations that define four classes , those that have increased ( 1 ) misincorporation , ( 2 ) extension of a misincorporated base , ( 3 ) both misincorporation and extension , and ( 4 ) those that block the activity of the transcription proofreading factor , TFIIS . | [
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] | 2014 | A Genetic Assay for Transcription Errors Reveals Multilayer Control of RNA Polymerase II Fidelity |
Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis . It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression . DNA copy number alterations ( CNAs ) are one of the ways in which cancer genes are deregulated in tumor cells . We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss . To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data . The resulting regions of high co-occurrence can be investigated for between-region functional interactions . Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies , respectively , showing that we can recover truly co-occurring genomic alterations . In addition , our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes . These networks are also highly enriched for functional relationships between genes . We further examine sub-networks of these networks , core networks , which contain many known cancer genes . The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network . Our findings suggest that large-scale , low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes .
Tumor development is generally thought to be a process in which healthy cells transform into malignant tumor cells through the step-wise acquisition of oncogenic alterations [1] , [2] . This implies that certain changes have to occur together for effective oncogenic transformation of a normal cell . There are a multitude of ( epi- ) genetic lesions that cause deregulated expression of oncogenes and tumor suppressor genes . Co-operative deregulation of cancer genes has indeed been observed in several different settings . Retroviral insertional mutagenesis screens in mice have shown preferential co-mutation of specific combinations of genes within the same tumor [3] . Likewise , in a study where a thousand individual tumors were screened for mutations in 17 different oncogenes , preferential co-mutation of the PIK3CA and KRAS genes was observed [4] . Besides single basepair mutations or retroviral integrations , the activity of genes can also be perturbed by DNA copy number alterations that arise as a result of genomic instability , which is frequently observed in tumor cells [1] . Whether genomic instability is important for tumor initiation is controversial , but its contribution to tumor progression is undisputed [5] , [6] . Loss of DNA is a mechanism for the tumor to eliminate copies of tumor suppressor genes , which prevent cancer formation . Conversely , DNA copy number gain or amplification may lead to activation of oncogenes that promote tumor development . We aimed to find genomic regions of gains and losses that are preferentially gained or lost together . We could subsequently link genes that lie in co-occurring regions to each other , allowing us to find functional interactions that reveal the mechanisms underlying tumor development . DNA copy number alterations ( CNAs ) may be measured on microarray platforms [7] . Array-based comparative genomic hybridization ( aCGH ) of differentially labeled tumor and normal ( 2n ) DNA is performed on oligonucleotide- or Bacterial Artificial Chromosome ( BAC ) based microarray platforms . For each probe on the microarray , the ratio of signal intensities of tumor versus normal DNA is a measure of the relative DNA copy number of the corresponding genomic region in the tumor sample . Platforms designed to identify single nucleotide polymorphisms ( SNPs ) can also infer CNAs by comparing the raw probe intensity values measured in a tumor sample with a reference sample . In order to extract those DNA copy number aberrations that preferentially occur together , we developed an analysis framework . The basic premise of our analysis is to define a pair-wise score for any given pair of genomic locations present in the dataset . This scoring index will only be high if both genomic locations are recurrently aberrated in multiple independent samples within the tumor panel , and if they co-vary similarly over the different samples ( Figure 1 ) . Using a Gaussian kernel convolution method we look for aggregates of high scores in the 2D genomic pair-wise space ( Figure 2 ) . The top peaks in the convolved score matrix can be mapped back to two distinct co-mutated genomic locations . The genes that reside in these genomic locations can then be functionally related to each other . The raw data consist of non-discrete measurements of the average DNA copy number of the population of cells present in the measured sample . The signal consists of a measurement of a heterogeneous population of tumor cells , which may contain many populations potentially carrying different mutations and copy number alterations , as well as normal ( diploid ) cells . To reduce heterogeneity as much as possible we choose to analyze a collection of hematopoietic tumor cell lines , which on a per-sample basis can be considered clonal . There were several other reasons for analyzing this particular dataset . First , it is a high resolution dataset of well-characterized , clinically relevant samples . Although these samples are cell lines , they are widely used as a model system for the diseases from which they have been derived . Second , this collection of samples includes cell lines derived from T- and B-cell leukemias carrying rearranged T-cell receptor and immunoglobulin loci , respectively . We therefore should be able to separate these two distinct lymphoid malignancies based on co-occurring DNA copy number losses at the T-cell receptor and immunoglobulin loci . During T- and B-cell development , these loci undergo DNA recombination and gene deletion in a process known as V ( D ) J-recombination . The human genome contains three specific T-cell receptor loci ( alpha/delta , beta and gamma ) on two different chromosomes that determine their variability . B-cells have three different loci ( IgG kappa , IgG lambda and the IgG heavy chain ) on three different chromosomes that undergo recombination to generate a diverse repertoire of immunoglobulins . Since T- and B-cells only undergo recombination of their respective loci after lineage commitment , it is unlikely that T-cell receptor loci are recombined in B-cells and vice-versa . If our approach is successful at finding co-occurring losses , it should identify the co-occurring rearrangements at the T-cell receptor alpha/delta and beta/gamma loci in T-cell leukemias . Similarly , we should be able to pick up co-occurring losses at the IgG kappa , lambda and heavy chain loci in B-cell malignancies .
A classic example of finding associations in a large ( binary ) dataset is association rule mining . Identification of cooperating events in continuous data requires a different approach than binary association rule mining . First we developed a method to score for co-occurrence between two continuous measurements ( Figure 1 ) . We then applied this score in a framework that is able to find co-occurrences in genome-wide measurements . This framework is shown in Figure 2 and is detailed in the Materials and Methods . DNA copy number measurements at two different genomic loci can be visualized in a 2D space , with each axis representing measurements at a certain genomic locus . A point in this space represents a sample in which both loci were measured . Figure 1a shows four hypothetical combinations of measurements . We sought to score for co-occurring high or low values in the DNA copy number data; in other words , regions that display similar patterns of large-amplitude amplification and deletion across the tumor set . This situation is shown in the third panel Figure 1a . The other panels show other potential situations that may arise when comparing two continuous measurements . To score for co-occurring gains all negative values are set to zero ( Figure 1b ) . To score for co-occurring losses all positive values need to be set to zero and the absolute values of the measurements need to be used . We use the covariance of the two measurements to score for co-occurring loci . This score only rewards a high value to a truly co-occurring and co-varying pairs of measurements ( Figure 1c , right panel ) . However , a high covariance alone is not sufficient , since it is possible that a high covariance occurs while at least one of the loci never reaches a high amplitude ( see Figures 1e and 1f ) . For this reason we multiply the covariance score with the sum of the individual valued in each sample . This method of scoring only rewards a high value to a co-varying pair of measurements with a large aberration amplitude across the tumors ( Figure 1c , right panel ) . The co-occurrence scores can be computed for every pair of genomic loci ( Figure 2c ) . By performing a two-dimensional Gaussian kernel convolution on these scores in the co-occurrence space we can take local neighborhood effects into account . This operation is performed for different kernel widths in order to capture scale dependent effects , resulting in a Convolved Co-occurrence Matrix ( CCM ) as shown in Figure 2d . High values in this matrix represent candidate co-occurring regions in the data . A peak in the CCM can be mapped back to two specific loci , the size of which is determined by the σ parameter of the Gaussian function used to convolve the score matrix ( Figure 2e ) . The genes that are located in the loci associated with a peak in the CCM are subsequently investigated . We examined both enrichment for known cancer genes in these gene lists and we investigated functional relationships between the genes derived from the two loci ( Figure 2f ) . Additional details can be found in the Materials and Methods section . We ran our analyses on the aCGH profiles of 95 hematological tumor cell lines analyzed on the Affymetrix Genome-Wide Human SNP Array 6 . 0 . See the supplemental data ( Dataset S1 ) for a list of the cell lines that were analyzed . The data was generated by the Cancer Genome Project ( Wellcome Trust Sanger Institute , Hinxton , UK ) . We employed three scale parameters: 2Mb ( σ = 1/3 Mb ) , 10Mb ( σ = 5/3 Mb ) and 20Mb ( σ = 10/3 Mb ) . In the remainder of this text we will refer to these as Scales 2 , 10 and 20 . These scales roughly determine the size of the aberrant regions we expect to find . By employing a small , medium and large scale we maximize the chance of detecting co-occurring changes of all possible sizes . To remain conservative we limited our primary analysis to the top 50 peaks in the Convolved Co-occurrence Matrix ( CCM ) for each of the scales and each of the comparisons ( gain-gain , loss-loss , loss-gain ) . This resulted in 9 top-50 lists of co-occurring regions retrieved from this dataset . A substantial fraction of the 95 cell lines are derived from T- or B-cell lymphomas with functionally rearranged T-cell receptor or IgG genes . We therefore expected to identify co-occurring losses at the T-cell receptor alpha/delta and beta/gamma loci in the T-cell leukemias . Similarly , our method should identify co-occurring losses at the IgG kappa , lambda and heavy chain loci in B-cell malignancies . Because the recombination loci for both the T-cell receptor and the IgG genes are both relatively small ( in the 1Mb range ) we expected to retrieve these co-occurring losses in the small ( 2 Mb ) scale analyses . Since we disregarded co-occurrences on the same chromosome we expected to find five co-occurring losses . Indeed , four of the five expected co-occurring losses are present in the top 50 peaks of the Scale 2 analyses ( Table 1 ) . Figure 3 shows two examples from the top 50 lists of co-occurring loci . The separation of T- and B-cell lines is immediately apparent . T-cell lines are strongly associated with losses in the T-cell receptor loci . A large subset of B-cell lines are associated with losses in the IgG loci . However , a subset of the B-cell lines is not associated with any loss of these loci . In this particular subset of lines the IgG loci seem to be gained . It is known that the IgG loci are favorite partners for oncogenic translocations [8] . Whether this is the cause of the amplification of these loci is not known . While the recovery of the V ( D ) J-related recombination loci as co-occurring losses serves as a positive control for our analysis approach , we are mainly interested in identifying cooperating genes or regions that might play a role in cancer . To see whether the locations we recover are linked to this disease , we analyzed whether the co-occurring genomic loci are enriched for genes known to play a role in cancer . As a reference gene set we used the Cancer Gene Census list [9] . The results of this analysis are shown in Table 2 . As can be seen , the co-lost loci are mainly enriched for tumor suppressor genes , and the gain-gain regions for oncogenes . Since one expects loss of tumor suppressors and gain of oncogenes , this is a logical result , further increasing our confidence that our approach identifies truly relevant genomic loci . While finding enrichment for cancer genes is an encouraging result , this does not explain the possible cooperation between two loci . We expect that the co-occurring loss of two regions points to a functional relationship between the constituents of the genomic loci . A co-occurrence between two genomic regions can point to many different kinds of interactions between the genes residing in both regions , e . g . biochemical interactions of the protein products or functional collaboration of two cancer genes in tumorigenesis . We therefore decided to employ interaction data to shed further light on the genes present in the co-occurring regions . We translated the co-occurring pairs of genomic loci to pairs of gene sets , and we investigated the functional relationships of their protein products using the STRING database [10] ( version 8 . 1 ) . The STRING model weighs functional associations between genes based on several different sources of evidence , among which: biochemical interaction , joint presence in a pathway , high-throughput interaction experiments , text mining and interactions of homologs in other species . To find a functional relationship between two co-occurring regions we looked for a direct interaction in the STRING database between the two gene-sets defined by our co-occurrence analysis . To determine whether the number of observed interactions is significant , we compared the number of direct interactions found between genes located in the top 50 co-occurring regions to a set of randomly chosen pairs of genomic loci . The metric we used to determine significance is the ratio between the number of interacting genes and the total number of genes found on the genomic loci . A p-value for enrichment for direct interactions was calculated using a two-tailed Fisher's exact test . Results are shown in Figure 4 . As can be seen , the only analysis that resulted in an enrichment of functional interactions is Scale 20 , for all three situations . We found no enrichment for interacting protein coding genes on Scale 2 ( not shown ) and Scale 10 . Since we evaluated gene sets in a window one-third the size of the analysis-scale we may be under-estimating the size of the co-occurring loci and the larger Scale 20 actually captures the size of the aberrations best . In order to keep control of the complexity , we considered in our co-occurrence analysis only radially symmetric kernels , i . e . Gaussian kernels with diagonal , equal variance covariance matrices . This implies that asymmetric co-occurring regions – where a small locus co-occurs with a large locus – will not be optimally detected . Since an asymmetric co-occurring region typically consists of a series of symmetric co-occurring regions detected on a smaller scale ( just like a rectangle can be constructed from a collection of squares ) , we set out to construct larger co-occurring regions from the results of the smaller scales using a hierarchical clustering approach . For details see Supplemental Figure S1 . Briefly , we collected the loci involved in the top 500 co-occurrences of the Scale 2 analysis . This resulted in 1000 genomic loci . For each pair of loci , we calculated the genomic distance in base pairs . The distance between two loci on different chromosome arms was set to a default high value ( 1 * 108 ) . This resulted in a 1000×1000 distance matrix . On this distance matrix we performed single linkage hierarchical clustering . The resulting dendrogram was cut at 1 * 107 bp ( 5 kernel widths ) . The resulting clusters are unique genomic loci and were represented as nodes in a graph . Clusters were then linked if a co-occurrence was found between individual loci of different clusters . These links are represented as edges in a graph . The result of the clustering analysis is shown in Figure 5 . As can be seen in Figure 5 we were able to construct a network of co-occurring copy number changes for the gain-gain , loss-loss and gain-loss situations . As expected , the gain-gain and loss-loss networks show enrichment for oncogenes and tumor suppressor genes , respectively . The gain-loss network only shows enrichment for tumor suppressors . The percentage of genes involved in functional interactions between the nodes that are linked in the graph vastly exceeds the functional interaction enrichment found in the single scale 20 Mb analyses . At least 11% of the genes present in the genomic locations - represented by the nodes in the graphs - have high confidence ( >0 . 9 ) annotated functional interactions along the edges as revealed by STRING analysis . The thickness of the edges in the graphs shown in Figure 5 indicates how often a co-occurrence was found in the top 500 of the Scale 2 analysis . Several edges were strongly supported by co-occurrences in the top 500 . These strongly supported edges were always associated with loci that were ranked high in the co-occurrence list ( as indicated by node size ) . The nodes that are associated with these highly represented edges seem to form an important subgraph . To reveal these subgraphs , we removed all edges supported by less than 5% of the top 500 co-occurrences . For brevity and simplicity we only consider the gain-gain and loss-loss networks . This resulted in the two core networks shown in Figures 6 and 7 . The edge thickness of the gain-gain core network shown in Figure 6 represents the number of functional interactions found using the STRING database between genes that map within the loci described by the nodes . To determine the common denominator among the interacting genes , we employed Ingenuity Pathway Analysis ( IPA; Ingenuity Systems ) to perform a functional enrichment analysis on all genes residing within the gain-gain core network . This revealed strong enrichment for processes involved in cancer ( Figure 6b ) . From Figure 6a it is immediately apparent that most of the functional interactions are found between 1q and 7p/q . If we remove the 1q node from the entire network described in Figure 5 the enrichment for functional interaction drops dramatically ( Figure 6c ) . Therefore , we hypothesize that the co-occurring gain between 1q and 7p/q is the most important effect in the gain-gain analysis in this dataset . This is strengthened by the fact that almost all known oncogenes within the entire network map to 1q , 7p or 7q ( Figure 6a ) . The well-studied canonical oncogene MYC maps to 8q and is not a determining hub in the gene interaction network as constructed by STRING . The loss-loss core network is shown schematically in Figure 7a . A loss of approximately 18 megabases on chromosome 17p appears to be a central hub , which is co-lost with several other genomic loci . These loci show a very high enrichment of genes that interact with 17p , and of the six loci , four contain multiple known tumor suppressor genes . A functional enrichment analysis of all genes residing on loci co-lost with 17p , reveals many cancer-related processes ( Figure 7b ) , suggesting that the interacting genes are most likely also the cancer-relevant genes . If we remove 17p from the original network we see a large decrease in the percentage of genes involved in functional interactions ( Figure 7c ) confirming the importance of 17p in the loss-loss network . One of the most intensively studied cancer genes , TP53 , resides in the 17p locus . Furthermore , the canonical cancer gene RB1 and the CDKN2A/B locus are present in two of its co-lost regions . Since these are well known tumor suppressors , and therefore the subject of thousands of research papers , they might constitute the bulk of the functional relationships in our analysis . To test this hypothesis , we excluded these four genes and repeated the interaction analysis of the core network . As can be seen in Figure 7c , the enrichment is only slightly lower without the canonical genes , suggesting that the functional relationship between the co-occurring losses on 17p and the other loci are driven by other genes . We investigated the remaining 113 interactors for any interesting interactions that might be a target of this collection of co-occurring losses . Within the total network of interactors we found a sub-network centered on the nuclear co-repressor NCOR1 ( TRAC1 ) ( Figure 7d ) . This interaction network included – besides NCOR1 – the peroxisome proliferator-activated receptor alpha ( PPARA ) , the MAPK pathway suppressor GPS2 , the nuclear co-activator ( and known tumor-suppressor ) p300 and a gene of unknown function , CBFA2T3 . All interactions found are based on physical binding and co-occurrence in Pubmed abstracts . To see whether we could find more information regarding the putative tumor suppressor function of the different interactors , we tested if we could corroborate our findings with data from a large retroviral insertional mutagenesis ( IM ) screen where hematopoietic tumors were induced through Murine Leukemia virus ( MuLV ) infection of wild-type mice or Trp53 or p19-ARF deficient mice [11] . An illustration of the retroviral insertions sites near Cbfa2t3 is shown in Figure 7d . Although Cbfa2t3 was not flagged as a common integration site , several viral integrations near this gene were found . Remarkably , two individual tumors harbored a bi-allelic integration near the transcription start site of Cbfa2t3 , suggesting functional inactivation of this candidate tumor suppressor gene . Indeed , bi-allelic integration is thought to be a hallmark of tumor suppressor genes in IM screens [12] . Given that we find this sub-network of interactors in a co-occurring network of DNA copy number losses and the recovery of inactivating insertions in a retroviral IM screen , we conclude that this network might be a putative tumor suppressor network .
Several studies have investigated concerted copy number changes in aCGH data . In studies on lung cancer [13] and ovarian cancer [14] the authors performed a post-hoc co-occurrence analysis on genomic locations that were found to be significantly altered in a one-dimensional analysis . A more integrated effort to analyze relations between CNAs in brain cancer was published recently [15] . Although this study scores systematically for co-aberration , it is limited in resolution as it employs cytobands as the genomic unit within which aberrations are scored . Cytobands are relatively arbitrarily determined entities and are quite heterogeneous in size . Furthermore this approach is dependant on converting the continuous-valued copy number data to discrete copy number calls . This results in loss of important information since it removes the possibility of weighting the intensity of a CNA . In contrast , our approach is able to correct for unequal probe distances , enabling us to perform our analysis on a very high ( 20 kbp ) resolution . In addition , our scoring method not only incorporates the sign of the copy number change , but also its intensity and the concomitant CNAs within the immediate genomic neighborhood . The output of our analysis does not include a measure of significance . Constructing a background distribution based on permutations of the DNA copy number data would mean re-running our analysis thousands of times , a task which remains computationally infeasible at this stage . Furthermore , the multiple-testing problem would have to be properly addressed , given that the number of tests is the square of the number of grid points in the 2D space . Due to the complexity of the analysis procedure ( minimum operation and kernel smoothing ) the definition of an analytical null distribution has remained elusive . Therefore , we have chosen to work with top n results , residing in the extremes of the results distribution , thus minimizing the chance of including false positives . The top n lists allowed us to generate workable results which we have validated extensively with other sources of evidence . While we were able to use a distributed computing solution for our analysis , we were fortunate to have the required computational architecture at our disposal . Since the problem basically consists of repeating the same action many times it could be well-suited to software optimization or a hardware based solution where the most time-consuming actions are handled by a dedicated processing unit . When looking for areas in the 2D pair-wise space highly enriched for co-occurrence scores we convolve this space with a 2D-Gaussian kernel . The sigma parameter of this function is a representation of the size of the aberrations we expect to recover . Currently we make the implicit assumption that the co-occurring aberrations have the same size by using a symmetric kernel for the convolution . This could be relieved by allowing for an asymmetrical ( ellipsoid ) Gaussian kernel for all combinations of scales used . Clearly , this comes at the cost of increased computational complexity . Here we resolve this issue by concatenation of the results obtained in a small scale . In this way we can recover co-occurring losses of different sizes that give a better enrichment for functional interactions when combined with the single peaks obtained in a higher scale analysis . In our analysis of a set of cell lines derived from hematological malignancies we found enrichment of cancer related genes and functional interactions in co-occurring DNA copy number changes . Our results suggest that tumorigenesis requires elimination of multiple gatekeeper genes and gain of multiple oncogenes as demonstrated by the presence of many functional interactions between the loci in the gain-gain and loss-loss core networks . Haploinsufficiency is a well known characteristic of several tumor suppressor genes , where simple reduction of gene dosage by loss of gene copies at the DNA level can already promote oncogenic transformation [16] . It is conceivable that changes in gene dosage of multiple interconnected genes involved in cancer-related processes such as cell cycle , DNA repair and signaling can also weaken a cells defense against uncontrolled cell proliferation . In this case , heterozygous loss or gain of large genomic regions , such as the ones identified in this study , might effectively sensitize cells to become tumorigenic . We show that the 17p loss and its co-lost regions are highly enriched for functional relationships , which are not fully explained by the presence of the TP53 gene , often thought to be the single target of this deletion [17]–[19] . Although TP53 is no doubt an important target of the DNA copy number loss , our analysis indicates that the concomitant loss of other genes near TP53 , as well as co-occurring losses on the other genomic loci may together account for the full tumorigenic effect . Loss of the loci on 17p , 9p , 9q , 13q , 16q and 22q has been reported previously for several types of hematological malignancies represented in our dataset [20]–[23] . The picture that emerges from this analysis of collaborative aberrations is that many of the reported losses collaborate with the frequently occurring 17p loss as a central hub . We don't recover co-occurring losses among the spoke loci in the core network . This could suggest that the non-17p regions form subsets of co-occurring losses with 17p , whose interconnections themselves do not occur frequently enough in the top 500 co-occurring losses we investigated . Not all of the gene-gene interactions defined by the 17p network involve the well-known canonical cancer genes TP53 , RB1 and CDKN2A ( INK4a/ARF ) . We found one sub-network of genes around NCOR1 which might be an example of other tumor suppressor genes that are affected by the concerted loss of these genomic loci . The hub of this interaction network , NCOR1 , is a well-known transcriptional co-repressor that associates in a ligand-independent manner with nuclear receptors [24] . It is responsible , together with the closely related factor SMRT , for recruitment of HDAC proteins to the DNA to induce transcriptional silencing . Its role in cancer is not well-established . NCOR1 null mice die in early embryogenesis [25] . A dominant-negative mutant of NCOR1 is known to increase proliferation in hepatocytes [26] and more recently it has been shown that NCOR1 decreases AKT phosphorylation , thus countering its pro-survival signal [27] . It would seem that specific loss - or at least decrease in gene dosage of NCOR1 - might increase proliferation and promote survival . All interactions between NCOR1 and its partner genes ( PPARA , GPS2 and CBFA2T3 ) have been based on co-occurrence in PubMed abstract and true physical binding [28]–[31] . CBFA2T3 is a close relative of ETO , which is a target of the recurrent AML1-ETO translocation that occurs in acute myeloid leukemia . It has been shown that the fusion gene AML1-ETO actually interferes with the CBFA2T3-NCOR1 interaction , and that its oncogenic effect derives from that inhibition [31] . In a retroviral insertional mutagenesis screen in mice , Cbfa2t3 is recurrently targeted by bi-allelic retroviral integrations , which are predicted to cause functional inactivation of Cbfa2t3 [11] . PPARA is a member of the Peroxisome proliferator-activated receptors , and has been implicated in hepatocellular carcinoma development in rodents [32] . Since other members of this family , such as PPARG , exhibit a tumor suppressor-like phenotype , it is possible that PPARA can act as a tumor suppressor in hematological malignancies . GPS2 is a known suppressor of JNK signaling [33] , which is one of the constituents of the MAP kinase signaling pathway . Deregulation of this pathway is a well-known phenomenon in cancer [34] . Taken together with the association between NCOR1 and the known tumor suppressor p300 , our data suggest a selective advantage for loss of multiple constituents that interact with NCOR1 since they all may have tumor suppressor-like activities . Many studies focus on a single hematological malignancy in which a single combination of aberrations might be important [19] , [35] , [36] . Since we examine a large panel of samples derived from many different hematological malignancies , our results might not specifically apply to any single type of lymphoma or leukemia . They might hint at more general processes that are important for the tumors to arise and maintain themselves . However , one should not forget that this analysis is based on a panel of cell lines , which may have adapted to in vitro tissue culture conditions by acquiring additional aberrations that are rarely found in real tumors in patients . Furthermore , given the fact that we examine copy number changes it might be worthwhile to analyze a highly genomically unstable tumor type , such as BRCA1/2-related breast cancer . We have developed a method for genome-wide analysis of collaborating DNA copy number changes and their corresponding networks . Using this approach we have identified a loss-loss network centered around a region on human chromosome 17p . This network is highly enriched for functional relationships and hints at a more complex system of tumor suppression in which many different genes are affected simultaneously to induce cancer . We show one example of a sub-network around the nuclear co-repressor NCOR1 that may be a novel network of tumor suppressor genes that are affected by the observed co-occurring losses . The observation that DNA copy number changes may affect gene dosage of larger numbers of cancer-relevant genes deviates from the classical view where mutations in a few ( 5–7 ) cancer genes lead to tumor development . Our data support the notion of cancer-related networks or pathways , where multiple collaborating genes are deregulated simultaneously to induce oncogenesis . Such a network view of oncogenesis is an important step towards developing effective drug targets because it increases the number of potential targets . However , this view also implies that multiple molecules need to be targeted simultaneously in order to achieve optimal therapy response and to reduce the risk of therapy resistance .
Datasets consisting of array-based copy number measurements are continuously increasing in size . If probe level interactions are evaluated , the analysis space is of dimensionality for probes on the genome . As a result , the analysis time and memory usage will also increase quadratically with the number of probes . Instead of a grid positioned at the genomic positions of the probes , we employ an equally spaced genomic grid as a basis for all subsequent steps . The distance between grid-points is a user-defined variable , and will determine the finest resolution of the outcome and computational efficiency . We have performed all analyses using a genomic grid with a grid spacing of 20 Kb . Given a genome of base pairs and a grid spacing of , this results in grid positions , with , where represents the integer part of the real number , . The grid positions can be represented in the following row vector: , where . Let the aCGH profile of the tumor be represented by the following row vector of probe measurements: , with being the number probes . Let the midpositions of the probes be located at . To employ the genomic grid we need to compute , for each aCGH array , the value of the aCGH profile on the grid points . We achieve this by performing , for the grid position , , a kernel-weighted regression of all probe values situated in the range , employing a triangular kernel centered at , with maximal amplitude of 1 and width of 2 . More specifically , the interpolated copy number aberration at the grid position is given by: ( 1 ) Here the set is the set of probe positions such that . The interpolated copy number profile of the tumor is represented by the row vector: . The complete dataset of tumors is refopresented by the matrix , where the probe values of the tumor constitute the row of matrix . Negative and positive log2 values respectively denote loss or gain of DNA in the test sample versus the reference sample . We regard both situations separately , which prevents the negative and positive values cancelling each other through summation later in the algorithm . We separate gains and losses by only retaining grid positions with positive values for the gains or negative values for the losses . The absolute values of the separated matrices are then used in the downstream steps . The remaining grid positions are set to zero . More specifically , the gains matrix , is given by , with ( 2 ) Similarly , the loss matrix , is given by with ( 3 ) Because we treat gains and losses separately we have four different co-occurrence situations to be considered given two loci on the genomic grid: i ) gain/gain , ii ) gain/loss , iii ) loss/loss and iv ) loss/gain . So , when evaluating the co-occurrence of loci and , we will evaluate the behavior of i ) columns and for gain/gain; ii ) columns and for gain/loss; iii ) columns and for loss/loss and iv ) columns and for loss/gain . ( Here is the column of matrix ) . All subsequently described steps will be performed for these four situations separately , where and will be employed as shorthand for the abovementioned column vectors of interpolated copy number values associated with genomic grid positions and , respectively . The first component of the co-occurrence score is the continuous variant of the AND Boolean logic function: the minimum operation . For two grid points , and , the sum across all tumors of the minimal probe value per tumor at and , , is calculated as follows: ( 4 ) These values are aggregated in a matrix , . If we only use the minimum as a scoring function , those grid positions that are ubiquitously aberrated will always receive a high score , regardless of the aberration pattern in the other grid position . Two regions that are aberrated ubiquitously in all tumors are undoubtly important to the tumor but they are not necessarily functionally related . They might be a hallmark of the particular disease under study , but show no direct functional interaction . To prevent these ubiquitously aberrated regions from dominating the analysis and to detect those regions that represent functional co-occurrences , we weigh the minimum score computed above with the covariance of the interpolated probe values at the two grid positions and , ( 5 ) where and are the expected values of the probe values at grid position and across tumors , respectively ( i . e . and ) . These values are aggregated in a matrix , . We combine both the minimum matrix and the co-variance matrix by element-wise multiplication to form the co-occurrence score matrix , , with ( 6 ) Since we believe the co-occurrence score to be a smooth variable , and since neighboring co-occurrence values can therefore be employed to reduce the noise locally , we convolve the co-occurrence score matrix with an isotropic 2D Gaussian kernel function . In practice this implies sampling the 2D Gaussian kernel function on a square grid consisting of × genomic grid positions and then performing the convolution of this sampled kernel function with the co-occurrence score matrix . The sampled isotropic 2D Gaussian function is defined as , with ( 7 ) The standard deviation of the isotropic Gaussian , , determines the scale of the analysis . Since the Gaussian quickly decays we set , allowing contributions from , convolving with a finite kernel with minimal loss in accuracy . The scale of an analysis is therefore defined as . The scales employed in this study are: 2 Mb ( = 1/3 Mb ) , 10Mb ( = 5/3 Mb ) and 20Mb ( = 10/3 Mb ) . Before the convolution step , we pad the co-occurrence matrix by mirroring the true data at each chromosome boundary and each centromere . By convolving the appropriately padded co-occurrence score matrix and the sampled 2D Gaussian function the Convolved Co-occurrence Matrix ( CCM ) is obtained: ( 8 ) with , as the convolution operator and ( 9 ) This matrix is a representation of the amount of co-occurrence between two locations on the genome . We calculate a CCM-matrix for each possible combination of chromosome-arms and for each of the four combinations of gains and losses listed above . With 39 unique chromosome arms in the human genome ( disregarding the p-arms of the acrocentric chromosomes and the sex chromosomes ) , three different scales and 4 triangular pair-wise matrices to evaluate ( loss-loss , gain-gain , gain-loss and loss-gain ) we compute 8892 different CCMs . To solve this problem computationally we used a large distributed computing cluster . Our choice of resolution of the genomic grid was bounded by the memory present on the nodes . We set to 20000 base pairs , which is the lowest value still allowing the largest chromosome-arm pair to be successfully computed on one computing node . For each CCM we determine the top N peaks for each combination of gains and losses . The nth peak represents two co-occurring loci , and , and the location of the peak is defined by two co-ordinates on the genomic grid: . For each locus , we define a region of interest of size centered on and , respectively . We define this small region of interest to only select regions that are very near to the actual peak . To investigate the co-occurrence for functional relationships , we extract , for each of the co-occurring loci , the genes present in the regions of interest . More specifically , we define , for loci and , the associated gene sets and , where ( 10 ) and ( 11 ) Where is the position of gene , which we chose to be the mid-position of the gene . The genesets were established by a BioMart query from the Ensembl database . We restricted ourselves to the bio type ‘protein_coding’ . The list of CGC genes was obtained from the CGC website ( http://www . sanger . ac . uk/genetics/CGP/Census/ ) . The reference list of all genes was retrieved from the Ensembl website , with a filter to keep only genes with bio-type = ‘protein_coding’ . This left 18840 genes . All CGC genes that could not be mapped back to the reference gene set were excluded . The CGC genes that were annotated as ‘recessive’ were used as the tumor-suppressor genes and ‘dominant’ as oncogenes . Enrichment for all CGC genes , the tumor-suppressor subgroup and the oncogene subgroup in the gene sets determined by the co-occurrence analysis was calculated using a Fisher's exact test . The set of pairs of interacting genes which are such that one gene is associated with locus and the other gene of the pair with locus is then defined as ( 12 ) Where represents the confidence of interaction , according to the STRING database , between genes gk and gl . We then determine all gene lists of interactors for the top N peaks of a given co-occurrence analysis , i . e . : ( 13 ) For each of the top N co-occurring loci , we also determine the total number of genes in the regions of interest of those loci . So , for loci and we define the set: ( 14 ) The total number of genes associated with the top N co-occurring loci is then given by ( 15 ) The interaction ratio , , is then defined as ( 16 ) where denotes the cardinality of set . As a control we randomly pick size-matched locations for all co-occurring regions in the top N and repeat the process for recovering interactions . For 100 randomly chosen co-occurring regions we calculate the resulting . A Fisher's exact test is then used to asses the significance of enrichment of versus . For all pairs of co-occurring loci , , present in the top N of an analysis , let the set of loci representing the first and second member of the co-occurrence locus be defined asandrespectively . Given that the pairs of genomic locations corresponding to the top N co-occurring loci are given bywe define the set of genomic locations loci involved in co-occurrences asFor each possible pair of locations in the genomic distance is aggregated in matrix : ( 18 ) Where is defined as: ( 19 ) We perform hierarchical clustering on matrix using single linkage hierarchical clustering . Leaf nodes are assigned to clusters using a distance cutoff of 107 bp ( 10Mb ) . Clusters are represented as nodes in a graph . Edges between nodes are drawn if any co-occurrence relationship is found between loci present in the nodes . The case we subjected to analysis was a dataset containing 105 cell-lines derived from hematological origin . The aCGH measurements were done on 1 . 8 million probe Affymetrix SNP 6 . 0 arrays . After data pre-processing we were left with 95 samples . These cell lines are a subset of the Cancer Genome Project cancer cell line project ( http://www . sanger . ac . uk/genetics/CGP/CellLines/ ) . A list of the cell lines included in this dataset can be found in Dataset S1 . | It is generally accepted that a normal cell has to acquire multiple mutations in order to become a malignant tumor cell . Considerable effort has been invested in finding single genes involved in tumor initiation and progression , but relatively little is known about the constellations of cancer genes that effectively collaborate in oncogenesis . In this study we focus on the identification of co-occurring DNA copy number alterations ( i . e . , gains and losses of pieces of DNA ) in a series of tumor samples . We describe an analysis method to identify DNA copy number mutations that specifically occur together by examining every possible pair of positions on the genome . We analyze a dataset of hematopoietic tumor cell lines , in which we define a network of specific DNA copy number mutations . The regions in this network contain several well-studied cancer related genes . Upon further investigation we find that the regions of DNA copy number alteration also contain large networks of functionally related genes that have not previously been linked to cancer formation . This might illuminate a novel role for these recurrent DNA copy number mutations in hematopoietic malignancies . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"molecular",
"biology/bioinformatics",
"oncology/hematological",
"malignancies",
"hematology",
"computational",
"biology/genomics"
] | 2010 | Identification of Networks of Co-Occurring, Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach |
Leprosy neuropathy is considered the most common peripheral neuropathy of infectious etiology worldwide , representing a public health problem . Clinical diagnosis of primary neural leprosy ( PNL ) is challenging , since no skin lesions are found and the slit skin smear bacilloscopy is negative . However , there are still controversial concepts regarding the primary-neural versus pure-neural leprosy definition , which will be explored by using multiple clinical-laboratory analyses in this study . Seventy patients diagnosed with primary neural leprosy from 2014 to 2016 underwent clinical , laboratorial and neurophysiological evaluation . All patients presented an asymmetric neural impairment , with nerve thickening in 58 . 6% . Electroneuromyography showed a pattern of mononeuropathy in 51 . 4% . Positivity for ELISA anti-PGL1 was 52 . 9% , while the qPCR of slit skin smear was 78 . 6% . The qPCR of nerve biopsies was positive in 60 . 8% . Patients with multiple mononeuropathy patterns showed lower levels of anti-PGL-1 ( p = 0 . 0006 ) , and higher frequency of neural thickening ( p = 0 . 0008 ) and sensory symptoms ( p = 0 . 01 ) than those with mononeuropathy . PNL is not a synonym of pure neural leprosy , as this condition may include a generalized immune response and also a skin involvement , documented by molecular findings . Immunological , molecular , and neurophysiological tools must be implemented for diagnosing primary neural leprosy to achieve effective treatment and reduction of its resultant disabilities that still represent a public health problem in several developing nations . Finally , we propose a algorithm and recommendations for the diagnosis of primary neural leprosy based on the combination of the three clinical-laboratorial tools .
Leprosy is a chronic infectious disease caused by the Mycobacterium leprae , an alcohol- and acid-resistant obligatory intracellular bacillus with predilection to infect peripheral nerves and skin . Its clinical forms are defined by the host immune response and bacillary load , resulting in a wide clinical spectrum [1 , 2 , 3] . Leprosy neuropathy is considered the most common peripheral neuropathy of infectious etiology worldwide , representing a public health problem , mainly due to its incapacitating potential and strong social discrimination and stigma [4] . Leprosy is classified into five clinical forms according to the Ridley-Jopling , proposed in 1966 , which is based on skin lesion histopathology and bacterial load . According to this classification , cases with cellular immune response mediated by T lymphocytes are classified as tuberculoid ( TT ) , while anergic patients with humoral response are considered to be suffering from lepromatous leprosy ( LL ) . Patients between these two extremes are defined as borderline , presenting intermediate immune responses . For operational purposes aiming to achieve proper treatment regimens , patients are divided into paucibacillary ( PB ) or multibacillary ( MB ) forms , according to their bacilloscopic index ( BI ) , the number of skin lesions and affected nerves [5 , 6 , 7] . The M . leprae bacillus causes multiple mononeuropathy , which may result in autonomic , sensory and motor dysfunction . Histopathologically , there are myelinic and axonal dysfunctions , followed by substitution of the nervous tissue by connective tissue and fibrosis . The peripheral neural impairment includes nerve trunks as well as distal cutaneous branches . Sensory symptoms often correspond to the initial and most common complaints , always with an asymmetrical impairment . Mononeuropathy , multiple mononeuropathy and confluent mononeuropathy are the most common clinical presentations [8 , 9 , 10] . Primary neural leprosy ( PNL ) , also known as pure neural or neuritic leprosy form , was initially described by the Indian classification of 1955 [11]; since then it became a challenging clinical diagnosis . This clinical form is characterized by no skin lesions and negative slit skin smear bacilloscopy . Therefore , diagnosis is mainly based on supplementary tests , such as electroneuromyography , nerve biopsy , serology and molecular analyses [12 , 13 , 14 , 15 , 16 , 17] . However , most of the leprosy reference services do not have access to advanced diagnostic methods; therefore , diagnosis is based mainly on clinical manifestations , such as the absence of skin lesions and negative skin smears bacilloscopy . But the scarcity of symptoms at the disease onset has commonly led to diagnostic errors and under diagnosis of the neural clinical form . For this reason , several laboratory tools are required for the investigation of this neuropathy , enabling not only early diagnosis , but contributing to the prevention of incapacities [12 , 18 , 19] . Our aim was to characterize the clinical , neurophysiological , serological , and molecular patterns of patients with PNL diagnosis , which led us to propose the combination of these tools to achieve an early diagnosis and to better control the disease .
The Ethics Committee of the Federal University of Uberlandia approved the study ( CAAE: 48293215 . 7 . 0000 . 5152 ) . Written informed consent was obtained from all participants . Some participants were minors and their parents provided written consent on behalf of them . Seventy individuals with diagnosis of PNL were recruited among 317 new cases from July 2014 to July 2016 treated at the National Reference Center of Sanitary Dermatology and Leprosy ( CREDSH ) , Uberlandia , MG , Brazil . The PNL diagnosis fulfilled the following criteria: clinical evidence of peripheral neuropathy associated with the absence of skin lesions and negative slit skin smear bacilloscopy [12] . Patients who showed other possible etiologies of peripheral neuropathies during diagnosis were excluded , namely those with: chronic alcoholism , diabetes mellitus , thyroid disease and/or other hormonal dysfunctions , malnutrition , hereditary neuropathy , hepatitis B or C , HIV , rheumatic and/or autoimmune diseases . Epidemiological ( age , gender , previous contact with leprosy cases ) and clinical ( initial symptoms , sensory impairment modalities , presence of muscle weakness and amyotrophy , neural thickening , deep reflexes evaluation ) data were examined . The level of functional disability was evaluated , according to the recommended protocol of the Ministry of Health [20] , which evaluates the neural function integrity and the degree of physical disability during diagnosis , through muscle strength , and sensoriality tests of the hands and feet . In relation to the grade 2 disability caused by leprosy , observations were based on the presence of visible deficiencies , such as claws ( clawing of digits ) , bone resorption , muscular atrophy , contractures and wounds . All patients underwent a rigorous dermatoneurological evaluation by expert professionals . Slit skin smears–Slit skin smears from six sites wasperformed: the two ear lobes , bothelbows and the two knees , as well as from skin and/or nerve biopsy samples . The sample collection was preceded by topical application of cream containing lidocaine ( 7% ) and tetracaine ( 7% ) atall sites , awaiting the anesthetic effect for one hour . The vial with phosphate buffer is sterile and all collected material is immediately sent to the laboratory of molecular pathology and biotechnology . The tubes are always individually processed and compared with two negative controls to ensure that the sample is not contaminated . Bacilloscopy–Bacilloscopic analyses were performed on slit skin smears from six sites ( two ear lobes , two elbows , two knees ) , and skin and/or nerve biopsy samples . ELISA anti-PGL-1 serology–Serum IgM antibodies were detected by enzyme-linked immunosorbent assay ( ELISA ) performed against the purified native PGL-I from the Mycobacterium leprae cell wall , as described elsewhere [21] . DNA Extraction and Real Time Quantitative Polymerase Chain Reaction ( Real Time PCR ) –DNA extraction from dermal smear samples , nerve biopsies , and superjacent skin was performed . To detect M . leprae DNA , a previously described quantitative real-time PCR ( qPCR ) primer/probe assay targeting the M . leprae species-specific genomic element of dispersed repeats ( RLEP ) was performed in the real-time PCR system ABI 7300 ( Applied Biosystems , Foster City , CA , USA ) [11 , 22 , 23 , 24] . In the laboratory the vials are always individually processed and compared with two negative controls to ensure that the sample is not contaminated . Electroneuromyographic studies were performed using a MEB 4200K ( NIHON-KODHEN ) electroneuromyographer . For the sensory conduction analysis , the median , ulnar , dorsal hand cutaneous , radial , lateral antebrachial cutaneous , median antebrachial cutaneous , sural , and fibular superficial bilaterally nerves were examined . For the motor conduction analysis , the median , ulnar , common fibular , and tibial bilaterally nerves were examined , supplemented by techniques for focal impairment identification at compression sites often affected in leprosy neuropathy , such as median nerve at the wrist , ulnar nerve at the elbow , fibular nerve at the fibular head and tibial nerve at the ankle . According to the PNL concept , none of the patients presented skin lesions . For this reason , biopsies were performed on the small elbow skin fragment , which is the coldest region with a possible intradermal impairment , and a site often attacked in leprosy neuropathy , even without an evident local skin lesion . Nerves that underwent biopsy were selected according to the patient’s clinical condition , and included exclusively sensory nerves that presented sensory changes and/or thickening , and also one of the following electrophysiological changes in the sensory conduction analysis: absence of response on both sides; unilateral absence of response; bilaterally decreased amplitude of the sensory nerve action action potential ( SAP ) , considering reference values; and over 50% decrease in the amplitude of the SAP , compared with the contralateral side . During the biopsy , the nerve was isolated and completely transected . All patients signed a specific informed consent form referring to this process . During the procedure , a skin biopsy of the area superjacent to the corresponding territory of the nerve also underwent a biopsy procedure . The biopsied nerve and skin were processed and studied according to routine standard procedures . Formalin-fixed paraffin-embedded were cut longitudinally and transversely at 5 μ thickness and stained with hematoxylin and eosin stain . In addition special stains like Masson Trichome to assess fibrosis . Fite-Faraco stain was performed for bacilli identification . Continuous and dichotomous variables were applied to evaluate differences of clinical and laboratory factors among groups . The Shapiro Wilk test was applied to verify data normality prior to applying parametric or non-parametric analyses . The Wilcoxon-Mann-Whitney U Test was carried out to compare differences between independent groups when the dependent variables were not normally distributed . The Binomial Test was applied to evaluate dichotomous variables . The statistical software used was GraphPad Prism version 7 ( La Jolla , CA , USA ) , and all tests presenting a probability below 5% were considered significant .
Seventy patients diagnosed with PNL , from 2014 to 2016 , were included in this study and 44 . 3% ( 31/70 ) of these were household contacts of patients with a previous leprosy diagnosis . The average age was 42 . 9 ( ±17 . 3 ) years , and 52 . 9% ( 37/70 ) were male . Slit skin smear bacilloscopy of the six sites ( ear lobes , elbows , and knees ) was negative in all patients , who also did not present any skin lesions compatible with leprosy . Among patients , 61 . 4% ( 43/70 ) were clearly symptomatic . All assymptomatic patients ( 27/70 ) were household contacts of leprosy patients , who were annually assisted by epidemiological surveillance , throughout a 7-year period , and presented some electroneuromyographic abnormality , reinforcing the need for a detailed interview and an active search for neurological signs and symptoms in this high-risk group . All symptomatic patients presented an asymmetric neural impairment , with a predominance of sensory symptoms , particularly hypoesthesia , paresthesia and pain , evidenced by thermal , painful , and/or tactile impairment , in addition to an intradermic sensory involvement in 69 . 8% ( 30/43 ) . Deep reflexes and vibration sensation changes were present in only 8 . 6% ( 6/70 ) of the cases , while 30% ( 21/70 ) complained of muscular weakness and/or amyotrophy , besides the sensory symptoms . Neural thickening of one or more nerves was observed in 58 . 6% ( 41/70 ) of the patients , of which 75 . 6% ( 31/41 ) presented focal myelin impairments in the electroneuromyographic evaluation . As to the disability degree during diagnosis , 20% ( 14/70 ) presented grade 2 disability , mostly evidenced by the presence of muscular weakness and amyotrophy . In relation to the electroneuromyographic evaluation , an average of only 2 . 3 altered nerves per patient was observed . The most frequently affected nerves were the ulnar in the elbow segment ( 34 . 4%; 56/163 ) , common fibular in the fibula head segment ( 30 . 2%; 33/163 ) , followed by the sensory ulnar ( 12 . 8%; 20/163 ) , superficial fibular ( 10 . 4; 17/163 ) , and sural nerve ( 6 . 1%; 10/163 ) ( Table 1 ) . As to the neurophysiological pattern observed in electroneuromyography , 51 . 4% ( 36/70 ) presented only one altered nerve ( mononeuropathy ) , while 48 . 6% ( 34/70 ) presented two or more affected nerves ( asymmetrical multiple mononeuropathy ) . The electromyographic pattern and its distribution are detailed in Table 2 . The ELISA anti-PGL1 IgM serology was positive in 52 . 9% ( 37/70 ) of the cases . The qPCR test in slit skin smears was positive in 78 . 6% ( 55/70 ) of the cases , which was much higher than bacilloscopy ( negative in all cases ) . It should be emphasized that only 21 . 4% ( 15/70 ) of the neural cases showed negative qPCR in slit skin smears . In relation to the skin biopsy in the elbow area ( routine lab services in all cases with absence of suspected dermatological lesions ) , a positivity of 30% ( 21/70 ) for M leprae DNA was observed , whereas only one case ( 1 . 4% ) showed positive bacilloscopy in the biopsy of this area . According to clinical data and the electroneuromyography results , 57 . 1% ( 40/70 ) of patients demonstrated at least one eligible nerve for biopsy , but only 70% ( 28/40 ) of those were submitted to this process . The most frequent nerve submitted to biopsy was the sensory ulnar—dorsal cutaneous of the hand ( 82 . 1%; 23/28 ) , followed by superficial fibular ( 10 . 7%; 3/28 ) , sural ( 3 . 6%; 1/28 ) , and deep fibular ( 3 . 6%; 1/28 ) . Only 13 . 8% ( 4/28 ) of the nerves that underwent biopsy presented some histopathological alterations , suggestive of leprosy , such as endoneural or epineural infiltrate , presence of fibrosis , perineural thickening or presence of endoneural granuloma . Only one case ( 3 . 5% ) presented positive bacilloscopy in the peripheral nerve biopsy . On the other hand , qPCR of nerve biopsies was positive in 60 . 8% ( 17/28 ) of the cases . The qPCR of the superjacent skin area was positive in only 10 . 7% ( 3/28 ) of the nerve biopsies , with negative bacilloscopy in all samples . To achieve a better understanding of the disease phenotype and clinical progression , patients were divided into two groups: one composed of individuals presenting electroneuromyographic pattern of mononeuropathy ( 51 . 4%; 36/70 ) , and the other of those presenting a multiple mononeuropathy pattern ( 48 . 6%; 34/70 ) ( Table 3 ) . For the group of patients with multiple mononeuropathy patterns , lower levels of ELISA antiPGL-1 were observed ( p = 0 . 0006 ) , as well as higher neural thickening frequency ( p = 0 . 0008 ) , and sensory symptoms ( p = 0 . 01 ) . A higher motor symptom incidence , although not significant , was also found in this group ( p = 0 . 1440 ) , reinforcing the greater severity of neural damage . The positivity of the qPCR in slit skin smears was smaller in this group ( p = 0 . 03 ) ( Table 3 ) . Table 4 details a new analysis of the clinical and laboratory profile of two new groups of PNL patients , defined by their seropositivity to the ELISA anti-PGL1 test . The seronegative group presented a larger number of impaired nerves ( p = 0 . 003 ) , higher proportion of neural thickening ( p = 0 . 001 ) , sensory symptoms ( p<0 . 0001 ) and motor symptoms ( p = 0 . 001 ) . Lower positivity of qPCR in the peripheral blood , slit skin smear and skin biopsy were observed , reinforcing that the bacillary load in this group was lower , although not statistically different ( Table 4 ) . The combined evaluation of all diagnostic tools ( Table 5 ) demonstrated a highly variable presentation , with 17 . 1% of patients being positive only in slit skin smear qPCR and 8 . 6% being negative in all tests , reinforcing the importance of peripheral nerve biopsy in some cases .
The present study characterizes for the first time the clinical , serological , molecular , and neurophysiological aspects of 70 patients with PNL diagnosis , assisted in a leprosy national reference center in Brazil from 2014 to 2016 , evidencing the importance of using multiple analytical tools for proper diagnosis of this neuritic leprosy form . The prevalence of this clinical form was 22 . 1% , considering the 317 diagnosed cases during this period , contrasting with the very low prevalence ( 5 . 5% to 17 . 1% ) found elsewhere [12 , 13 , 14 , 16] , evidencing the difficulty in diagnosing this leprosy form . Probably , this difficulty is due to the absence of serological , molecular , and neurophysiological diagnostic tools , thus accounting for the under diagnosed of many cases , leading to the late diagnosis of this disease . In the present study , we have observed not only a high proportion of neural cases , but also a premature recognition of this clinical form , obtained by a combination of diagnostic tools and an active search of cases through the evaluation of household contacts . Interestingly , 38 . 6% of the patients were diagnosed during an epidemiological surveillance and follow-up of household contacts of leprosy patients , supporting the need for control measures and early disease recognition in this high risk population . It is estimated that household contacts of multibacillary patients may present a relative risk of developing leprosy 5 to 10 times higher than the general population [25 , 26 , 27] . The clinical presentation pattern was defined in all patients , and the asymmetric impairment of symptoms was observed in all cases . The sensory symptoms were the most dominant , and were present in all symptomatic patients , supporting previous findings demonstrated elsewhere , such as an asymmetric peripheral neuropathy that is predominantly sensorial [12 , 13 , 14 , 16 , 28 , 29 , 30] . The most affected nerves were the ulnar in the elbow segment and the common fibular nerve in the fibular head segment , followed by the ulnar sensory nerves , superficial fibular , and sural . Although controversial , most of the researchers identify the ulnar as the nerve most compromised by leprosy , although any peripheral nerve can be affected by this neuropathy . The ulnar , median , common fibular , tibial , facial , cutaneous radial , and major auricular are the nerves most frequently reported in different studies [12 , 13 , 15 , 29 , 31 , 32] . This variability may be due to the different electroneuromyography protocols used , emphasizing the importance of an extensive and careful evaluation of leprosy neuropathy , mostly through an extended analysis of motor and sensory conductions , including nerves that are not evaluated in the routine . The deep sensation and deep tendon reflex impairment , as well as the presence of muscular weakness and amyotrophy , generally occur in cases of prolonged evolution . In this study , motor impairment was more frequent in ulnar and fibular nerves . Apparently , the bacillus’s preference for colder areas of the body will lead to a focal reduction of the conduction velocity , which can be detected at some preferential sites , such as the ulnar nerve in the elbow area and the common fibular nerve in the fibula head area [13 , 16 , 33 , 34] Neural thickening was present in the majority of the cases . However , the clinical evaluation of neural thickening is subjective , especially for professionals with limited experience , which may explain the very large data variation found among different examiners [35 , 36] . Besides that , the neural thickening is not a pathognomonic finding of leprosy neuropathy , which can be observed in compressive , inflammatory focal neuropathy , and even in hereditary neuropathies [13 , 14] . It should be emphasized that thickened nerves can also present a normal electroneuromyographic result [37] , as observed in some of our patients . The electroneuromyography of leprosy patients is very important , because it allows the stratification of the severity , the definition of patterns of the peripheral neural impairment , and also the early detection of PNL . These findings were reinforced by the large percentage of household contacts detected with this neuritic leprosy form , classified as oligo/asymptomatic patients , who do not always present neural thickening or other signs of this neuropathy . In leprosy neuropathy , some patients seems to present a subclinical form , in which the sensory conduction study is superior to thermal sensation , vibratory , strength , and monofilament tests , with capability of detecting neural impairment in earlier phases [32 , 36] . Detection of patients with high disability level ( grade 2 ) during diagnosis reinforces the complexity of these cases , leading to treatment delays in a clinical form whose neural damage is much more aggressive than the damage observed in other forms of the disease . The absence or amplitude reduction of the sensorial action potential of ulnar nerves in leprosy patients can precede the disease’s classic clinical symptoms [38] , which is corroborated by our electroneuromyography findings in oligosymptomatic patients , reinforcing the fact that the sensory ulnar nerve is the most biopsied nerve . Besides that , an early focal myelinic impairment of ulnar or fibular nerves was observed , also preceding the clinical manifestations of the disease [39] . However , there are doubts as to the electrophysiological changes most frequently found in this peripheral neuropathy , which reflects a disease with differential phenotypes that can evolve insidiously or through reactional episodes , accentuating neural damage and leading to functional disabilities and sequelae [40] . In relation to diagnostic tools , the diagnostic tests used for leprosy pursue direct demonstration of bacilli through biopsy and bacilloscopy , or indirect detection through serological or molecular analyses . These methods differ in sensitivity , specificity , reproducibility , and do not present a homogeneous response across leprosy forms; therefore , it is reasonable to investigate and adopt new methods to elucidate the neural forms [2] . The positivity of ELISA anti-PGLI during diagnosis in most cases emphasizes its importance as screening and as a risk indicator , particularly for oligo/asymptomatic patients . The anti-PGL-I seropositivity indicates that the bacillus has successfully penetrated the circulatory system , and represents a relative risk almost six times higher for disease occurrence , corroborating the leprosy neuropathy diagnosis . Nevertheless , the number of seropositive patients does not indicate existing infection prevalence , which reached 47 . 1% of our cases , since paucibacillary patients rarely produce specific antibodies [11 , 17 , 26 , 27 , 41] . The use of the polymerase chain reaction ( PCR ) to detect M . leprae DNA has been reported as a useful diagnostic tool for all clinical forms of leprosy , including the primary neural form , and is considered an important tool for early diagnosis [18 , 42 , 43] . Our study demonstrated a 78 . 6% positivity of M . leprae DNA in the slit skin smears , although all these patients were diagnosed with leprosy in their primary neural form , considering the current diagnostic criteria , which only require negativity in slit skin smear bacilloscopy . Therefore , it is important to emphasize that the concept of a pure neural form cannot be accepted , although it is often used as a synonym of the primary neural form , since only 21 . 4% of our cases presented a clinical and laboratory presentation that supports a uniquely neural involvement . In addition , clinical leprosy often starts from neurological symptoms instead of skin disease , and skin lesions may appear later [44] . The qPCR of peripheral nerves was positive in 60 . 8% , which has signficantly contributed to the leprosy diagnosis . There is a great variation in the literature related to the bacillus identification and to the histopathological analysis in peripheral nerve biopsy through conventional bacilloscopy , reinforcing the importance of qPCR use in these cases due to its greater sensitivity [16 , 18 , 45 , 46] . According to current recommendations for the operational classification of leprosy patients , which defines the multidrug therapy regimens , those cases with primary neural form that present more than one affected nerve , properly documented by loss or reduction of sensation in the respective areas , should be treated as a multibacillary form [20] . However , as observed in this study , many mononeuropathy patients presented high titers of anti-PGL-1 serology , which implies the patients’ bacillary load status and defines them as multibacillary cases with predominance of humoral immune response , considered a less aggressive disease , and also an early diagnosis , since other leprosy clinical signs were not present during diagnosis . If one considers only the number of affected nerves , treatment failures may occur , including disease relapse due to insufficient treatment . Contrarily , lower anti-PGL-1 serology levels , characterizing the paucibacillary form , were observed in the multiple mononeuropathy patient group , suggesting a stronger cellular response and corroborating the greater immune aggression of nerves , which is evidenced by the greater severity of the peripheral neuropathy , with greater number of altered nerves , higher proportion of sensory-motor symptoms , and thickened nerves . Thus , diagnosis of both clinical and operational classifications of patients with the primary neural form still represents a big challenge . Due to their hazardous and highly disabling neuropathy , we believe that all PNL cases should be treated with multibacillary treatment regimen , especially because of the lack of clear diagnostic criteria to distinguish paucibacillary from multibacillary patients , and also on account of the lack of association between the number of altered nerves and the bacillary load . Early diagnosis of suspected leprosy neuropathy cases has been always posed a problem due to the long incubation period of the disease , the variable and insidious symptoms and clinical signs in both early and advanced cases , a context that reinforces the notion that PNL is underdiagnosed , causing severe disabilities and favoring the maintenance of the infection transmission chain . We propose an algorithm for PNL diagnosis ( Fig 1 ) considering that for early recognition of the leprosy neural form , a severe public health problem in several developing countries and regions , the implementation of specific methods is an urgent requirement , including immunological , molecular and neurophysiological tools , which are necessary to elucidate the epidemiology of this disabling clinical form , thus contributing not only to an effective treatment , but also to the reduction of disabilities , deformities , and sequelae . | The long incubation period , insidious symptoms and signs of leprosy produce difficulties in its diagnosis and correct clinical classification , especially in its primary neural form characterized by negative bacilloscopy and lack of cutaneous lesions . Despite significant progress in leprosy control in recent years , early identification of cases remains one of the primary goals of leprosy control programs . In addition , the failure of current therapeutic schemes on the incidence of leprosy shows that elimination of this disease , a public health problem , depends on incisive action to interrupt its transmission chain . Therefore , efforts must be focused on improving the leprosy diagnosis . However , because it is a primarily neural disease , the use of neurophysiological , serological and molecular methods in this group of patients may contribute not only to early diagnosis , but also to a correct classification and treatment , preventing sequelae and controlling outbreaks of infection . Therefore , in order to improve the leprosy elimination program in many countries , we propose the implementation of a combination of specific tools for detecting M . leprae and its neural impairment , which may further break down the transmission chain , enabling a more effective control of the disease . | [
"Abstract",
"Introduction",
"Patients",
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"methods",
"Results",
"Discussion"
] | [
"medicine",
"and",
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"peripheral",
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"neurology",
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] | 2017 | Revisiting primary neural leprosy: Clinical, serological, molecular, and neurophysiological aspects |
Undifferentiated febrile illness ( UFI ) is one of the most common reasons for people seeking healthcare in low-income countries . While illness and death due to specific infections such as malaria are often well-quantified , others are frequently uncounted and their impact underappreciated . A number of high consequence infectious diseases , including Ebola virus , are endemic or epidemic in the Federal Republic of Sudan which has experienced at least 12 UFI outbreaks , frequently associated with haemorrhage and high case fatality rates ( CFR ) , since 2012 . One of these occurred in Darfur in 2015/2016 with 594 cases and 108 deaths ( CFR 18 . 2% ) . The aetiology of these outbreaks remains unknown . We report a retrospective cohort study of the 2015/2016 Darfur outbreak , using a subset of 65 of 263 outbreak samples received by the National Public Health Laboratory which met selection criteria of sufficient sample volume and epidemiological data . Clinical features included fever ( 95 . 8% ) , bleeding ( 95 . 7% ) , headache ( 51 . 6% ) and arthralgia ( 42 . 2% ) . No epidemiological patterns indicative of person-to-person transmission or health-worker cases were reported . Samples were tested at the Public Health England Rare and Imported Pathogens Laboratory using a bespoke panel of likely pathogens including haemorrhagic fever viruses , arboviruses and Rickettsia , Leptospira and Borrelia spp . Seven ( 11% ) were positive for Crimean-Congo haemorrhagic fever virus ( CCHFV ) by real-time reverse transcription PCR . The remaining samples tested negative on all assays . CCHFV is an important cause of fever and haemorrhage in Darfur , but not the sole major source of UFI outbreaks in Sudan . Prospective studies are needed to explore other aetiologies , including novel pathogens . The presence of CCHFV has critical infection , prevention and control as well as clinical implications for future response . Our study reinforces the need to boost surveillance , lab and investigative capacity to underpin effective response , and for local and international health security .
Undifferentiated febrile illness ( UFI ) is one of the most common reasons for people seeking healthcare in many low-income countries . [1] While illness and death due to some specific infections such as malaria are often well-quantified , others which can be caused by a wide range of pathogens , are frequently uncounted and their impact therefore underestimated . [2 , 3] At least 12 outbreaks of undifferentiated febrile illness have been reported in the Federal Republic of Sudan since 2012 , frequently associated with haemorrhage and high case fatality rates , including a cluster in the Darfur region of Sudan in 2015/2016 which resulted in 594 cases and 108 deaths over 27 localities ( Table 1 ) . The aetiology of these outbreaks remains unknown . A range of high consequence infectious diseases ( HCID ) are endemic or epidemic in Sudan including Ebola virus , which was identified contemporaneously in Sudan and the Democratic Republic of Congo in 1976 . [19 , 20] The National Public Health Laboratory ( NPHL ) of Sudan intermittently identifies viral haemorrhagic fever ( VHF ) cases including Rift Valley fever ( RVF ) and Crimean-Congo haemorrhagic fever ( CCHF ) . Sudan is also at high risk of yellow fever virus ( YFV ) epidemics , the most recent outbreak occurring in 2012/13 . [21] Outbreaks of dengue fever and chikungunya are common , and cases of West Nile fever have been recorded . ( Table A in S1 Text ) . There have also been outbreaks of undiagnosed fever with haemorrhagic symptoms in South Sudan , most recently in Aweil State in 2016 , and of RVF in Eastern Lakes State in 2018 . Outbreak investigation in Sudan is the responsibility of the ministries of health of the 18 states , reinforced by the Federal Ministry of Health ( FMoH ) when cases appear to increase significantly or exhibit characteristics of HCID and/or person-to-person transmission . Alerts are received through 1659 sentinel sites ( 27% of all health facilities ) which transmit reports weekly or daily depending on the disease . In past outbreaks , epidemiological data have often been incomplete and laboratory analysis delayed due to the limited capacity of state-level laboratories which necessitates transfer of samples for analysis to the NPHL in Khartoum . Rapid Response Teams comprising epidemiology , laboratory and clinical staff have been established in each State and at Federal level to improve the speed and depth of outbreak investigation . The Darfur outbreak , reported to FMoH on September 21 , 2015 and eventually affecting all 5 states in the Darfur region , was initially thought to result from severe dengue complicated by malaria and other underlying conditions such as sickle cell disease commonly found among some tribes in Darfur . [22] However , only 24% of the suspect case samples received and tested by NPHL showed evidence of dengue virus ( DENV ) IgM antibodies , and no samples were positive by PCR . Samples tested for viral haemorrhagic fevers at the WHO collaborating laboratory in Dakar , Senegal and the Robert Koch Institute in Berlin were also all negative . Limited in their capacity to test further due to restrictions on reagent importation , the NPHL tested a small number of samples ( 30 ) in-house for CCHFV and found 7 were PCR positive , all from East Darfur . A further 7 samples were found to have serological evidence of West Nile fever virus but as neutralisation tests were not available , a cross-reaction could not be ruled out . Over the next 9 months , 594 cases were reported using the outbreak case definition ( Fig 1 ) across 27 localities of Darfur , the majority coming from West Darfur and focused on Kereinik , followed by Al Sareef in North Darfur , and Zalingei in Central Darfur–areas which hosted substantial numbers of displaced people . Cases peaked in November 2015 and dropped to sporadic cases from February until the announced end of the outbreak in May 2016 . ( Fig 2 ) Since then , at least 3 smaller outbreaks of a similar syndrome have occurred in different locations in Sudan . The unknown source ( s ) and ill-defined characteristics of these outbreaks are of significant concern . To try to identify the outbreak pathogen ( s ) , better characterise the outbreak syndrome , inform public health and treatment interventions , and assist development of diagnostic capacity , we investigated a set of stored samples from the outbreak with a bespoke panel of molecular and serological assays and epidemiological analysis .
Approval for the study was granted by the FMoH Technical Review Board , and the Ethics Committees of Karary University , Khartoum and the London School of Hygiene & Tropical Medicine ( Ref: 11930 ) . Individual consent was not required as samples were collected for diagnostic purposes during the public health response to the outbreak . Permission to export samples to the UK was given by the FMoH and samples and data were anonymised before transfer . The NPHL received blood samples from 263 of the 594 cases notified during the outbreak , from which serum was stored . After matching data held by the FMoH Epidemiology Unit with samples and data stored at the NPHL , we evaluated samples for inclusion in the study using the following criteria: sufficient sample volume to accommodate multiple tests ( >300 μl ) ; sufficient epidemiological data to allow minimum characterisation of the case; specimen not previously tested by an external laboratory , and not previously tested positive for CCHFV in NPHL . Sixty-five ( 65 ) of the 263 stored samples met the criteria and were transported as frozen serum to the Rare and Imported Pathogens Laboratory ( RIPL ) , Porton , UK where assays covering a broad range of likely pathogens were performed ( Fig 3 ) . As sample volume was limited , PCR assays were chosen based on clinical syndrome and geographical location and included haemorrhagic fever viruses , arboviruses , arenaviruses , leptospirosis and rickettsiae . Samples that did not meet the criteria ( 198 ) were not transferred and remained stored in NPHL . Sensitivity analysis was performed to assess if the samples transferred to the UK were representative of the samples that remained in Sudan . Detailed information on the design and conditions for each assay is available in the Technical Appendix: Laboratory and Metagenomic Materials and Methods in Supporting Information ( S1 Text )
Sixty-five ( 24 . 7% ) of the samples met the criteria for transfer for testing at RIPL . These were largely representative of the total cases sampled . There were no significant demographic differences , nor differences in the time from symptom onset to sample-taking , in the assays used by NPHL on the sample during the outbreak , or in their results or case outcome ( Table 2 ) . However , the transferred samples were associated with significantly less fever ( p <0 . 001 ) and more bloody diarrhoea ( p = 0 . 02 ) than those not transferred . It must be noted that , although a case definition was established during the outbreak , not all notified cases corresponded to it when analysed . Case fatality was similar in both transferred and non-transferred samples ( 6 . 4% , 3/47 and 8 . 2% , 16/196 respectively , p = 1 . 0 ) , but outcome data were missing in 18/65 cases in transferred group ( 27 . 7% ) and 2/198 in non-transferred samples ( 1 . 01% ) . Only 8 cases overall–none of which were among the transferred samples–reported any animal contact , but over 75% of data for this variable were missing . No other exposure variables were routinely reported , though early investigators reported seeing no epidemiological patterns , such as family clusters or healthcare worker infections , that might indicate person-to-person transmission . Of the 15 tests performed on the 65 samples transferred to RIPL ( Fig 3 & S1 Text ) , only the RT-PCR and ELISA for CCHFV produced positive results . Seven ( 11% ) samples were positive on both RT-PCR and IgG ELISA , including 2 samples which had previously tested negative for CCHFV at NPHL . Cycle thresholds ranged from 23 . 90 to 36 . 02 . Six of the 7 were also ELISA IgM positive . An additional 4 samples were RT-PCR and IgM-negative but positive for CCHFV IgG antibodies . All other samples tested negative on all assays . No significant results were initially obtained through the metagenomic sequencing of either the CCHFV positive or negative samples due to inadequate RNA quality after storage and PCR work . However , when fresh nucleic acid extracts were made from primary samples for the CCHFV positive samples , sequencing on an Illumina MiSeq was successful , and confirmed that sequence reads identifiable as CCHFV were present in all 7 samples . Genome coverage varied widely between the samples ( 0–99 . 5% for the S segment , 0–96 . 5% for the M and 5 . 5–98 . 5% for the L , at 5x minimum depth ) but produced adequate information to characterise the virus . Phylogenetic analysis of the near-complete S-segment of the sample with the highest quality information ( S segment: 99 . 5%; M segment: 96 . 5%; L segment: 98 . 5% ) , dated 18 October in Table 3: male , 5 years , Ct 23 . 9 ) , placed it within the Africa 3 S Segment clade , and showed close homology to the 2009 Sudan strain ( HQ378179 . 1 ) . ( Genbank accession nos . S Segment: MK442893; M Segment: MK442894; L Segment: MK442895 ) . See Fig 4 and S1 Text for further details . Serological assays performed by NPHL during the outbreak on some of the study samples identified evidence of dengue antibodies in 23 . 2% ( 13 of 56 tested samples ) , chikungunya virus ( 1/65 ) , hepatitis E virus ( 1/7 ) and West Nile virus ( 1/1 ) . None of these infections were detected in RIPL testing . The only potential for co-infection seen was malaria . Clinical records at the time reported that 62 . 9% of the samples transferred to the UK were malaria-positive , including three of the cases subsequently shown to be positive for CCHF . Malaria testing was not repeated in RIPL . All 7 CCHFV RT-PCR positive/IgM positive cases were males aged 21 to 30 years , except for a 5-year-old boy who was also the only reported death in the group ( CFR 20 . 0% of the 5 cases with reported outcome ) ( Table 3 ) . The fatality was one of three CCHFV cases reported to be coinfected with malaria . Four of the positive cases were farmers and 2 were of unknown occupation . Three came from East Darfur , 2 from North Darfur and 1 each from South and Central Darfur . Of the 4 cases who were only CCHFV IgG positive , 1 came from each of North , South and East Darfur and the origin of the 4th was unknown . Two of the 4 worked in animal husbandry . Acute CCHFV positive cases were similar to CCHFV negative cases in most characteristics and symptoms , including the time from symptom onset to admission to a health facility and to sample-taking . The only significant associations with acute CCHFV positivity were male sex ( p 0 . 02 ) and origin in the state of East Darfur ( p 0 . 002 ) . The association with location was reinforced when RIPL-identified CCHFV positive cases were added to those identified during the outbreak by NPHL: when combined , 23% of all samples originating from East Darfur during the outbreak ( 9/40 ) were CCHFV positive and occurred during a 9-week period ( September 28 , 2015—January 12 , 2016 ) . NPHL-identified CCHFV positives originated from 2 main localities in East Darfur: RIPL-identified positives occurred in similar areas . Unfortunately , epidemiological data are not complete enough to investigate possible transmission links . CCHFV positive cases were less likely to report rectal bleeding than CCHFV negative cases ( p 0 . 04 ) but half the CCHFV positive cases had missing data for this symptom .
Comprehensive diagnostic evaluation of this set of historical samples has demonstrated that CCHFV was one important cause , but not the only aetiology , of the large outbreak of undifferentiated febrile illness with haemorrhagic symptoms in Darfur in the 2015–2016 . This fact that CCHFV was not the main cause is reinforced by the absence of CCHFV-positive samples from West Darfur , the state reporting the majority of cases in the outbreak . The substantial proportion of CCHFV-positive samples from East Darfur might suggest that the virus played a stronger role in the outbreak there , or that it simply represents background transmission in an endemic area . The 4 cases who were only CCHFV IgG positive most likely represent previous CCHFV exposure . It is also important to note that we found no evidence of DENV infection despite several previous outbreaks in the area having been attributed to this pathogen . CCHFV-specific antibodies have been found in 19 . 1% of cattle in East Darfur and 21 . 3% of camels in Khartoum State , as well as in camels , sheep and goats exported from Sudan . [24 , 25] The first human cases of CCHFV in Sudan were confirmed during an outbreak of haemorrhagic fever among healthcare workers in Al Fulah Rural Hospital , Western Kordofan in 2008 with a CFR of 69 . 2% . [26] Since then , an average of 12 cases of human CCHFV have been confirmed by NPHL per year and multiple strains have been identified . [27] However , the persistent lack of laboratory capacity and supply at central level and complete absence of testing at district level mean that cases are likely to be under-reported . The CFR of 20 . 0% among the CCHFV positive cases identified in this outbreak is at the lower end of the reported range for comparable resource-limited treatment settings . It is lower than might be expected given the severity of the reported illness[28 , 29] , but similar to mortality in highly endemic regions such as Kazakhstan and Tajikistan . [30] One explanation may be that the severely ill and dead were less likely to be sampled , a possibility supported by the much higher mortality among outbreak cases reported but not sampled ( 24 . 1% ) . The only fatal case identified was in a 5year-old child with haemorrhage , and reportedly coinfected with malaria , who was admitted two days after onset of symptoms , who tested negative by PCR at the NPHL but subsequently positive by PCR and sequencing at RIPL and died 3 days after admission . While fatal outcome of CCHF in children is thought to be rare it has been reported from a range of settings . [31–33] An explanation for the finding of positive CCHFV results in two samples previously tested ‘negative’ at NPHL could be that CT values were borderline , but unfortunately documentation at that time only reported results as negative or positive . It is also possible that the assays used ( Altona real time PCR and Euroimmune ELISA ) could have been at the limit of their validity as NPHL have had great difficulty in maintaining reagent supply and conditions during the embargo in Sudan and with frequent power cuts and equipment failure . The importance of livestock to the Sudanese economy and the risks that CCHFV presents to healthcare workers and other patients[34] , especially in resource-limited healthcare facilities , highlight the urgent need for improved surveillance and faster , more accessible CCHFV laboratory diagnosis . But while our comprehensive testing clearly highlights the risks and response requirements for CCHFV and has underlined some important negative results which excluded other HCIDs and VHFs , it has not solved the conundrum of what caused the majority of cases . The absence of a diagnosis for the majority of these historical specimens may result from compromised sample integrity in transportation from the field to the NPHL , or during the storage period ( 18–24 months ) between sample collection and final laboratory analysis . While the NPHL’s receipt of samples for almost 50% of reported cases is remarkable given the challenges in surveillance and outbreak response in these low-resourced and remote settings , the inherent delays and difficulties with cold chain take their toll on sample condition . It is also possible that delayed presentation to health facilities could have led to sampling later in the disease course when opportunity to identify pathogens by PCR is reduced . A further factor difficult to assess is the impact of genetic variation and primer and/or probe mismatches during the PCR testing which may have affected opportunity for positive findings . The extent of our laboratory work and our sample size was also limited by the relatively small amounts of stored sample available . This combined with the absence of convalescent samples precluded more detailed serological analysis . Increasing the capacity to investigate samples on site through the development of innovative near-patient diagnostic platforms—a priority in the WHO R &D Blueprint for Action to Prevent Epidemics[35]—and/or improving storage and transfer of samples to the reference laboratory , will be key to rapid identification of pathogens in future outbreaks . Additional diagnostic capacity achieved by increasing the range of assays available in the NPHL , collecting a broader range of field samples ( e . g . urine , naso-oropharangeal and stool samples as well as convalescent samples ) and a developing a sequencing capability , will also increase diagnostic yield . Our interpretation of the syndrome characteristics was limited by missing epidemiological data . The absence of full case investigation forms ( CIF ) for 19 of the 65 investigated samples restricted characterisation of symptoms , occupation and outcomes . Exposures and contact information were also rarely recorded–an important oversight for outbreak control–and similar or greater gaps in data were found in the information of the un-transferred cases . Using a more detailed CIF in future outbreaks , ideally in electronic format to speed interpretation , and reinforcing the importance of face-to-face interviews with patients , family and community will help the capture of important data . To assist investigation of future outbreaks , the UK Public Health Rapid Support Team/FMoH research collaboration has put in place an ethics-approved prospective study protocol and trained a study team comprising FMoH , NPHL and University staff ready to deploy . In conclusion , Sudan is a large country at the crossroads of Africa and the Middle East that has experienced several outbreaks of HCIDs and regularly has outbreaks of zoonotic infections . We have shown the presence of CCHFV as an important cause of fever and haemorrhage in Darfur which has critical infection prevention and control as well as clinical implications for future care and response . To fulfil its global obligations under the International Health Regulations ( 2005 ) , the FMoH needs to maintain and develop robust surveillance , response and laboratory capacity . Support in these areas , and for well-developed prospective fever studies , could dramatically improve understanding of circulating pathogens in Sudan and facilitate the rapid recognition and investigation of the next outbreak . | The Federal Republic of Sudan has had at least 12 outbreaks of febrile illness of unknown cause associated with symptoms of haemorrhage and high case fatality rates since 2012 . Outbreaks without clear diagnosis are concerning , particularly in countries such as Sudan where a range of high consequence diseases , including viral haemorrhagic fevers , are endemic or epidemic , and local laboratory capacity is limited . We transferred historical samples stored in the National Public Health Authority from one of these outbreaks that occurred in Darfur 2015–2016 to the Public Health England Laboratory at Porton , UK , and tested them against a wide range of infectious diseases to try to identify the cause , and to help the Sudanese Federal Ministry of Health to develop and target their limited laboratory capacity . We found that Crimean-Congo Haemorrhagic Fever was an important cause but not the only source of cases in this outbreak . This has implications for prevention and control as well as for treating cases . Our study also highlighted the need for future studies to explore other possible causes , including new pathogens , and reinforced the need to boost surveillance , lab and investigative capacity for more timely and complete outbreak response . | [
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] | 2019 | Detection of Crimean-Congo Haemorrhagic Fever cases in a severe undifferentiated febrile illness outbreak in the Federal Republic of Sudan: A retrospective epidemiological and diagnostic cohort study |
Lutzomyia longipalpis is the South American vector of Leishmania infantum , the etiologic agent of visceral leishmaniasis ( VL ) . Male L . longipalpis produce a sex-aggregation pheromone that is critical in mating , yet very little is known about its accumulation over time or factors involved in release . This laboratory study aimed to compare accumulation of pheromone over time and determine factors that might influence release in three members of the L . longipalpis species complex . We investigated male sex-aggregation pheromone gland content at different ages and the release rate of pheromone in the presence or absence of females under different light conditions by gas chromatography-mass spectrometry ( GC-MS ) . Pheromone gland content was determined by extraction of whole males and pheromone release rate was determined by collection of headspace volatiles . Pheromone gland content appeared age-related and pheromone began to accumulate between 6 to 12 h post eclosion and gradually increased until males were 7–9 days old . The greatest amount was detected in 9-day old Campo Grande males ( ( S ) -9-methylgermacrene-B; X ± SE: 203 . 5 ± 57 . 4 ng/male ) followed by Sobral 2S males ( diterpene; 199 . 9 ± 34 . 3 ) and Jacobina males ( ( 1S , 3S , 7R ) -3-methyl-α-himachalene; 128 . 8 ± 30 . 3 ) at 7 days old . Pheromone release was not continuous over time . During a 4-hour period , the greatest quantities of pheromone were released during the first hour , when wing beating activity was most intense . It was then substantially diminished for the remainder of the time . During a 24 h period , 4–5 day old male sand flies released approximately 63 ± 11% of the pheromone content of their glands , depending on the chemotype . The presence of females significantly increased pheromone release rate . The light regime under which the sand flies were held had little influence on pheromone release except on Sobral 2S chemotype . Accumulation of pheromone appears to occur at different rates in the different chemotypes examined and results in differing amounts being present in glands over time . Release of accumulated pheromone is not passive , but depends on biotic ( presence of females ) and abiotic ( light ) circumstances . There are marked differences in content and release between the members of the complex suggesting important behavioural , biosynthetic and ecological differences between them .
There are over 800 known phlebotomine sand fly species , but only approximately 56 Lutzomyia and Phlebotomus species are proven or suspected vectors of human leishmaniasis [1] . Among them , L . longipalpis is the primary vector of Leishmania infantum , the etiological agent of visceral leishmaniasis ( VL ) in the Americas [2] . The presence of L . longipalpis has been recorded in 12 countries , including Argentina , Bolivia , Colombia , Costa Rica , El Salvador , Guatemala , Honduras , Mexico , Nicaragua , Paraguay , and Venezuela . It is also widely distributed throughout Brazil [1] . During the last two decades it has colonised urban environments and expanded its geographical range , which has resulted in an increase in the number of cases of canine and human VL [3 , 4] . The taxonomic status of L . longipalpis has been uncertain since it was first described by Mangabeira in 1969 [5] and recent analysis of molecular and genetic markers [6] , morphological features [7] , copulation songs [8] , and chemical communication [9] all indicate that L . longipalpis is a complex of recently evolved cryptic species [10] . However , there is no consensus on the number of species in the complex or their geographic distributions [7 , 11 , 12] . In many Dipteran species , sex pheromones , together with visual , tactile and acoustic signals , play an important role in courtship behaviour [13] . Sex-aggregation pheromones occur in male L . longipalpis [9 , 14] and may be widespread in the genus Lutzomyia . There is chemical evidence that they also occur in L . cruzi [15] , L . pseudolongipalpis [16] , L . pessoai [17] , L . lichyi [18] , L . lenti , L . carmelinoi [19] and L . cruciata [20] . They have also been found in the closely related genus Sergentomyia , e . g . S . minuta and S . fallax [21] . These species produce volatile terpenoid compounds that are structurally similar to the sex-aggregation pheromones of the L . longipalpis species complex . Based on behavioural experiments , there is some evidence that pheromones may also play a role in the mating of Phlebotomus papatasi [22] , the main vector of the Old World cutaneous leishmaniasis [1] . In the L . longipalpis species complex the sex-aggregation pheromones have been studied for both their taxonomic value and to exploit their vector control potential [23] . Analysis of the main terpene component of the sex-aggregation pheromone gland extract has shown that there are at least four distinct chemotypes of L . longipalpis [9 , 24]: i ) ( 1S , 3S , 7R ) -3-methyl-α-himachalene ( 3MαH ) , a novel bicyclic methylsesquiterpene with a 16 carbon skeleton ( C16 , molecular weight ( mw ) : 218 ) . In Brazil , this chemotype has been found only in Bahia State; ii ) ( S ) -9-methylgermacrene-B ( 9MGB ) , a novel monocyclic methylsesquiterpene ( C16 , mw: 218 ) . It is also the most widespread chemotype in the Americas , and is found in Argentina , Colombia , Paraguay , Venezuela , Honduras , Costa Rica and Brazil . This chemotype is common in Brazil , particularly in the centre , south and to a lesser extent , in the northeast of the country; iii ) a partially characterised diterpene ( C20 , mw: 272 ) is the second most widely distributed chemotype in Brazil [25] . It is mainly found in the northeastern states although recent reports indicate that it is present in the southeast [4]; iv ) a related partially characterised diterpene has also been found only in specimens from Jaíba , Minas Gerais State , Brazil [25] . A racemic version ( containing both the R and S isomers ) of the 9-methylgermacrene-B sex pheromone has been synthesised in bulk , shown to be active in the field and formulated for long-term controlled release [23] . It is currently being evaluated for its potential to reduce the risk of canine VL infection in a lure-and-kill vector control tool and for enhanced monitoring . Optimising the controlled release formulation of the synthetic pheromone for both of these functions relies on knowledge of how pheromone is produced and released by individuals and groups of males under different conditions . The sex-aggregation pheromone is synthesised and stored in glandular tissue underlying the abdominal tergites and is transported via cuticular ducts to modified structures , “papules” , on the cuticle surface [19 , 26] . Pheromone glands in young , 0–6 h old , males are undifferentiated but appear to be fully differentiated in 4-day old males [27] . Pheromone production is currently believed to start after 12 h and increase continuously for 3 days when it reaches a plateau [28] . No studies have been undertaken to determine if differences in pheromone gland content occur between different members of the species complex nor to determine which factors , if any , might contribute to subsequent pheromone release . It has been suggested that wing-fanning , which occurs in males during courtship , may help to distribute pheromone [29–32] and it has also been suggested that frequent mating attempts during courtship might increase pheromone release but deplete glandular pheromone reserves [29] . Males with depleted gland contents are less successful at obtaining mating attempts than males with fuller glands [29] . In this study , we have investigated the accumulation of pheromone and the dynamics of release for each of three members of the L . longipalpis species complex . Specifically , we addressed the following questions: a ) do males of different chemotypes have the same total amount of pheromone ( gland content ) over time ? b ) how much pheromone is released from the glands into the atmosphere ? c ) is pheromone release affected by the presence of conspecific females ? and d ) do light conditions have an effect on pheromone release ?
All three colonies ( chemotypes ) of L . longipalpis used in this study were originally established from females collected using miniature CDC light traps in chicken shelters . The Jacobina ( 3MαH ) , and Campo Grande ( 9MGB ) colonies were established from groups of females collected in Jacobina , Bahia State , ( 11° 11' S , 40° 31' W ) and Campo Grande , Mato Grosso do Sul State ( 20° 28’ S , 54° 37’ W ) . The Sobral 2S ( diterpene ) colony was established from Sobral , Ceará State ( 3° 41’ S , 40° 20’ W ) . The Jacobina colony was originally established in 1974 [33] ( estimated 380th generation ) . The Campo Grande colony was established in 2009 ( estimated 63rd generation ) and the Sobral 2S colony was established in 2013 ( estimated 27th generation ) . Previously , chromatographic analysis of the pheromone gland contents of individual males from both Jacobina and Campo Grande colonies established that both were allopatric and contained representatives of only one chemotype [17 , 23] . In Sobral the diterpene and 9MGB chemotypes are sympatric . The diterpene chemotype males can be distinguished from the 9MGB males by the number of pale patches on the abdomen . The diterpene chemotype males have two patches ( 2S ) , whereas the 9MGB chemotype males have only 1 ( 1S ) . Using careful iso-female rearing [34] we were able to establish a diterpene producing colony . Evidence collected from the Sobral field site indicates that the 2 chemotypes do not cross-mate [9 , 24] . Sobral 2S males produce a Burst-type copulatory song and the Jacobina males produce a Pulse-type copulatory song , categorised as P1 because of trains of pulses with usually two or three cycles per pulse [12] . The Campo Grande chemotype copulatory song has not yet been categorised . The sand flies were maintained at 28 ± 2°C , 80 ± 5% relative humidity ( RH ) and a 12:12 light:dark ( L:D ) photoperiod in an insectary at Lancaster University ( United Kingdom ) . Immature stages were maintained in rearing pots in which the bottom was filled with a layer ( 2 cm ) of dampened Plaster of Paris to maintain humidity . Females and males were pooled together 3–4 days after eclosion in Barraud cages ( 18 x 18 x 18 cm ) and the females were routinely blood-fed on anaesthetized mice to maintain the colony . Sand fly blood feeding for colony maintenance was performed according to the guidelines and regulations of the Animals in Science Regulation Unit ( ASRU ) and in accordance with the terms of a regulated licence ( PPL 40/3279 ) in compliance with the UK Home Office , Animals ( Scientific Procedures ) Act ( ASPA ) regulations . All procedures involving animals were reviewed and approved by the Animal Welfare and Ethical Review Board ( AWERB ) at Lancaster University . Analysis of male sex-aggregation pheromone gland extracts and headspace entrainment extracts was performed on an Agilent 7890A/5975C GC-MS ( Agilent Technologies UK Ltd , Cheshire , UK ) operating in electron impact mode . Chromatographic analysis was conducted on a non-polar HP-5MS capillary column , 30 m x 0 . 25 mm i . d . , 0 . 25 μm film thickness ( Agilent , UK ) , using H2 as carrier gas at 1 ml min-1 . Samples were introduced via an on-column injector set at 40°C . The temperature program was an initial temperature ( 40 oC ) held for 2 min and then increased at 10°C min-1 to a final isothermal temperature ( 250 oC ) held for 10 min . To remove potential contaminants , all glassware was carefully cleaned prior to use by washing in a 10% detergent solution . It was then rinsed with distilled water , dried with acetone and finally heated in an oven at 180ºC for 12 h . The components of the the entrainment apparatus were connected with fluorinated ethylene propylene ( FEP ) tubing that was cleaned internally by rinsing with hexane ( BDH HiPerSolv , 97% , VWR , Lutterworth , UK ) before and after each entrainment . A new clean 50 ml r/b flask was used for every experimental replicate to ensure that the potential presence of residual pheromone did not interfere with the outcome of successive entrainments . To obtain male sand flies of known age , larval rearing pots were inspected every 2 h , and newly emerged males were transferred to nylon netting cages ( 18 x 18 x 18 cm ) inside plastic bags . These males were kept under the same temperature , RH and L:D conditions as the colony . Humidity was maintained by placing dampened laboratory filter paper inside the plastic bags and sugar ( 50% fructose solution ) was freely available on a small piece of cotton wool inside the holding cage . Males were selected for experimentation at known ages; 0–2 , 6–8 , 12–14 , 18–20 , 24–26 hours old and 2 , 3 , 5 , 7 , 9 , 12 and 15 days old . To determine the pheromone gland content , six individuals ( replicates ) of each age category were analysed by GC-MS . Males were individually placed in Pasteur pipette ampoules and covered with a drop ( ca . 10 ul ) of analytical grade hexane ( ≥ 99% purity , SupraSolv , Merck , Germany ) . The ampoules were flame-sealed and left for 24 h at room temperature prior to analysis . Subsequently , the ampoules were opened and the solvent was gently evaporated under N2 to a volume of ca . 1 ul . The entire sample was then injected into the GC-MS system . Groups of 10 males , which appeared to be healthy and vigorous , were immobilised by cooling in a freezer for 30 s , and transferred from the holding cage into a clean 50 ml r/b glass flask using a battery powered aspirator . Pheromone released from the males was collected from the headspace volatiles using a portable entrainment apparatus ( Barry Pye , Kings Walden , Herts , UK ) . Clean air was pushed through the 50 ml r/b glass flask containing the male sand flies into a glass tube filled with Tenax , an adsorbent polymer ( ORBO 402 , Sigma-Aldrich Ltd . , Dorset , UK ) . All joints in the apparatus were sealed with Teflon tape and the airflow at the outlet of the Orbo 402 tube was measured accurately with a bubble flow meter and adjusted with a rotameter ( GPE Ltd . , Leighton Buzzard , UK ) to 400 ml min -1 . Adsorbent tubes were used only once . The entrainment was done in an insectary at 26–28°C and 60–80% RH under controlled light conditions . Volatiles adsorbed on the Orbo 402 tubes were eluted in 2 ml of pure analytical grade hexane . These extracts were collected in small , clean glass Pasteur pipette vials and concentrated under a gentle stream of N2 to 10 ul , and then 1 ul ( 1 male equivalent ) was injected into the GC-MS system . Peak areas of the main terpene component present in the extracts were compared to those of known amounts of both caryophyllene ( 40 ng/ul ) and 9MGB ( 40 ng/ul ) as external standards . The major terpene peak usually represents more than 90% of the total terpenes present , and behavioural biossays have demonstrated that it is the active component of the extract [35 , 36] . Analytical standards ( n-alkane series C8-C20 ) of known concentration ( 10 ng ul -1 ) were also injected at the begining and end of each analytical session to provide comparative retention time data , an accurate average for the peak areas , and as a check on the GC-MS system performance . To determine the effect of the presence of females on pheromone release , three 4-day old virgin females were placed in the 50 ml r/b flask along with the 10 males ( males + females ) . The females remained with the males throughout the experiment and the Orbo 402 tubes were replaced each hour as previously described . To determine if light or dark had an effect on pheromone release we entrained pheromone from males and males + conspecific females in two lighting conditions light ( L ) or dark ( D ) . Entrainments were carried out on groups of males and males + females . For each light regime 4–6 experimental replicates were carried out . The pheromone content of 5-day old males ( n = 1 male , 3 replicates ) was compared with the amount of pheromone released during 24 h by 5-day old males ( 12:12 LD ) ( n = 10 males , 3 replicates ) for each of the three chemotypes studied . The mortality within the entrainment glass r/b flask varied between 10% to 20% . A Kruskal-Wallis non-parametric ANOVA was used to compare the amount of pheromone: 1 ) extracted from the glands of individual males of the three chemotypes at different ages , 2 ) extracted from 5-day old males with the amount of pheromone released during 24 h by 4–5 day old males , 3 ) released during each hour of the 4 h period by 4–5 day old males and males + conspecific females , under the two light regimes for each of the three chemotypes . Results are expressed as mean ± standard error ( X ± SE ) ng male -1 hour -1 . All statistical analyses were done using SPSS ( v15 . 0 , SPSS Inc . ) software . Alpha was set at P < 0 . 05 .
GC-MS analysis confirmed that the retention times ( Rt ) of the major peaks of each of the chemotypes were 14 . 58 min ( 3MαH , Jacobina ) , 15 . 82 min ( 9MGB , Campo Grande ) and 20 . 17 min ( diterpene , Sobral 2S ) ( Fig 1 ) . Retention time and mass spectral data allowed us to accurately identify the relevant pheromone peak in both pheromone gland and headspace extract chromatograms even when they were present in trace amounts . The GC-MS analysis of the Jacobina male extract showed that up to 12 other terpene compounds were present in minor quantities ( four were present in trace amonts only and were unquantifiable ) , which eluted both before and after the main peak ( Fig 1A ) . In the Campo Grande male extracts , we noticed two small terpene peaks that eluted before the major 9MGB peak ( Fig 1B ) . In the extract of Sobral 2S males seven other minor diterpene components were apparent ( Fig 1C ) . These data are consistent with previous observations from field collected L . longipalpis and confirmed that the terpene components of the glands had not changed over the time they were kept in a laboratory colony , Jacobina [37] , Sobral 2S [24 , 35] and Campo Grande [23] . None of the pheromone extracts from any of the three populations contained significant quantities of the predominant pheromone molecule ( s ) characteristic of any of the other populations . Analysis of the pheromone gland content revealed that males of the three chemotypes produced and stored pheromone throughout the 15 days of the experiment , although the amount of pheromone stored varied with age ( Fig 2 ) . Traces of pheromone were detected in extracts from individual Campo Grande and Sobral 2S males at 6–8 h post-emergence but were not detected in individual Jacobina males until 12–14 h after emergence ( Fig 2 ) . Each chemotype displayed a distinct pattern of pheromone accumulation over time; generally , pheromone gland content increased for 7–9 days , after which a small reduction in quantity of pheromone was observed in most of the oldest specimens studied . Overall , there was no significant difference in the amount of pheromone present in the glands of the three chemotypes despite large differences in quantities on specific days . Jacobina gland content ( Fig 2A ) peaked at 7 days but the amount of pheromone ( 128 . 8 ± 30 . 3 ng ) was not significantly different to the other two chemotypes ( χ2 = 5 . 81 , df = 2 , P = ns ) . Campo Grande gland content ( Fig 2B ) peaked at 9 days ( 203 . 5 ± 57 . 4 ng ) and Sobral 2S male’s pheromone gland content ( Fig 2C ) peaked at 7 days ( 199 . 9 ± 34 . 3 ng ) . The biggest increase in pheromone gland content was between 1st and 2nd day old Jacobina males when the average amount of pheromone stored in the glands increased from 10 . 7 ± 3 . 0 ng to 102 . 3 ± 18 . 9 ng , a 10-fold increase . The Jacobina gland content remained relatively constant for the remainder of the time with a slight dip in pheromone content in older males . A similar increase was observed in Campo Grande males , where the amount of pheromone stored in 2-day old males showed a 10-fold increase ( from 11 . 1 ± 3 . 4 ng to 117 . 7 ± 28 . 7 ng ) compared to 1-day old males . Pheromone continued to be produced and content reached a peak at 9 days , after which time it also declined . Pheromone accumulation in the Sobral 2S males was markedly different to the other two chemotypes . There was no increase in the gland content between 1 and 2 days , but the amount of pheromone increased gradually and reached a peak at 7 days , after this time gland content was greatly reduced . When males were first placed in the 50 ml r/b entrainment flask , they were very active , and appeared to compete with each other to establish space around themselves . This activity occurred both when females were present and absent . Within the first hour of the entrainment , males spent 15–45 min fanning their wings , a behaviour that is associated with pheromone release . Afterwards , they remained mostly motionless for several hours , periodically repositioning themselves within the flask . The general pattern of pheromone release for all three chemotypes was that it was greatest during the 1st h of the entrainment . In Jacobina and Campo Grande chemotypes release was significantly reduced during the following 3 h , with release rate values approaching zero in some samples after 2–4 h of continuous entrainment ( Figs 3 and 4 ) . The amount of pheromone released by the Sobral 2S chemotype males was much lower than for the other chemotypes and the decrease in release over time was more gradual ( Fig 5 ) . Nevertheless , this hourly pattern of pheromone release was observed in all three chemotypes in all experimental regimes , both L and D regimes , and in male and male + female entrainments . Males always released more pheromone when females were present during the 1st h of the entrainment for all three chemotypes . However , after the 1st h , the presence of females made no significant difference to the release of pheromone for either the Jacobina or Campo Grande chemotypes ( Figs 3 and 4 ) . By contrast , Sobral 2S males in the presence of females continued to release more pheromone per hour than males alone although in general without significant differences ( Fig 5 ) . For the Jacobina chemotype , 1 . 8 times more pheromone was released when females were present under light conditions ( χ2 = 5 . 4 , df = 1 , P ≤ 0 . 05 ) and 2 . 3 times when females were present in dark conditions ( χ2 = 3 . 0 , df = 1 , P ≤ 0 . 05 ) ( Fig 3 ) . For the Campo Grande chemotype , 2 . 1 times more pheromone was released when females were present in light ( χ2 = 5 . 4 , df = 1 , P ≤ 0 . 05 ) , and 1 . 2 times more when females were present in dark ( χ2 = 0 . 3 , df = 1 , P = ns ) ( Fig 4 ) . For Sobral 2S , 2 . 3 times more pheromone was released when females were present in light ( χ2 = 5 . 7 , df = 1 , P ≤ 0 . 05 ) and 3 . 2 times more when females were present in dark ( χ2 = 3 . 8 , df = 1 , P ≤ 0 . 05 ) ( Fig 5 ) . Light conditions appeared to have little effect on pheromone release by the Jacobina and Campo Grande chemotypes ( Table 1 ) . However , they were important for pheromone release by the Sobral 2S chemotype where males and males + females released more pheromone under light compared to dark conditions ( Table 1 ) . For males and males + females of both the Jacobina and Campo Grande chemotypes there was no significant difference in the amount of pheromone released for any of the 4 h periods of both light regimes ( Table 1 ) . For the Sobral 2S chemotype , males released almost twice as much pheromone during the 1 st h in light compared to the dark ( 2 . 6 ± 0 . 6 ng vs 1 . 0 ± 0 . 3 ng; χ2 = 5 . 0 , df = 1 , P ≤ 0 . 05 ) . A higher increase was found during the 2 nd h ( 1 . 9 ± 0 . 8 ng vs 0 . 06 ± 0 . 1 ng; χ2 = 5 . 2 , df = 1 , P ≤ 0 . 05 ) . When females were present there was a significant difference in the pheromone released in light vs dark conditions only during the 3rd h of entrainment ( 2 . 3 ± 1 . 1 ng vs 0 . 06 ± 0 . 1 ng; χ2 = 6 . 2 , df = 1 , P ≤ 0 . 05 ) ( Table 1 ) . During the 1st h of entrainment , a significant difference in the average amount of pheromone released by the males and males + females was observed between the three chemotypes . Campo Grande males released the greatest quantities of pheromone , followed by Jacobina males and then Sobral 2S males . The average pheromone release of individual , 4–5 day old males was significantly different for each of the three chemotypes ( χ2 = 22 . 6 , df = 2 , P ≤ 0 . 001 ) . Campo Grande males released 40 . 3 ± 12 . 6 ng , Jacobina chemotype males released 16 . 0 ± 4 . 8 ng and Sobral 2S chemotype males 2 . 0 ± 0 . 9 ng . The average amount of pheromone released by 4–5 day old males kept with females was also significantly different for each of the three chemotypes ( χ2 = 15 . 1 , df = 2 , P ≤ 0 . 001 ) . As before , the Campo Grande chemotype males released more pheromone ( 66 . 6 ± 17 . 7 ng ) , followed by the Jacobina chemotype males ( 31 . 9 ± 8 . 4 ng ) and the Sobral 2S chemotype ( 4 . 8 ± 1 . 3 ng ) . After 24 h of entrainment , 5-day old Campo Grande males had released 92 . 6 ± 32 . 1 ng of pheromone; the Jacobina males 61 . 3 ± 37 . 2 ng and the Sobral 2S males 90 . 9 ± 38 . 9 ng . Five days old , Campo Grande males had 125 . 5 ± 37 . 6 ng stored in their pheromone glands , Jacobina males 97 . 1 ± 7 . 8 ng and Sobral 2S 131 . 0 ± 16 . 9 ng . Thus , overall , males had released 73 . 7% , 63 . 3% and 67 . 4% of pheromone relative to their gland contents , respectively .
This study shows that in L . longipalpis , the content of the pheromone gland , which is likely to be closely related to biosynthesis and release , is influenced by both internal and external factors . The age of commencement of pheromone production varies between members of the complex . The amount of pheromone present in the gland depends on the chemotype , and the age of the male sand fly . Pheromone gland content is not linearly related to age and in both of the methylsesquiterpene-producing chemotypes ( Jacobina and Campo Grande ) there is a period of significant increase in gland content , which may reflect either a period of increased pheromone production or improved ability to store the pheromone . In the Sobral 2S chemotype , the gland content increased over a much longer period , from 2 to 7 days . This may reflect changes in the rate of production and/or accumulation of pheromone within the gland; in any case , the pattern is markedly different from the other two chemotypes . In this study we have also demonstrated that the amount of pheromone released by males depends on several factors , which include whether or not females are present and the activity of the males . The light conditions in which they were held only affected pheromone release in the Sobral 2S chemotype . Previous studies on the ultrastructure of pheromone glands of L . longipalpis have shown that male sand flies have structures that could be involved in the storage and subsequent release of sex-aggregation pheromone [38 , 39] . These structures appear to develop in synchrony with pheromone gland cell maturation and pheromone content [28] . As we detected the presence of traces of pheromone 6–8 h after eclosion in Campo Grande and Sobral 2S males , and after 12–14 h in the Sobral 2S chemotype , we confirm previous work in which pheromone synthesis was shown to commence 10–14 h post emergence [28 , 38 , 39] . As technical developments in GC/MS detectors lead to improved sensitivity , it is likely that pheromone production will be seen to start at an even earlier age . Previous studies have shown that males up to 4-days old [28] or 9-days old [38] have pheromone present in their glands but we have shown in this study that pheromone is present in the glands of 15-day old males . The biological significance of this remains to be determined but clearly suggests that production , storage and potentially release of pheromone is lifelong for males despite younger males having greater success at obtaining matings [39] . The pheromone gland content in the Campo Grande and Jacobina chemotypes increased by 1000% during a 24 h period between 1 and 2 days after emergence . By comparison , the gland content of Sobral 2S chemotype males increased more slowly ( 300% between day 2 and 3 ) and started when the males were older . The amounts of pheromone continued to increase in males of all three chemotypes up to 7–9 days old , and thereafter remained constant or gradually declined . This drop , which was particularly noticeable in Sobral 2S males , may partly account for the lack of mating success in older male sand flies [39] . A drop in pheromone gland content with advancing age is common in many groups of insects , such as flies , e . g . Isoceras sibirica [40] , and moths , e . g . Ctenopseustis spp . , Planotortrix octo and Epiphyas postvittana [41] . The differences in pheromone gland content between the three chemotypes and in particular between the methylsesquiterpene producing populations ( Jacobina and Campo Grande ) and the diterpene population ( Sobral 2S ) suggest important behavioural or reproductive differences . A detailed analysis of the terpene composition of some wild populations of L . longipalpis from Brazil was previously described [24] . The quantity of pheromone found in our Sobral 2S laboratory colony males ( 132 . 0 ± 37 . 9 ng male-1 and 199 . 8 ± 90 . 9 ng male-1 at 5 and 7 days old , respectively ) was similar to the amounts found in wild-type mixed-age males ( 167 . 9 ± 52 . 4 ng male-1 ) . The amounts of 9MGB from wild specimens collected from different parts of Brazil varies considerably , e . g . males from Lapinha ( Minas Gerais State ) produced 116 . 5 ± 13 . 5 ng male-1 of pheromone which was significantly more than wild type Sobral 1S males ( 47 . 8 ± 10 . 6 ng male-1 ) . Our laboratory colonised Campo Grande males produced 125 . 5 ± 9 . 6 ng male-1 at 5 days and 184 . 4 ± 10 . 0 ng male-1 at 7 days . This may indicate that wild sand flies contain less sex-aggregation pheromone than laboratory colonised sand flies as a consequence of environmental factors , e . g . temperature , relative humidity , diet , habitat , season and/or physiological stage [42–44] . However , these differences could also occur because the 2 Sobral populations are sympatric whereas the others are allopatric [24 , 45 , 46] . In addition , these differences may reflect the population substructuring seen across Brazil [12] . Male behaviour in the entrainment flasks was typical of “lekking” males and involved parading , wing flapping , wing fanning and/or wing vibrating , walking forward in short bursts and changing directions , and fighting with other males [39 , 47 , 48] . Wing flapping and/or fanning has been suggested by some authors to be a way of distributing pheromone [30 , 33] and males that fan their wings more than competitor males are more likely to be successful in obtaining a mate [29] . Our results suggest that during this intense activity the males partly deplete their pheromone glands , as there is a notable decline in the amount of pheromone released after the 1st h of entrainment compared to the next 3 h . After this initial period of activity , males remained largely motionless for several hours . This stage called “quieting” was reported as a possible indication of pheromone communication because the males that were distributed with regular spacing around the flask , may have established a dominance hierarchy [47] . Although the males may use this “quieting” time to replenish pheromone reservoirs after periods of heavy demands , our results suggest that even after 24 h the pheromone in the glands are not completely depleted . It would be useful to measure the amount of pheromone in the glands during and after the resting period to see whether gland content is restored and how long the recovery period is . More pheromone was released by males of all three chemotypes when conspecific females were present . This was most noticeable during the 1st h when increases of between 15 and 300% were observed . When both sexes were held together , an unquantified increase in male activity including wing fanning and other behaviours were observed , which may account for the greater release of pheromone . Overall , our study showed that light had little or no effect on pheromone release from males of the Jacobina and Campo Grande chemotypes . However , Sobral 2S males released more pheromone either when alone or with females in light conditions compared to dark . Whether or not the light regime also influences pheromone production by the Sobral 2S chemotype remains to be determined . In the future it will be interesting to determine the role of other factors on pheromone gland content and release . Studies on other insects have shown that the density and numbers of males and male diet cause changes in the sexual signalling and mating behaviour [49 , 50] . In L . longipalpis other factors such as body size [39] and gland or tergite width [29] have been reported to have no effect . From these studies it is clear that pheromone gland content and release are dynamic and responsive processes . The work presented here is the first attempt to provide a comparative analysis of the sex-aggregation pheromone gland content and factors that might influence the release of the pheromone of the three most widespread chemotypes of L . longipalpis from Brazil . Although this study was conducted under laboratory conditions on only one population of each of the chemotypes , it is clear that a number of factors can influence pheromone release and that it is a dynamic and not a passive process . We have shown that the presence of females and light conditions influence pheromone release . The observations suggest that significant behavioural , biosynthetic and ecological differences between the three chemotypes and in particular between the methylsesquiterpene chemotypes ( Jacobina and Campo Grande ) and the diterpene chemotype ( Sobral 2S ) occurs . It is likely that there are other factors that may also be important but which we have not investigated , for example numbers of males and the presence of host odour on the pheromone gland content . Further work is also needed to identify the circumstances under which males produce and store pheromone and how other factors could positively or negatively impact both of these . In this study we did not investigate the effect of any of these factors on pheromone gland content and it will be interesting in the future to examine these factors also . An exploration of other aspects of the sex-aggregation pheromones , such as their volatility and the subsequent dispersion of these chemicals , is critical to understanding their behavioural and ecological importance . We have looked at three different chemotypes of L . longipalpis and each of these represent a member of the species complex . However , the precise nature of the L . longipalpis species complex is unclear and there are several contradictory views on the numbers of sibling species and their associations that have recently been reviewed [10] . A better understanding of chemical communication will also be useful for developing synthetic pheromone for control and monitoring applications , e . g . an understanding of differences in rates and patterns of pheromone release by the methylsesquitepene and diterpene producing members of the L . longipalpis complex may require different approaches to the practical application of these chemicals . Finally , we believe that sex-aggregation pheromones are a valuable tool for defining members of the L . longipalpis species complex . The different pheromones represent important differences between members of the complex because they act as a premating isolating barriers . These variations are underpinned by significantly different biosynthesis in males and receptor biology in females . The differences between the chemotypes that this study highlighted are therefore valuable additional supporting evidence to ultimately help define the members of the complex . | The Dipteran subfamily Phlebotominae includes the genera Lutzomyia and Phlebotomus among which several species are important vectors of parasitic and bacterial pathogens . The sand fly Lutzomyia longipalpis is considered the main vector of visceral leishmaniasis ( VL ) in the New World . Based on the main component of the male sex-aggregation pheromone gland , different sex pheromone-producing populations ( chemotypes ) of L . longipalpis are recognized in Brazil . Given the importance of the sex-aggregation pheromones in the biology of this species complex , we present here the first attempt to study how pheromone accumulates in the glands over time and factors that might influence its release in the three most common chemotypes from Brazil . Our results demonstrated that pheromone first starts to accumulate a few hours post-eclosion ( 6–12 h ) and this continues over 15 days . Pheromone release is a dynamic process which varies between the 3 chemotypes depending on biotic factors , such as light regime and presence/absence of conspecific females . This work provides valuable information , critical to our understanding of the behaviour and ecology of L . longipalpis sand flies and which will contribute to investigations to improve field-based pheromone control and monitoring of L . longipalpis sand flies . | [
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] | 2017 | A temporal comparison of sex-aggregation pheromone gland content and dynamics of release in three members of the Lutzomyia longipalpis (Diptera: Psychodidae) species complex |
Upon cell invasion , retroviruses generate a DNA copy of their RNA genome and integrate retroviral cDNA within host chromosomal DNA . Integration occurs throughout the host cell genome , but target site selection is not random . Each subgroup of retrovirus is distinguished from the others by attraction to particular features on chromosomes . Despite extensive efforts to identify host factors that interact with retrovirion components or chromosome features predictive of integration , little is known about how integration sites are selected . We attempted to identify markers predictive of retroviral integration by exploiting Precision-Recall methods for extracting information from highly skewed datasets to derive robust and discriminating measures of association . ChIPSeq datasets for more than 60 factors were compared with 14 retroviral integration datasets . When compared with MLV , PERV or XMRV integration sites , strong association was observed with STAT1 , acetylation of H3 and H4 at several positions , and methylation of H2AZ , H3K4 , and K9 . By combining peaks from ChIPSeq datasets , a supermarker was identified that localized within 2 kB of 75% of MLV proviruses and detected differences in integration preferences among different cell types . The supermarker predicted the likelihood of integration within specific chromosomal regions in a cell-type specific manner , yielding probabilities for integration into proto-oncogene LMO2 identical to experimentally determined values . The supermarker thus identifies chromosomal features highly favored for retroviral integration , provides clues to the mechanism by which retrovirus integration sites are selected , and offers a tool for predicting cell-type specific proto-oncogene activation by retroviruses .
Retroviruses and retrotransposons are of profound importance to eukaryotic biology , evolution , and medicine . These retroelements constitute at least 40% of the mass of mammalian genomes [1] and 75% of the maize genome [2] . When retroelements are transcribed they remodel eukaryotic genomes by generating a cDNA and integrating it into locations scattered throughout the host cell genome [3] , [4] . By doing so , retroelements have the potential to influence local gene expression or to promote recombination and generate deletion mutations [5]–[7] . In some cases they act in trans to catalyze retrotransposition of cellular RNAs , generating pseudogenes or new exons within existing genes [8] , [9] . Since retrotransposon enhancer elements influence local gene expression , and retrotransposon silencing can vary from cell to cell , it has been proposed that retrotransposons contribute to the phenotypic variation that distinguishes genetically identical individuals [10] . Additionally , it has been suggested that programmed release from retroelement silencing accompanies metazoan development and leads to hypermutation in complex somatic tissues like the brain [11] , [12] . Among retroelements , retroviruses have received much attention , in part due to their association with human disease . Basic studies concerning retroviral replication have greatly advanced understanding of the biochemistry of retrotransposition [4] , [13] . A tetramer of the viral integrase protein ( IN ) [14] cleaves the ends of the viral cDNA to produce recessed 3′OH and free CA dinucleotides at the terminus of each long terminal repeat ( LTR ) [15] . IN catalyzes nucleophilic attack of host chromosomal DNA by the two free 3′-OH viral DNA ends , resulting in covalent attachment of the retroviral DNA strands to the host DNA [16]–[18] . The remaining free ends of the viral DNA are then repaired by host enzymes [19]–[21] . Study of HIV-1 , the retrovirus that causes AIDS , has led to the development of drugs that block retrotransposition and alter progression to AIDS [22] , [23] . Attempts to develop better therapies for HIV-1 would benefit from a deeper understanding of the integration mechanism . Gene therapy vectors based on another retrovirus , MLV , dramatically rescued children from a life-threatening illness , but a large percentage of the patients suffered from insertional activation of proto-oncogenes [24]–[28] . This lethal complication further emphasizes the need to better understand retroviral integration site selection in host chromosomal DNA . Retroviruses establish proviruses at sites throughout the host cell genome , but integration is not random . Some regions are favored hundreds of times over others [29] , [30] . For some retroviruses , transcribed regions are preferred [31] , [32] , though high-level , concurrent transcription at a given target gene inhibits integration [33] . Nucleosome-bearing DNA is targeted more efficiently than free DNA in vitro [34]–[37] perhaps because the integration machinery preferentially targets bent DNA [38] . Indeed , high-throughput sequencing experiments analyzing over 40 , 000 HIV-1 integration sites in cells show periodic distribution on predicted nucleosome positions , consistent with favored integration into outward-facing DNA major grooves in chromatin [39] . The retrotransposition mechanism , and integration site selection on a genomic scale , differs considerably from one class of retrovirus to another . HIV-1 infects non-dividing cells [40] , [41] and integrates preferentially into transcriptionally active genes , all along the length of the gene [32] , [42] , [43] . In contrast , MLV integration requires mitosis [41] , [44] and has a tendency to localize near promoters , 20% of the time within 2 kB of transcriptional start sites [31] , [42] . Retroviral capsid ( CA ) is sufficient to determine whether a given virus infects non-dividing cells [45] , [46] but both CA and IN contribute to integration site selection: an HIV-1 vector in which IN-coding sequences and a fragment of gag encompassing CA were replaced by the homologous MLV sequences exhibits the retrotransposition behavior of MLV [43] . Of the many host factors reported to interact with retroviral CA or IN [47]–[52] , the lentiviral IN-interacting protein PSIP1/LEDGF/p75 [53]–[55] is the most informative regarding integration site selection . LEDGF promotes the infectivity of HIV-1 and related lentiviruses and influences integration site selection [56]–[59] perhaps by acting as a physical tether directing integration to the chromosomal sites this protein naturally occupies . In support of this model , fusion of heterogeneous chromatin binding domains to the part of LEDGF that binds IN redirected the site of HIV-1 integration [60]–[62] . The mechanism by which gammaretroviruses such as MLV preferentially target promoter regions is unknown . We attempted to identify chromatin features predictive of retroviral integration site selection by exploiting ChIPSeq datasets . Compared to previous methods , this technology has brought profiles of human DNA binding factors and histone epigenetic modifications closer to genome-wide saturation [63]–[68] . Over 60 ChIPSeq datasets were compared with 14 retroviral integration data sets in order to develop tools for predicting viral integration sites throughout the genome with maximal predictive power .
To identify markers predictive of retroviral integration site selection , stringent associations were sought between ChIPSeq profiles for more than 60 chromatin-associated factors ( Table 1 ) [63]–[69] and 14 retroviral integration site datasets ( Table 2 ) [31] , [43] , [70]–[77] . Following a common convention in the retrovirus integration literature [78] , association with a given marker was defined as integration within 2 kB ( wi2kB ) of the nearest marker on the linear sequence of the chromosome . The proviruses in the datasets used here ( Table 2 ) were cloned from host genomic DNA using restriction enzymes , each of which has the potential to introduce a bias [79] . Therefore , as described in the literature [42] , [43] , [78] , [80] , each integration site was matched to ten control sites designed to exhibit the same bias as the experimental set: control sites were placed the equivalent distance from randomly chosen recognition sites of the restriction enzyme that was used to clone the provirus ( see Methods ) . No distortion of the results by the control datasets was evident , in that identical values for provirus association with a given chromatin feature were obtained using 10 different randomly-generated control datasets . Integration datasets are generally compared with control datasets using Fisher's exact test and reported as the p-value [42] , [43] , [77] , [80] . Since significance determination is dependent upon dataset size , these measures can be easily conflated , generating extraordinarily low p-values and making it difficult to compare the importance of two factors [78] . Receiver operating characteristic area methods ( ROC ) have also been used to identify associations [78] , [80] , [81] , but these methods also have drawbacks when it comes to discriminating between markers for retroviral integration . With the datasets used in these studies , the number of true negatives ( control sites not associated with the marker ) is considerably higher than the number of false positives ( control sites associated with the marker ) . Given that the false positive rate = false positives / [false positives+true negatives] , two markers which differ by as much as 10-fold in terms of the number of false positives will fail to be differentiated from one another using ROC [82] . To address the problems associated with the analysis of these highly skewed data sets , we borrowed the concepts of Precision and Recall from the field of Information Retrieval [82]–[84] . In the context of this discussion , Precision is defined as the number of experimentally-determined integration sites associated with a marker divided by the sum of all associated experimental and all associated control sites ( see Methods ) . Recall is the number of marker-associated experimental integration sites divided by all experimental integration sites . The Fβ score , a convenient way to aggregate Precision and Recall , is the weighted harmonic mean of the two measures [85] . Usual values for β are 0 . 5 , 1 or 2 [86] . To limit the influence of true negatives in the analysis of these skewed datasets , we emphasized Precision over Recall by setting β = 0 . 5 . The F score tracks better with statistical significance when β = 0 . 5 , than 1 or 2 ( see the comparison of results using different values for β , as well as with other metrics , described below , as well as Text S1 ) . Moreover we normalized the number of false positives with respect to the number of experimental integration sites so as to make the F score independent of control sample size . For the analysis here , markers with F scores between 0 . 5 and 1 were considered to be associated with integration sites . To visualize genome-wide association of proviruses with potential markers , chromosome projection mandalas were developed ( Figure 1A , see Methods ) . Each dot on the mandala represents a retroviral integration site with the following polar coordinates: angular distance corresponds to genomic location on the indicated chromosome; radial distance from the contour of the circle is the distance in nucleotides from the nearest site of the marker in question , log-scaled from 0 to 1 megabase . Currently , the best chromosomal marker for retroviral integration site selection is the association of CpG islands and transcription start sites ( CpG+TSS ) with gammaretroviruses [31] , [43] , [71] . By examining published datasets for MLV , 21 to 27% of integration sites fall within 2 kB ( wi2kB ) of CpG+TSS , with probabilities <3×10−22 to <4×10−42 ( Table 3 ) . Despite these extremely low p-values , F scores calculated for these datasets fall between 0 . 36 to 0 . 51 ( Table 3 and Figure 1E ) , indicating that CpG+TSS is not a powerful predictor of MLV integration sites . Stronger association with CpG+TSS was observed with porcine endogenous retrovirus , PERV ( 50% wi2kB; p<10−250; F score 0 . 72 ) , and xenotropic MuLV-related virus , XMRV ( 33% wi2kB; p<10−46; F score 0 . 58 ) , two viruses from the same gammaretrovirus family as MLV ( Table 3 and Figure 2 ) . No significant association with CpG/TSS was observed for proviruses generated by non-gammaretroviruses , including HIV-1 , for which the F score was 0 . 11 ( Table 3 , Figure 3 ) , or with ASLV , HTLV , or Foamy virus ( Table 3 , Figure S1 ) . ChIPSeq datasets for 60 chromatin-associated factors ( Table 1 ) were compared with 14 provirus datasets for MLV , PERV , XMRV , HIV-1 , HTLV-1 , ASLV , Foamy virus , and HIV/MLV chimeras ( Table 2 ) . Acetylation of H3 and H4 at several positions , and methylation of H2AZ , H3K4 , and K9 , were strongly associated with gammaretroviral integration sites , all with F scores >0 . 80 ( Figures 1 and 2 , Table 3 and Tables S1 and S2 ) . H3K4me3 in particular was strongly associated with MLV integration sites ( 68% wi2kB; p<10−324; F score 0 . 83 ) and with the integration sites of PERV ( 60% wi2kB; p<10−350; F score 0 . 82 ) and XMRV ( 64% wi2kB; p<10−170; F score 0 . 81 ) ( Figures 1 and 2 , Table 3 ) . The effect of window size on the F score was examined for factors strongly associated with MLV and the other gammaretroviruses . Interestingly , the F score was maximal when it was calculated using a window of +/−2 kB for proviruses flanking the sites of these chromatin features ( Figure 4 ) . In contrast to the gammaretroviruses , HIV-1 integration sites were not associated with H3K4me3 ( 9% wi2kB; p>0 . 05; F score 0 . 21 ) ( Figure 3 and Table 3 ) . Among the markers for which ChIPSeq datasets were available from HeLa cells , H3K4me1 had the strongest association with HIV-1 proviruses ( 48% wi2kB; p<10−31; F score 0 . 6 ) , though H3K4me1 was the sole chromatin marker that yielded F score values greater than 0 . 5 across all queried viruses ( Table 3 , Table S3 ) . H3K4me3 , and other chromatin modifications linked to transcriptionally active promoters [64] , [87]–[89] , were reported to be associated with HIV proviruses when a window of 50 kB flanking the proviruses was considered [81] , [90] . This could be explained by the fact that HIV-1 proviruses localize to active transcription units with equal distribution along the length of the genes [32] , [42] , [43] , and that the size of the average transcription unit is on the order of tens of kilobases . To examine this further , the F score for HIV-1 versus H3K4me3 in HeLa cells was plotted as a function of window size ( Figure 5 ) . For comparison , a similar plot was generated for a hypothetical marker at the TSS of transcribed genes in HeLa cells , taking into account the length of these genes , and considering a uniform distribution of proviruses on each gene . For both H3K4me3 and the hypothetical TSS marker , the F score plateaued at a window size of 20 kB , the median gene length . Thus if the window size is large enough to encompass the TSS and half of the gene length , the F score becomes significant . This could explain the window-size dependence of HIV-1 association with H3K4me3 . We also analyzed an integration site map for an HIV-1 vector in which IN-encoding pol sequences and part of gag were replaced by homologous sequences from MLV [45] . It was shown previously that substitution of these two viral components from MLV is sufficient to change the integration site preference of HIV-1 , such that it targets TSS with a frequency like MLV [43] . Replacement with these MLV genes was sufficient for HIV-1 proviruses to associate with methylated histones ( 65% wi2kB , p<10−182 , F score 0 . 82 ) in a manner that was indistinguishable from MLV ( Figure 3 ) . A remarkable association was found between MLV integration sites and STAT1 binding sites in IFN-γ stimulated HeLa cells ( 68% wi2kB; p<10−324; F score 0 . 83 ) ( Figure 1 and 2 , Table 3 ) . Strong association with STAT1 binding sites was also observed for porcine endogenous retrovirus ( 60% wi2kB; p<10−350; F score 0 . 82 ) and XMRV ( 64% wi2kB; p<10−170; F score 0 . 81 ) . Interestingly , if MLV was compared with STAT1 bindings sites in HeLa cells that had not been treated with IFN-γ the association was greatly decreased ( 34% wi2kb; p<10−120 , F score: 0 . 69 ) . HIV-1 proviruses showed no association with STAT1 ( 8% wi2kB; p>0 . 4; F score 0 . 27 ) . Substitution of HIV-1 IN and parts of gag with the corresponding genes from MLV was sufficient for HIV-1 proviruses to associate with STAT1 binding sites ( 64% wi2kB , p<10−182 , F score 0 . 81 ) ( Figure 3 , Table 3 ) . Attempts to detect a protein-protein interaction between STAT1 and MLV IN were unsuccessful . STAT1-deficient cell lines , either Stat1−/− mouse embryonic fibroblasts [91] , HeLa cells with stable STAT1 knockdown using lentiviral vectors [92] , or well-characterized , STAT1 mutant , HT1080 cells [93] , were challenged with MLV and , as a control , HIV-1 . No clear defect associated with STAT1-deficiency was detected when MLV infectivity was compared with HIV-1 ( data not shown ) . These results suggest that STAT1 itself is not directly responsible for MLV integration site preference but that its chromatin preferences resemble those of MLV . The stability of the F score for H3K4me3 , an excellent marker , and for TSS/CpG , a poor marker , was examined as the size of a dataset containing 588 MLV proviruses [43] was decreased . The ratio of the size of the provirus dataset with respect to the control dataset was fixed at ten . While the p-value varied enormously as the size of the provirus dataset decreased , the F score was constant for both H3K4me3 and TSS/CpG over the full range from 50 to 500 proviruses ( Figure 6A ) . The size of the provirus dataset was then fixed at 588 [43] and the F score was plotted versus the ratio ( from 0 . 1 to 10 ) of the experimental and control datasets . Under these conditions the F score for either factor was constant except for a small increase when the ratio of the experimental to control datasets decreased below 0 . 3 ( Figure 6B ) . The p-value for H3K4me3 changed markedly with the change in ratio of the datasets . Thus , while the p-value is strongly biased by the size of the provirus dataset or by the ratio of experimental to control sites , the F score is a remarkably stable measure . Similar stability was observed for the F score of all markers as compared to all proviral integration datasets ( data not shown ) . As demonstrated for the F score ( Figure 6 ) , the area under the curve ( AUC ) ROC method used previously to evaluate markers associated with retroviral integration sites [78] , [80] , [81] is a robust measure that is insensitive to dataset size . Like the F score , AUC ( ROC ) also works well to assess markers that are weakly or moderately associated with integration sites ( Text S1 ) . But , as demonstrated for the highly associated marker H3K4me3 , AUC ( ROC ) does not respond to the increase in false positives that is expected with increasing window size ( Figure 7A ) . Moreover , this insensitivity to false positives leads AUC ( ROC ) to overestimate the association of markers that are more common in the genome . Consequently , AUC ranks markers differently from statistical significance , as shown in Figure 8 and discussed in more detail in Text S1 . In contrast , the p-value and the F0 . 5 score incorporate an adjustment for the increase in false positives as window size increases , and both measures achieve a maximal value at a window size of 2 kB ( Figure 7A ) . A standard regression plot shows that the F0 . 5 score tracks with the p-value almost perfectly ( R2 = 0 . 97 ) , whereas the AUC ( ROC ) diverges considerably ( R2 = 0 . 37 ) ( Figure 7B ) . The F0 . 5 score and the p-value adjust similarly for the increasing number of false positives . Indeed among a set of measures that included F0 . 5 , F1 , F2 , Area Under Curve ( AUC ) , Area Under Precision/Recall ( AUPR ) , Odds Ratio ( OR ) , Shannon Mutual Information ( SMI ) , and Difference of Proportions ( DOP ) , the F0 . 5 score showed the strongest link with statistical significance ( see Methods ) . We analyzed one of the MLV integration dataset in HeLa cells [43] ( the same results were obtained using the other HeLa dataset [31] ) and the MLV integration dataset in CD4+ T cells [71] . The strength of association of 9 significant markers ( in terms of p-value ) from HeLa cells , and 31 significant markers from CD4+ T cell , was assessed . Markers were ranked according to each of the above methods and the results of each were compared with the ranking obtained using significance −log ( p value ) . This was done by fixing the matched control data set size at 10-times the experimental dataset size and using window sizes of 2 , 5 , 10 , and 20 kilobases . Results for the analysis are reported in Table 4 and in Text S1 . Several conclusions can be drawn from this analysis . Concerning markers that were highly associated with proviruses , the ranking yielded by the F0 . 5 score closely tracked with significance ( Table 4 ) . By increasing the weight of recall over precision by increasing the beta value ( F1 or F2 ) the F score tracked less well with significance ( it was the F0 . 5 score that was used throughout this manuscript ) . The SMI also tracked well , but , unlike the F score , the results with this method vary with dataset size ( see Text S1 ) . The AUC , OR , AUPR , and DOP were clearly not as good as the F0 . 5 score . Concerning markers that are moderately or weakly associated with proviruses ( Text S1 ) , the ranking based on the F0 . 5 score was similar to that obtained by significance , AUC , AUPR , OR , or DOP ( Table 4 ) . SMI scored less well for these markers . Figure 8 visualizes the deviation of AUC , AUPR or F0 . 5 from significance . Red squares indicate cases in which the ranking calculated by the specified metric differs from the rank obtained by significance . All results indicate that , for the datasets evaluated here , the F0 . 5 score is a superior measure at discriminating among factors for differences in magnitude of association with genomic sites of integration . Given the effectiveness of the F score for identifying and ranking individual factors associated with retrovirus integration site selection , markers with the best F scores were combined in an attempt to generate a supermarker ( see Methods for more details ) . An estimate of the probability of proviral integration into the host genome ( P ( V ) ) was derived based on the genomic distribution of combinations of ChIPSeq peaks for the best scoring markers with respect to particular experimental provirus datasets . The resulting probability mass function ( at base- pair resolution ) is ( A ) where V is the set of proviral integration sites , Fj is the F score associated with each marker Mj , for the set of peaks Γj . x is the physical position on chromosomal DNA and K is a normalization constant . From this composite distribution , the peaks with the largest amplitude were identified , and the subset of peaks yielding the maximal F score in the test dataset was defined as the supermarker peak set . Two strategies were used to validate the supermarker procedure . First we calculated the supermarker and the relative peak set on each single proviral dataset and then we evaluated the association with the remaining datasets . The second strategy was a standard 10-fold cross-validation applied to each single dataset . The two evaluations yielded the same results ( Table 5 and Table S5 ) . Further , we compared the strength of association of the supermarker peak set for gammaretroviral datasets to the performance of the Random Forest machine learning algorithm [94] . The two methods obtained superimposable results ( Table S6 , see Methods for details ) . With respect to MLV integration in HeLa cells , H3K4me1 , H3K4me3 , H3K9ac and STAT1 were the markers with the best F scores ( >0 . 80 ) ( Table S1 and S2 ) . Examination of the ChIPSeq peaks derived from all combinations of these five candidates revealed that the best supermarker was generated by combining H3K4me3 , H3K4me1 , and H3K9ac ( 75% wi2kb; p<10−284; F score 0 . 87 ) ( Figure 9 and Table 5 ) . Figure 9A shows the distribution of supermarker density and MLV integration sites across the human genome , with an expansion of chromosome 1 to help visualize detail in Figure 9B . The Pearson correlation for the supermarker density and MLV integration site density across the whole genome was 0 . 75 ( p = 0 , with both functions averaged over a non-overlapping 10 kB window ) . Figure 9C shows the correlation for chromosome 1 in isolation . As with the single marker H3K4me3 , the supermarker yields a maximal F score using a window size of 2 kB ( Figure 4 ) . Inclusion of STAT1 in the HeLa supermarker increased the number of false positives over the number of true positives and thus decreased the composite F score . This suggests that any information carried by STAT1 is contained within the other markers . Among the ChIPSeq data in CD4+ T cells , the best individual markers associated with MLV were H3K4m1 , H3K4m2 , H3K4m3 , H3K9ac , H2BK120ac , H2BK5ac , H3K18ac , H3K27ac , and H2AZ ( all >0 . 80 , Table S1 and S2 ) . The best supermarker for MLV on CD4+ T cells was composed of H3K4m1 , H3K4m2 , H3K4m3 , and H3K9ac ( 71% wi2kb; p<10−122; F score 0 . 84 ) . The F scores reported here ( Tables 3 and 4 ) were calculated using ChIPSeq and provirus datasets that were matched for cell type . In a previous report , when AUC ( ROC ) was used to evaluate epigenetic marks mapped in T cells , the correlation with proviruses cloned from T cells was no greater than the correlation with proviruses cloned from other target cell types such as the human embryonic kidney cell line HEK 293 or the fibrosarcoma cell line HT1080 [90] . Differences due to experimental error were in fact greater than differences due to cell type [90] . To determine if the F score has the ability to discriminate between cell types , MLV provirus data sets from HeLa and CD4+ T cells were compared with the supermarker for each of these cell types , in all combinations . As mentioned above , when an MLV provirus dataset obtained from infection of HeLa cells [43] was compared with the supermarker from HeLa cell ChIPSeq data , very strong association was observed ( 75% wi2kB; p<10−284; F score 0 . 87 ) ( Table 5 and Figure 10 ) . When the same provirus dataset was compared with the supermarker derived from CD4+ T cell ChIPSeq data the strength of the association was much decreased ( 32% wi2kB; p<10−57; F score 0 . 61 ) ( Table 5 and Figure 10 ) . The same pattern was seen for the chimera HIVmINmGag , for which association with the supermarker in HeLa cells ( 70% wi2kB; p<10−263; F score 0 . 86 ) ( Table 5 and Figure 10 ) was much greater than association with the supermarker in CD4+ T cells ( 27% wi2kB; p<10−24; F score 0 . 56 ) ( Table 5 and Figure 10 ) . The opposite pattern was also seen in that MLV proviruses cloned from CD4+ T cells [71] were strongly associated with the supermarker derived in these cells ( 71% wi2kB; p<10−112; F score 0 . 84 ) ( Table 5 and Figure 10 ) , and less well associated with the supermarker from HeLa cells ( 39% wi2kB; p<10−42; F score 0 . 67 ) ( Table 5 and Figure 10 ) . A similar analysis was attempted with provirus datasets for the gammaretroviruses XMRV and PERV ( Table 5 ) . The XMRV provirus data was obtained in the human prostate cancer cell line DU145 [76] and ChiPSeq datasets are not available for these cells . Despite the mismatched cell lines , when the XMRV dataset from DU145 cells was compared with the epigenetic markers mapped in HeLa cells strong correlation was observed with the supermarker ( 66% wi2kB; p<10−190; F score 0 . 83 ) . When the supermarker was derived from CD4+ T cell data , the association with XMRV was much less significant ( 41% wi2kB; p<10−85; F score 0 . 70 ) . Similarly , the PERV provirus dataset cloned from HEK 293 cells was better associated with the supermarker from HeLa cells ( 66% wi2kB; p<10−350; F score 0 . 83 ) than from CD4+ T cells ( 51% wi2kB; p<10−350; F score 0 . 75 ) . To understand why some mismatched cell comparisons gave higher F scores than others , CD4+ T cells , HeLa , DU145 , Jurkat , HEK 293 , and CD34+ hematopoietic stem cells were clustered based on global gene expression profiles ( http://www . ncbi . nlm . nih . gov/geo ) . The resulting dendrogram ( Figure S2 ) demonstrated that the cells clustered into two groups , one consisting of HeLa , DU146 , and HEK 293 cells , and the other CD4+ T cells , Jurkat cells , and CD34+ cells . Based on expression profiles DU145 cells are more similar to HeLa cells than to CD4+ T cells , offering an explanation for the higher F score when XMRV was compared with HeLa . As a first step towards examining the utility of the supermarker in the context of published clinical or experimental data , supermarker density was examined in proto-oncogenes that have been activated by retroviral insertion . 20 SCID-X1 patients were successfully treated with autologous bone marrow CD34+ hematopoietic stem cells transduced ex-vivo with an MLV vector expressing the therapeutic gene IL2RG . 5 of these patients developed T cell leukemia and 4 possessed insertional mutations from the MLV vector at LMO2 [24]–[28] , a T cell oncogene [95] . The fifth patient had a provirus near CCND2 , another lymphoid oncogene [96] that encodes cyclin D2 . When ChIPSeq datasets from HeLa cells were used to generate the supermarker , no high probability sites were identified near the promoters of LMO2 or CCND2 ( Figure 11 ) . For LMO2 the nearest sites in HeLa cells were >150 kbp upstream and >200 kbp downstream of the TSS . For CCND2 the nearest sites in HeLa were >800 kbp upstream and >50 kbp downstream of the TSS . Sufficient ChIPSeq datasets to generate a supermarker were not available for CD34+ hematopoietic stem cells . Given the relative similarity of the transcription profile ( Figure S2 ) we used the supermarker data generated from CD4+ T cells . The F score when crossing from CD34+ cells to CD4+ cells decreases from 0 . 85 to 0 . 78 ( 57% wi2kb , p<10−102 ) , but is much better than when using HeLa cell data ( 38% wi2kB; p<10−48 ; F score 0 . 66 ) . With respect to the LMO2 TSS a very prominent supermarker peak was observed at −1730 bp ( Figure 11A ) . Based on the probability of the supermarker we estimate that 1 out of 105 MLV proviruses would target this gene in CD34+ cells or CD4+ T cells , as compared to a much less frequent 1 out of 107 MLV proviruses in HeLa cells . Nearly identical probabilities were calculated based on experiments in which MLV proviruses were cloned from T cell lines and HeLa cells [97] . These authors observed a hotspot for MLV integration located between −1740 to −3000 of the LMO2 promoter within CD4+ T cells but not within HeLa . Though experimental data for calculating the probability of integration into CCND2 is not available , it is interesting that multiple , high-probability supermarkers are located wi2kB of the promoter ( Figure 11B ) .
Prior to this study , the best predictor for retroviral integration site selection was the association of TSS/CpG with gammaretroviruses such as MLV [31] , [43] , [71] . Given a window of 2 kB , TSS/CpG predicts 21 to 27% of MLV integration sites . But even this modest prediction comes with the cost of a high background rate ( low precision ) and consequently a borderline F score ( 0 . 51 under the best conditions ) . In contrast , H3K4me3 predicts 63 to 68% of MLV integration sites with high precision ( F score 0 . 84 ) . H3K4me1 predicts 90% of MLV integration sites but , in isolation , this marker has a higher background rate ( F score 0 . 78 ) due to the larger size of the H3K4me1 ChIPSeq dataset ( 300 , 000 binding sites for H3K4me1 versus 70 , 000 for H3K4me3 ) . Previous studies have reported the same histone modifications as markers associated with integration sites [81] , [90] . The Precision-Recall methods used here have been shown to be better suited than ROC when negative results far exceed positive ones [82] . Precision-Recall methods have been shown to perform better than ROC in a number of other areas in biology , including the prediction of functional residues within proteins [98] or predicting the function of genes [99] . In our case , the resolution offered by the Precision-Recall-based F score allowed us to rank markers according to statistical significance ( Text S1 ) . Then , by ranking markers with respect to their F score , we were able to combine them to generate a supermarker which predicts 75% of MLV integration sites wi2kB with very high precision ( F score 0 . 87 ) . It will certainly be important to find an explanation for the remaining 25% of integration sites not accounted for by the markers identified here . The supermarker was used here to predict the probability of gammaretroviral integration into a specific locus , in a cell-type specific manner ( Figure 11 ) . Our in silico probability estimates for integration near a particular proto-oncogene , LMO2 , were nearly identical to the probabilities calculated from experimental data [97] , and even concurred with respect to the cell-type specificity of the experimentally determined probability . Additional experimental confirmation of supermarker predictions is called for but the case of LMO2 suggests that the supermarker is indeed the first powerfully predictive tool for retroviral integration site selection . A supermarker generated from cell-type-specific ChIPSeq data for a handful of markers has the potential to transform how decisions are made concerning clinical gene-therapy trials . The calculations here were based on distinct datasets from multiple sources ( Tables 1 and 2 ) . It is possible that by generating matched datasets , i . e . , integration datasets and ChiPSeq datasets from identical cells and by the same laboratory , or by combining ChIPSeq data for new factors in new combinations , the ability of the supermarker to predict integration sites will be improved even further . On the other hand , STAT1 , a powerful marker in isolation , increased the false positive rate and decreased the F score . In addition to the ChIPSeq datasets in Table 1 , we checked if the F score was improved by examining other previously reported features , including GC content , AT content , putative consensus sequences for integration or transcription factors [80] , [100] . When a window of 2kB was considered , these features failed to yield a significant F score ( all were ≤0 . 5 ) for all of the retroviral provirus datasets , and these factors considerably lessened the F score when combined with the highly associated markers ( Table S7 ) . The strength of the associations with H3K4me3 , H3K4me1 , and H3K9ac indicates that gammaretroviral integration is not a quasi-random process , but rather , a deterministic process that follows the epigenetic histone code . Though some of these histone modifications are linked to transcriptionally active promoters [64] , [87]–[89] , the link to transcription per se seems not to be relevant since 60 to 70% of supermarker loci are not associated with TSS/CpG . Consistent with this point , our supermarker is highly associated with the LMO2 promoter in CD4+ T cells , but not in HeLa cells , and these cell-type-specific differences in marker binding do not correlate with differential LMO2 expression in these cells [97] . The 2 kB window maxima for the F score of the supermarker is intriguing and suggests that it is a physical property of chromatin that is favored for integration by gammaretroviruses , perhaps linked to the position of the supermarker relative to nucleosomes or bent DNA [34] , [36]–[38] . The factors constituting the supermarker , along with the other histone modifications listed in Tables S1 and S2 that are also associated with MLV integration , suggest a mechanistic link between gammaretroviral integration and chromatin-associated complexes with H3K4 methyltransferase and histone acetyltransferase activity . H3K4 methylation is clearly linked with histone acetylation , in that promoters which are methylated are much more likely to become acetylated [65] and knockdown of WDR5 , a factor required for H3K4 methylation [101] leads to altered histone acetylation [65] , [102] . Methylation may recruit chromatin remodeling complexes [103] , [104] , the methylated histone may be bound by the acetylases [105] , or acetylases may be components of the methylase complex itself [101] . CBP/p300 is associated with H3K4 methyltranferase activity in vivo [106] , [107] . ChIPSeq data on acetyltransferases shows a weak but significant association between CBP and MLV integrations in CD4+ T cells ( F score 0 . 68 , Table S4 ) . Interestingly , combination of CBP and p300 leads to an aggregated F score of 0 . 75 . Thus , any of these chromatin associated factors , methylated histones , methylases , chromatin remodeling complexes or acetylases are candidates for gammaretroviral IN-binding factors . Interestingly , HIV-1 IN associates with , and is acetylated by , p300 [108] but the p300 ChIPSeq binding profile was not associated with the HIV-1 proviral datasets ( F score 0 . 34 ) . Though very strong association was observed when any of the gammaretroviruses were compared with STAT1 binding sites , adding this transcription factor to the supermarker did not improve the F score . This is perhaps because any retroviral targeting information derived from STAT1 binding sites is already present in the modified histone H3 . 90 to 95% of the STAT1 binding sites are in fact within 2 kB of the nearest H3K4me1 site . Our attempts to detect STAT1 binding to MLV IN , or to see effects of STAT1 disruption on MLV infectivity were unsuccessful . Taken together it seems likely that STAT1 itself is not mechanistically involved in gammaretrovirus integration . More likely , STAT1 homes to chromosomal regions that are also preferred targets for integration by these viruses . STAT1 has a complex relationship with the histone acetylase CBP/p300 . Acetylation of histones is required for STAT1-mediated transcription [89] , [109] but STAT1 itself binds CBP/p300 [110] and is also acetylated and this contributes to its inactivation [111] . The best single marker for HIV-1 in HeLa cells , H3K4me1 , predicted 48% of proviruses wi2kB but with only moderate precision ( F score 0 . 60 ) . Using the F score we were able to detect a stronger association of HIV-1 with H3K4me1 in CD4+ T cells ( 57% wi2kB , p<10−71 , F score 0 . 73 ) but combining markers in an attempt to generate a supermarker failed to improve the F score . The associations that were observed may be related to HIV-1's propensity to integrate along the length of transcriptionally active genes [81] , [90] . Association with histone modifications at active promoters may be detected given short enough gene-length , or a wide-enough window around the provirus ( Figure 5 ) . Either way , we were unable to identify a marker capable of predicting HIV-1 integration site selection wi2kB . Perhaps the HIV-1 IN-interacting protein PSIP1/LEDGF/p75 [53]–[55] would be such a factor . Though binding sites have been reported for LEDGF [112] , this dataset is limited to 1% of the human genome and cannot be used for a genome-wide association study . LEDGF influences HIV-1 integration site selection in that its disruption causes a shift away from transcriptional units and towards CpG-rich sequences [56] , [58] , [59] . Nonetheless , these are relatively general effects and LEDGF binding sites may fail to give resolution down to a window of 2 kB . It appears that integration site selection by HIV-1 is mechanistically quite different than for the gammaretroviruses .
The analysis of integration sites was based on the published integration datasets in Table 2 . In the analysis performed here , to control for possible bias introduced during the cloning of the integration sites , 10 control sites in the human genome were generated for each integration site , as previously described [42] , [43] , [78] , [80] . These control , in silico-generated sites were used to calculate the significance and the F score ( see below ) . These genomic features were obtained from Annotated Genome version hg18 for human ( http://genome . ucsc . edu/ ) . CpG island and transcription start sites were combined into single datasets for determining association with retrovirus integration sites . ChIPSeq peaks were derived from published ChIPSeq datasets ( Table 1 ) with a robust and fast algorithm , F-Seq [113] running with default parameters and standard Poisson statistics . We recalculated the peaks even when the peak set was already available to confirm the reproducibility of published procedures . Two-sided Fisher exact test ( or χ2 approximation when appropriate ) was used to evaluate statistical significance . All p-values were Bonferroni corrected for multiple testing . p-values<0 . 01 were considered significant . To measure marker performance with respect to a given retroviral integration dataset , we used the -score ( van Rijsbergen 1979 ) . It is defined as the β-weighted harmonic mean of Precision and Recall ( 1 ) where tp is the number of actual integration sites within 2 kB from a specified factor; tn is the number of control datapoints ( generated in silico as described above ) >2 kB from a specified factor; fp is the number of control datapoints within 2 kB from a specified factor and fn is the number of actual integration sites >2 kB from a specified factor . We set β = 0 . 5 to give more weight to Precision than to Recall . This balances type I and type II errors by adjusting for the high rate of False Positives ( fp ) inherent in the examination of large datasets for genome-wide binding sites according to statistical significance ( Text S1 ) . Moreover , to overcome the limitation of standard statistical methods we normalized fp with respect to the number of actual integration sites . The normalized -score is finallywith V and C being , respectively , the number of effective and control integration sites . The resulting F score is almost constant with respect to the size and ratio of experimental and control datasets ( Figure 7 ) . It is worth noting that a null-predictor yielding ( i . e . a marker composed of all bases in the genome ) gives P = 0 . 5 and R = 1 , resulting in an F score0 . 5 . A marker is considered significant if the F score lies between 0 . 5 and 1 . 0 . Different metrics can be used to measure the association between proviruses and given markers . We opted to identify the metric among F0 . 5 , F1 , F2 , Area Under Curve ( AUC ) , Area Under Precision/Recall ( AUPR ) , Odds Ratio ( OR ) , Shannon Mutual Information ( SMI ) , and Difference of Proportions ( DOP ) that best agrees with statistical significance . The association between markers and proviruses was measured according to each of the above-mentioned metrics . Then the markers were ranked by comparing the measure associated to the i-esim marker with that associated with the j-esim marker and filling in an NXN matrix M for each measure . Formallywhere X is one of the considered metrics . As a reference , a similar matrix was built using the p-value ( significance ) obtained by Fisher's exact test , defined for the i-esim marker as . ThusA simple measure of similarity between metric X and reference S was calculated by ( sum spans over all matrices elements ) . Observe that . The mass probability functions p ( V = i ) or p ( M = i ) are defined as the probability of a provirus V or a marker M to be localized at a given genomic location defined as i≡ ( chromosome , position ) . p ( V = i ) is estimated from the linear combination of mass probability functions for candidate markers , that isCoefficient measures the goodness of fit of the marker and it seems reasonable to write as a function of the related F score . Indeed the probability of integration P ( V ) can be written aswith respect to a set of markers M1 , M2 , … , MN . Adding these equations we get the mixture model ( 2 ) Now , from ( 1 ) and we havethenA first order approximation of ( 2 ) is thenwhere K is a normalization constant . Eventually we set and the resulting new probability mass function is ( 3 ) The marker mass density was modeled as the sum of Gaussian functions centered on ChIPSeq peaks , with the variance set as the average size of the peak regions , as determined by the F-seq algorithm [113] . In this way we minimized the potential bias that can arise by summing ChIPSeq densities obtained over different experimental conditions . Briefly , each marker probability density function was written aswhere Γ is the peak set of the marker M . This function ( 3 ) summarizes the properties of all the markers and can be interpreted as a new ChIPSeq density . Indeed it contains all markers associated and not associated peaks . To reduce the number of false positives we applied a thresholding procedure similar to that used to filter raw ChIPSeq data in a training set of experimental and control integration sites . The peaks of function ( 3 ) were ranked with respect to their amplitude and the F score is recalculated on the training set as a function of the number of peaks . We define the supermarker M* as the marker set that yields a maximal F score . The supermarker density function is finally written as ( A ) where Γ* is the reduced peak set . To validate the model , we adopted two strategies . First we calculated the supermarker and the relative reduced peak set on each single proviral dataset and then we evaluated the association with the remaining datasets . The second strategy was a standard 10-fold cross-validation applied to each single dataset . To validate the effectiveness of the supermarker peak set , we trained RandomForest [94] , a machine learning algorithm , with the same set of markers composing the supermarker . Our datasets are extremely imbalanced and this results in a classifier with an high misclassification error for predicting the minority class ( i . e . the experimental dataset ) as shown in Table S6 . In order to correct for that , RandomForest can be tuned by an additional parameter , classwt , that can be used to assign priors to the classes ( experimental and control ) to minimize the misclassification error and improve the performance . We adopted a 10-fold cross-validation procedure by correcting the priors in the training set . Interestingly , the maximum achievable F score and the number of associated integration sites wi2kb match almost exactly with the F score and wi2kb that we obtained with our supermarker procedure . We consider this as further evidence of the effectiveness of the supermarker . PWM for retroviruses and human transcription factors was borrowed from [80] and from the JASPAR database ( jaspar . cgb . ki . se ) . All computation and graphics were done with ad-hoc Python scripts with the support of the motility library for PWM calculations ( cartwheel . caltech . edu/ motility ) , Matplotlib library for graphical and scientific computing ( matplotlib . sourceforge . net ) and the Random Forest implementation on R environment ( http://cran . r-project . org/web/packages/randomForest/ ) . Chromosome projection mandalas ( Figure 1 ) represent the distribution across of the genome of binding sites for a specific factor or histone modification on the circumference of a circle . Each dot represents a retroviral integration site with the following polar coordinates: angular distance corresponds to genomic location on the indicated chromosome; radial distance from the contour of the circle is the log-scaled distance in nucleotides from the closest marker site . Diagrams have been set to visualize proviruses located between 0 and 1 megabase . Proviruses located more than 1 megabase from the nearest marker accumulate at the center of the mandala . | When HIV-1 , murine leukemia virus ( MLV ) , or other retroviruses infect a cell , the virus generates a DNA copy of the viral RNA genome and ligates the cDNA within host chromosomal DNA . This integration reaction occurs at sites throughout the host cell genome , but little is known about how integration sites are selected . We attempted to identify markers predictive of retroviral integration by comparing the genome-wide binding sites for more than 60 factors with 14 retroviral integration datasets . We borrowed Precision-Recall methods from the Information Retrieval field for extracting information from highly skewed datasets such as these . For MLV and other gammaretroviruses , strong association was observed with STAT1 , acetylation of H3 and H4 at several positions , and methylation of H2AZ , H3K4 , and K9 . We generated a supermarker by combining high scoring markers . The supermarker localized within 2 kB of 75% of MLV proviruses and predicted the likelihood of integration within specific chromosomal regions in a cell-type specific manner . This study identified chromosomal features highly favored for retroviral integration . It also provides clues to the mechanism by which retrovirus integration sites are selected , and offers a tool for predicting cell-type specific proto-oncogene activation by retroviruses . | [
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] | 2010 | Deciphering the Code for Retroviral Integration Target Site Selection |
Spinocerebellar ataxia type 3 ( SCA3 ) , also known as Machado-Joseph disease ( MJD ) , is an untreatable autosomal dominant neurodegenerative disease , and the most common such inherited ataxia worldwide . The mutation in SCA3 is the expansion of a polymorphic CAG tri-nucleotide repeat sequence in the C-terminal coding region of the ATXN3 gene at chromosomal locus 14q32 . 1 . The mutant ATXN3 protein encoding expanded glutamine ( polyQ ) sequences interacts with multiple proteins in vivo , and is deposited as aggregates in the SCA3 brain . A large body of literature suggests that the loss of function of the native ATNX3-interacting proteins that are deposited in the polyQ aggregates contributes to cellular toxicity , systemic neurodegeneration and the pathogenic mechanism in SCA3 . Nonetheless , a significant understanding of the disease etiology of SCA3 , the molecular mechanism by which the polyQ expansions in the mutant ATXN3 induce neurodegeneration in SCA3 has remained elusive . In the present study , we show that the essential DNA strand break repair enzyme PNKP ( polynucleotide kinase 3’-phosphatase ) interacts with , and is inactivated by , the mutant ATXN3 , resulting in inefficient DNA repair , persistent accumulation of DNA damage/strand breaks , and subsequent chronic activation of the DNA damage-response ataxia telangiectasia-mutated ( ATM ) signaling pathway in SCA3 . We report that persistent accumulation of DNA damage/strand breaks and chronic activation of the serine/threonine kinase ATM and the downstream p53 and protein kinase C-δ pro-apoptotic pathways trigger neuronal dysfunction and eventually neuronal death in SCA3 . Either PNKP overexpression or pharmacological inhibition of ATM dramatically blocked mutant ATXN3-mediated cell death . Discovery of the mechanism by which mutant ATXN3 induces DNA damage and amplifies the pro-death signaling pathways provides a molecular basis for neurodegeneration due to PNKP inactivation in SCA3 , and for the first time offers a possible approach to treatment .
Spinocerebellar ataxia type 3 ( SCA3 ) , also known as Machado-Joseph disease ( MJD ) , is an autosomal dominant neurodegenerative disease caused by CAG repeat expansion in the C-terminal coding region of the ATXN3 gene [1–3] . SCA3 is the most common dominantly inherited ataxia world-wide , and a late-onset disease that manifests with cerebellar ataxia , peripheral nerve palsy , and pyramidal and extrapyramidal signs [1–4] . SCA3 neurodegeneration is primarily observed in the brainstem , cerebellum , basal ganglia and spinal cord [5–8] . Ataxia symptoms appear between the ages of 20 and 50 years , and manifest with cerebellar ataxia , opthalmoplegia , dysarthria , dysphagia , dystonia , rigidity and distal muscle atrophies [1–3 , 8 , 9] . The wild-type ATXN3 gene encodes 12 to 41 CAG repeats in its 10th exon at the human chromosomal locus 14q32 . 1 [3] . ATXN3 is a deubiquitinating enzyme that edits specific poly-ubiquitin linkages [10 , 11] . It has also been linked to transcriptional regulation [9 , 12] . However , ATXN3 does not seem to be essential for brain development and function , as mice lacking ATXN3 do not develop overt neurological phenotypes [13] . Therefore , the exact function of ATXN3 remains unknown , limiting efforts to establish the possible role of mutant ATXN3 in eliciting neuronal death in SCA3 . In SCA3 , the polymorphic CAG repeats are expanded to 62 to 84 glutamines and the mutant ATXN3 forms aggregates that are deposited in SCA3 neurons [2 , 3] . A large body of literature supports the hypothesis that multiple proteins aberrantly interact with the mutant ATXN3 and that the loss of function of the mutant ATXN3-interacting proteins contributes to neurodegeneration and SCA3 pathology [2 , 8–9] . Recent studies have reported that depletion of the mutant ATXN3 allele in a SCA3 transgenic mouse brains rescues the molecular phenotypes of SCA3 supporting the hypothesis that mutant ATXN3 elicits toxicity and neuronal dysfunction in SCA3 [14] . Recent studies have also shown that the mutant ATXN3 causes p53-mediated neuronal death in vitro and in vivo by activating the transcription of the p53-inducibe pro-apoptotic genes such as BAX ( Bcl2-associated X protein ) and PMAIP1 ( PUMA , p53 upregulated modulator of apoptosis ) , triggering mitochondrial apoptotic pathways [15 , 16] . However , the mechanism by which mutant ATXN3 increases p53 phosphorylation and activates the p53-dependent pro-apoptotic signaling pathways to facilitate neuronal death and dysfunction remains unknown . In the present study we show that PNKP ( Polynucleotide kinase 3’-phosphatase ) , a dual- function DNA strand break repair enzyme [17 , 18] , is a native ATXN3-interacting protein , and is inactivated by its interaction with the mutant ATXN3 in SCA3 . Our data also show that PNKP is also present , in part in the polyQ aggregates in SCA3 brain . Diminished PNKP activity results in persistent accumulation of DNA strand breaks , leading to chronic activation of the DNA damage-response ataxia telangiectasia mutated ( ATM ) protein kinase and the downstream pro-apoptotic p53-dependent signaling pathways in SCA3 . Additionally , activated ATM stimulates phosphorylation of c-Abl tyrosine kinase , which phosphorylates and facilitates nuclear inclusion of protein kinase C delta ( PKCδ ) , further amplifying pro-apoptotic output in SCA3 . Either overexpression of PNKP or pharmacological inhibition of ATM in mutant ATXN3-expressing cells blocked aberrant activation of the pro-death pathways and reduced cell death , suggesting that mutant ATXN3-mediated chronic activation of the DNA damage-response ATM signaling pathway plays a pivotal role in neuronal dysfunction and neurodegeneration in SCA3 . Therefore , our current study not only provides an insight into the mechanism of neurodegeneration in SCA3 , but also delineates potential drug targets for developing mechanism-based efficacious therapeutic modalities to combat systemic degeneration of neuronal cells in SCA3 .
Our studies described in the accompanying manuscript by Chatterjee et al suggest that PNKP is a native ATXN3-interacting protein , and that ATXN3 modulates PNKP activity and DNA repair ( Chatterjee et al , Figs . 1–3 ) . Immunoprecipitation of PNKP from the nuclear extract from human neuroblastoma SH-SY5Y cells and subsequent mass spectrometric analysis showed the presence of ATXN3 in the immunoprecipitated ( IP ) pellet; conversely , immunoprecipitation of ATXN3 and Western blot analysis revealed the presence of PNKP in the ATXN3 IP ( Chatterjee et al , Figs . 1 , S1 , 2A and 2B ) . Further , GST pull-down from the nuclear extract , followed by Western blot analysis , indicated that both wild-type and mutant ATXN3 directly interact with PNKP in vitro , ( Chatterjee et al; Fig . 2D ) . The wild-type ATXN3 protein stimulated , and in contrast , the mutant ATXN3 dramatically diminished , the 3’ phosphatase activity of PNKP in vitro ( Chatterjee et al; Figs . 3A and 3B ) . The interaction between these two proteins was further validated in SH-SY5Y cells co-transfected with the plasmids pCherry-PNKP and pGFPC-ATXN3–28 , expressing cherry-tagged PNKP and GFP-tagged ATXN3-Q28 , respectively , and imaged by confocal microscopy . Analysis of the transfected cells showed significant co-localization of the red fluorescence of PNKP with the green fluorescence of ATXN3-Q28 ( Fig . 1A ) . Similarly , cells co-transfected with pCherry-PNKP and pGFP-ATXN3-Q84 ( a plasmid expressing mutant ATXN3-Q84 encoding 84 glutamines ) showed marked co-localization of PNKP and ATXN3-Q84 ( Fig . 1B ) . However , co-transfection of plasmid pCherry-PNKP and pAcGFPC1 ( an empty control vector expressing GFP ) did not show any detectable reconstitution of yellow/orange fluorescence ( S1 Fig . ) , suggesting specificity of these interactions . Together , these data support our previous interpretation that both wild-type and mutant ATXN3 interact with PNKP in the cell ( Chatterjee et al ) . To further confirm the interaction of PNKP and ATXN3 in cell , we performed bi-molecular fluorescence complementation ( Bi-FC ) assays , a versatile method to assess in cell protein-protein interactions [19] . We cloned PNKP cDNA with the N-terminal amino acids of modified GFP into plasmid pBiFC-VN173 , and ATXN3 cDNA ( encoding 28 and 84 glutamines ) with the C-terminal amino acids of modified GFP into plasmid pBiFC-VC155 ( a description of these Bi-FC plasmids is provided in the Methods section ) . Transfection of pVN173-PNKP , pVC155-ATXN3-Q28 or pVC155-ATXN3-Q84 into SH-SY5Y cells individually did not reconstitute green/yellow fluorescence ( Fig . 1C , panels 1–3 ) . In contrast , co-transfection of plasmids pVN173-PNKP and pVC155-ATXN3-Q28 effectively reconstituted green/yellow fluorescence ( Fig . 1C , panel 4 ) . Importantly , co-transfection of plasmids pVN173-PNKP and pVC155-ATXN3-Q84 also resulted in robust reconstitution of green/yellow fluorescence ( Fig . 1C , panel 5 ) . These data substantiate our interpretation that both wild-type and mutant ATXN3 interact with PNKP in the cell . Furthermore , we analyzed these protein-protein interactions in SCA3 patients’ brain sections by proximity ligation assays ( PLA ) , a widely used technique to assess in vivo protein-protein interactions [20] . The PLA analysis clearly shows a robust reconstitution of red fluorescence in both SCA3 and normal control brains , suggesting an in vivo interaction between ATXN3 and PNKP ( n = 3; Fig . 1D ) . Importantly , about 70% of the ATXN3-PNKP complexes were detected in the nuclei in the control brain sections ( Fig . 1D; panel 2 and 3 ) . By contrast , PLA analysis of the SCA3 patients’ brain sections shows that the ATXN3-PNKP complexes are predominantly present in periphery or outside the nuclei ( n = 3 , Fig . 1D ) . Since PNKP is present in the mitochondria [18] , the extra-nuclear signals detected in the control brain sections presumably are from the PNKP-ATXN3 complexes present in the mitochondria . To further verify the specificity of the in vivo interaction of ATXN3 and PNKP , we performed PLA analysis to check the interaction of ATXN3 with DNA ligase 3α ( DNA LIG 3α ) , another critical DNA strand break repair enzyme present in the PNKP complex ( Chatterjee et al; Figs . 2A , 2B and S2 ) . The PLA analysis showed no significant interaction of ATXN3 with DNA LIG 3α in the brain sections from SCA3 patients , or in control brains under identical experimental conditions ( Fig . 1D; panels 1 and 4 ) , suggesting specificity of the interactions between ATXN3 and PNKP in vivo . Consistent with these data , PLA analysis also suggested specific and pronounced interactions of ATXN3 and PNKP in SH-SY5Y cells ( accompanying manuscript , Chatterjee et al , Fig . 2C ) . The in vivo interaction of PNKP and ATXN3 in SCA3 and control brain sections was further confirmed by immunostaining brain sections from SCA3 patients and control subjects with specific antibodies , followed by confocal microscopy . For immunostaining the brain sections we used an anti-PNKP antibody that shows high specificity for PNKP as evidenced by Western blot and immunohistochemical analyses ( S2 Fig . ) . Image analysis revealed a distinct co-localization of PNKP with ATXN3 in the cerebellum of normal control brain and SCA3 ( expressing mutant ATXN3 with 72 glutamines , ATXN3-Q72 ) brain sections ( Figs . 2A and 2B ) . Likewise , analysis of SCA3 brain expressing either ATXN3-Q79 or ATXN3-Q84 also showed discrete co-localization of ATXN3 with PNKP ( S3 Fig . ) . Importantly , consistent with the PLA data as described in Fig . 1D , majority ( 70 to 80% ) of the ATXN3-PNKP complexes were detected in the periphery and/or outside of nuclei in the SCA3 brain sections ( Figs . 2B and S3 ) ; in contrast , the ATXN3-PNKP complexes were predominantly detected inside the nuclei in the control brain sections ( n = 3; Figs . 2A and S3 ) . We next assessed in vivo interactions of ATXN3 and PNKP in transgenic mouse brains expressing mutant ATXN3 , as well as in wild-type control mouse brains . Previous studies have shown that this novel SCA3 mouse model ( CMVMJD135 ) develops SCA3-like motor incoordination and exhibits neurodegeneration in spite of the absence of aberrant cleavage of the mutant ATXN3 and accumulation of polyQ aggregates in brain [21] . We observed a distinct co-localization of PNKP with ATXN3 in the deep cerebellar nuclei area of the SCA3 mouse brain , as well as in age-matched control brain sections ( S4 Fig . ) . To assess whether PNKP is present in the polyQ aggregates in SCA3 patients’ brains , brain sections from SCA3 and age-matched normal subjects were co-immunostained with an anti-polyQ antibody ( 5TF1–1C2; green ) and anti-PNKP antibody ( red ) . Confocal image analysis showed distinct co-localization of PNKP- and polyQ aggregates in brain sections from SCA3 patients , but not in control brain sections ( Figs . 2C and 2D ) . The much less intense fluorescence signals observed in the brain sections from control subjects ( Fig . 2C ) presumably are from the shorter polyQ sequences present in the wild-type proteins , and do not show detectable co-localization with PNKP . Collectively , these data suggest that PNKP is a native wild-type ATXN3-interacting protein that also interacts with the mutant ATXN3 , and at least in part is recruited into the polyQ aggregates in the SCA3 brain . Recent studies have shown elevated levels of DNA damage/strand breaks in peripheral blood lymphocytes in SCA3 patients [22] , indicating that mutant ATXN3 can induce DNA damage . Our data in the accompanying manuscript by Chatterjee et al suggest that mutant ATXN3 binds PNKP and inhibits its 3’-phosphatase activity ( Chatterjee et al , Figs . 2D and 3B ) . We thus examined SH-SY5Y cells expressing ATXN3-Q84 , brain sections from SCA3 patients , as well as SCA3 transgenic mouse brains , for the presence of DNA damage . Oxidative DNA damage or double-strand breaks rapidly induce the phosphorylation of several damage-response kinases and thereby facilitate protein-protein interactions that collectively regulate a signaling cascade to repair DNA lesions . ATM is one of the major DNA damage-response kinases , and is rapidly activated by autophosphorylation at S1981 after genomic damage [23] . Genomic DNA damage or strand breaks also result in rapid phosphorylation of histone H2AX and p53-binding protein 1 ( 53BP1 ) , and the phosphorylated H2AX ( γH2AX ) and 53BP1 ( p-53BP1 ) are quickly recruited into damage sites and visualized as nuclear foci in damaged cells [23] . Since mutant ATXN3 interacts with and inactivates PNKP , we next investigated whether ectopic expression of mutant ATXN3 induces DNA damage . To this end we developed SH-SY5Y cells expressing ATXN3-Q28 and ATXN3-Q84; Western blotting and confocal image analysis confirmed effective expression of the wild-type ATXN3-Q28 as well as mutant ATXN3-Q84 in these cells ( Figs . 3A and 3B ) . To assess the accumulation of genomic DNA damage in cells expressing mutant ATXN3 , we used anti-phospho-53BP1 ( p-53BP1-S1778 ) antibody to perform immunohistochemical ( IHC ) analysis on the SH-SY5Y cells expressing wild-type vs . mutant ATXN3 . We observed about a 5-fold increase in 53BP1 focus formation in the SH-SY5Y cells expressing ATXN3-Q84 over the cells expressing ATXN3-Q28 ( Figs . 3C and 3D; the foci are shown by arrows ) . IHC analysis also revealed significantly more ( ~10-fold ) γH2AX foci in the mutant ATXN3-expressing cells compared to control cells ( Figs . 3E and 3F ) . Consistent with these results , immunohistological analysis of SCA3 brain sections with phospho-53BP1 ( p-53BP1-S1778 ) antibody also showed widespread 53BP1 nuclear foci , unlike controls ( n = 3 ) ( S5 Fig . ; the foci are shown by arrows ) . Further , comet analysis of neuronal cells from the deep cerebellar nuclei from a SCA3 transgenic mouse brain revealed the presence of DNA damage ( S6A and S6B Figs . ) . Compared to control cells , DNA damage in the mutant cells was significantly increased when exposed to hydrogen peroxide ( S6C , S6D and S6E Figs . ) . To further test our hypothesis that sequestration of PNKP can compromise the cellular DNA damage repair ability , resulting in increased accumulation of DNA lesions , we depleted PNKP in SH-SY5Y cells with siRNA . Western blotting confirmed about 70 to 80% depletion of PNKP in the PNKP-siRNA-treated cells ( S7A and S7B Figs . ) . These cells showed about a 5-fold increase in the formation of 53BP1 foci compared to the control siRNA-treated cells ( S7C and S7D Figs . ) . Likewise , the PNKP-depleted cells also showed about 10-fold more γH2AX focus formation vs . cells transfected with control-siRNA ( S7E and S7F Figs . ) . These data clearly suggest that the perturbation of PNKP activity by the mutant ATXN3 impairs DNA repair efficacy and facilitates the accumulation of DNA strand breaks in SCA3 . Activated ATM coordinates cell cycle progression with the damage-response checkpoints and DNA repair to preserve genomic integrity , via a well-orchestrated signaling network [23] . To investigate whether mutant ATXN3 activates ATM signaling in SCA3 , we expressed ATXN3-Q84 in differentiated SH-SY5Y cells and assessed activation of the ATM pathway . Expression of ATXN3-Q84 strongly activated the ATM pathway , inducing the phosphorylation of ATM and H2AX and ATM’s downstream substrates Chk2 and p53 ( Figs . 4A and 4B ) . By contrast , expression of wild-type ATXN3-Q28 did not activate the ATM pathway ( Figs . 4C and 4D ) , suggesting that mutant ATXN3 strongly activates the DNA damage-response pathway and the polyQ sequence length is important for ATM pathway activation . Likewise , expression of the mutant ATXN3 carrying 72 and 80 poly-glutamines ( ATXN3-Q72 and ATXN3-Q80 ) in SH-SY5Y cells also strongly activated the DNA damage-response ATM pathway ( S8 Fig . ) . Furthermore , to test whether mutant ATXN3 activates p53 and Chk2 via activating ATM , we pre-treated the cells with ATM inhibitor Ku55933 and expressed ATXN3-Q84 and assessed the activation of DNA damage response pathway . Consistent with our hypothesis , ATXN3-Q84 expression failed to stimulate phosphorylation of Chk2 and p53 in the presence of the ATM inhibitor Ku55933 ( S9 Fig . ) , substantiating our interpretation that mutant ATXN3 stimulates the DNA damage response p53 pathway via activating ATM . The dramatic increase in ATM , H2AX , Chk2 and p53 phosphorylation ( Figs . 4A and S8 ) and formation of 53BP1 and γH2AX foci ( Fig . 3 ) in response to mutant ATXN3 expression suggest that mutant ATXN3-induced genomic DNA strand breaks/damage is sufficient to activate the DNA damage- response pathway . Further , analysis of the tissue from the deep cerebellar nuclei ( DCN ) from SCA3 transgenic mice ( CMVMJD135 mice ) constitutively expressing mutant ATXN3 showed robust activation of the ATM pathway ( increased phosphorylation of ATM , H2AX and p53 ) ( Figs . 4E and 4F ) , suggesting that mutant ATXN3 strongly activates the DNA damage-response pathway in vivo . To further test whether inactivation of PNKP by mutant ATXN3 stimulates the ATM pathway , we examined PNKP-siRNA-treated differentiated SH-SY5Y cells for ATM pathway activation . Our data showed robust activation of the ATM and p53 pathways in cells transfected with PNKP-siRNA , but not in cells transfected with control-siRNA ( S10 Fig . ) . To rule out the possibility that DNA damage and subsequent activation of the DNA damage response might be due in part to non-specific off-target toxic effects of the PNKP-siRNA , we used micro-RNA-adapted RNA interference ( shRNAmir ) to achieve more specific knockdown of PNKP in cells , and assessed activation of the DNA damage-response pathway in these cells . Similar to our previous observation described in S7 Fig . , depletion of PNKP in SH-SY5Y cells with PNKP-shRNAmir constructs also resulted in increased genomic DNA damage ( 53BP1 and γH2AX foci formation; shown by arrows; S11 Fig . ) , and marked activation of the DNA damage-response ATM pathway ( S12 Fig . ) . Moreover , recent studies have indicated that a mutant ATXN3-mediated increase in oxidative stress might be responsible for inducing DNA damage and SCA3 pathology [22] . Since oxidative stress alone can activate the ATM pathway [24] , we sought to determine whether mutant ATXN3 activates ATM via an oxidation-dependent mechanism . To test this possibility , we induced ATXN3-Q84 expression in differentiated SH-SY5Y cells pre-treated with the antioxidant N-acetyl cysteine ( NAC ) . However , pre-treating cells with NAC did not block mutant ATXN3-mediated activation of the DNA damage-response pathway ( S13A and S13B Figs . ) . Likewise , expression of ATXN3-Q84 strongly activated the ATM pathway in cells overexpressing the antioxidant enzyme catalase ( S13C and S13D Figs . ) , suggesting that the mutant ATXN3-induced DNA damage-response ATM pathway activation is oxidation-independent . The transcription factor p53 is the primary target molecule in the ATM pathway , and many of the functions of ATM are p53-dependent . Activated p53 regulates a variety of cellular processes , such as transcription , cell cycle regulation , DNA damage-response repair and cell death [25–27] . The mutant polyQ proteins have been shown to induce p53-dependent apoptosis in SCA3 , Huntington’s disease and spinocerebellar ataxia type 7 ( SCA7 ) [15 , 28 , 29] . Ectopic expression of ATXN3-Q79 in cultured cerebellar neurons results in p53 activation , increased expression of BAX , increased release of cytochrome c from mitochondria , and apoptotic cell death [16] . However , the mechanism by which the polyQ proteins stimulate p53 activation and apoptosis remains unknown . We transfected the SH-SY5Y cells with either PNKP-siRNA or control-siRNA to test our hypothesis that the loss of PNKP activity triggers the pro-apoptotic signaling pathways in SCA3 . Western blotting showed markedly decreased PNKP levels in cells treated with PNKP-siRNA , but not with control-siRNA ( Fig . 5A ) . The TUNEL staining ( Fig . 5B ) , and increased ( ~2-fold ) caspase-3 activities ( Fig . 5C ) of the PNKP-depleted cells suggest robust activation of the pro-death pathways when PNKP was depleted . We thus developed SH-SY5Y cells overexpressing exogenous PNKP ( Fig . 5D ) and expressed the mutant ATXN3-Q84 in these cells to test whether PNKP overexpression blocks ATXN3-Q84-mediated cell death . The Western blot analysis clearly shows that ATXN3-Q84 failed to activate the ATM pathway in cells overexpressing PNKP ( Fig . 5E ) . Moreover , overexpression of PNKP in these cells blocked ATXN3-Q84-mediated caspase-3 activation ( Fig . 5F ) , suggesting that the loss of PNKP function plays an important role in mutant ATXN3-mediated cell death . Furthermore , quantitative RT-PCR ( qRT-PCR ) analysis of total RNA from the PNKP-depleted SH-SY5Y cells showed stimulated transcription of the p53-dependent pro-apoptotic genes such as BAX , BBC3 ( encoding PUMA ) , Bcl2L11 ( encoding BIM ) and PMAIP1 ( encoding NOXA ) ( Fig . 5G ) . Moreover , we found that pre-treating the cells with either the ATM inhibitor Ku55933 or the p53 inhibitor Pifithrin-α could block PNKP-siRNA-induced caspase-3 activation ( Figs . 5H and 5I ) . Likewise , expression of ATXN3-Q84 stimulated caspase-3 activity , whereas pre-treating the cells with Ku55933 or Pifithrin-α ameliorated the ATXN3-Q84-induced caspase-3 activation ( S14A and S14B Figs . ) . These data substantiate our previous interpretation that mutant ATXN3 activates the p53-dependent pro-death pathway by activating ATM , and that chronic activation of the ATM→p53 pathway plays a pivotal role in mediating neuronal death in SCA3 . In response to DNA damage , the tyrosine kinase c-Abl ( encoded by the mammalian homolog of the v-Abl oncogene from the Abelson murine leukemia virus ) is phosphorylated by ATM and DNA-dependent protein kinase , DNA-PK [30–32] . Activated c-Abl constitutively associates with PKCδ , resulting in the latter’s phosphorylation and nuclear translocation [33 , 34] . Cytosolic retention of PKCδ is required to maintain cell survival , whereas its phosphorylation and nuclear translocation activates an apoptotic pathway [33–36] . Since ATXN3-Q84-induced DNA damage strongly activated the ATM pathway , we explored the possibility that ATXN3-Q84 could induce the phosphorylation of the ATM target proteins c-Abl and PKCδ . Expression of ATXN3-Q84 indeed increased the phosphorylation of c-Abl ( T735 ) and PKCδ ( T311 ) , and caspase-3 cleavage ( Figs . 6A and S15A ) . However , pre-treating the cells with Ku55933 blocked these events ( Figs . 6B and S15B ) . Furthermore , consistent with our data in S10 Fig . showing marked activation of ATM pathway upon PNKP depletion , we found increased phosphorylation of c-Abl and PKCδ and higher caspase-3 activity in cells treated with PNKP-siRNA ( Figs . 6C and S15C ) , but not with control-siRNA ( Figs . 6D and S15D ) . However , depleting PNKP in cells pre-treated with Ku55933 stimulated the DNA damage response ( assessed by increased H2AX phosphorylation ) , but did not increase the phosphorylation of c-Abl and PKCδ or caspase-3 cleavage ( S16 Fig . ) . To test whether ATXN3-Q84 activates PKCδ by activating c-Abl , we pre-treated the cells with the c-Abl kinase inhibitor STI-571; ATXN3-Q84 expression failed to enhance PKCδ phosphorylation in cells pre-treated with STI-571 ( Figs . 6E and S15E ) . Moreover , PNKP depletion did not enhance PKCδ phosphorylation when cells were pre-treated with STI-571 ( Figs . 6F and S15F ) , suggesting that mutant ATXN3 increases PKCδ phosphorylation by activating the ATM→c-Abl signaling pathway . Since phosphorylated PKCδ is translocated to nuclei [33–34] and we observed that ATXN3-Q84 stimulates PKCδ phosphorylation ( Figs . 6 and S15 ) , we assessed the relative abundance of PKCδ in the sub-cellular compartments of SH-SY5Y cells expressing ATXN3-Q84 and ATXN3-Q28 . Cells expressing ATXN3-Q84 showed higher nuclear levels of PKCδ ( Fig . 7A; upper panel ) ; by contrast , cells expressing ATXN3-Q28 showed predominantly cytosolic PKCδ ( Fig . 7A , lower panel ) . Western blotting of the nuclear and cytosolic protein fractions showed higher nuclear levels of PKCδ in ATXN3-Q84-expressing cells than in control cells ( Figs . 7B and 7C ) . Depletion of PNKP also resulted in marked nuclear accumulation of PKCδ ( S17 Fig . ) . Furthermore , immunohistological analysis revealed that about 60 to 70% of the nuclei had significant nuclear accumulation of PKCδ in the SCA3 transgenic mouse brain sections ( S18 Fig . lower panels; arrows ) ; in contrast , control mouse brains showed predominantly cytoplasmic PKCδ ( S18 Fig . upper panels; arrowheads ) . We next assessed whether blocking PKCδ phosphorylation by inhibiting c-Abl kinase activity ameliorates mutant ATXN3-mediated caspase-3 activation . Pre-treating cells with STI-571 significantly inhibited mutant ATXN3-Q84-mediated caspase-3 activation ( S19A Fig . ) . Likewise , pre-treating cells with STI-571 also ameliorated PNKP-siRNA-mediated caspase-3 activation ( S19B Fig . ) . Collectively , these data , together with the data presented in the accompanying manuscript by Chatterjee et al , suggest that the wild-type ATXN3 interacts with and stimulates PNKP’s 3’-phosphatase activity , and this interaction possibly modulates the efficacy of DNA repair , and helps maintain genomic integrity and neuronal survival . In contrast , mutant ATXN3 interacts with PNKP and abrogates its 3’-phosphatase activity , resulting in increased accumulation of DNA damage that chronically activates ATM→p53 and ATM→c-Abl→PKCδ pro-apoptotic signaling to trigger neuronal dysfunction and apoptosis in SCA3 ( illustrated in Fig . 8 ) .
The DNA damage-response pathway is rapidly activated in response to DNA damage to repair the damaged sites by activating a well-orchestrated signaling network . However , if the DNA damage/lesions are irreparable , the damage-response pathway activates pro-death signaling cascades to ensure apoptotic demise of the damaged cells to maintain cell and tissue homeostasis . Due to their high metabolic activity , the post-mitotic neurons generate higher amounts of reactive oxygen species , and also have a higher risk of accumulating strand breaks due to their high transcriptional activity [37–41] . Therefore , post-mitotic neurons have an elaborate mechanism to repair DNA strand breaks/lesions to ensure longevity and functionality when subjected to insults [37 , 38 , 42 , 43] . An emerging picture suggests that mutation or loss of function of DNA repair genes in post-mitotic neurons results in the accumulation of DNA damage/strand breaks , neuronal dysfunction and systemic neurodegeneration [44–49] . For example , mutations in the DNA repair enzymes APTX and TDP1 have been shown to contribute to neurodegeneration and the development of ataxia in autosomal recessive disorders such as AOA1 ( ataxia with oculomotor apraxia type 1 ) [44 , 45] and SCAN1 ( spinocerebellar ataxia with axonal neuropathy ) respectively [46] . Another recent discovery suggests that mutations in FUS ( fused in sarcoma ) , a DNA repair protein that associates with the HDAC1-SIRT1 repair complex , result in the accumulation of DNA strand breaks , neurodegeneration and neurological defects in amyotrophic lateral sclerosis ( ALS ) [47] . Moreover , using genome-wide linkage analysis in consanguineous families of an autosomal recessive disease , multiple point mutations were identified in PNKP that result in neurological phenotypes characterized by microcephaly , intractable seizures , and developmental delay [48] . The presence of a homozygous frame-shift mutation in PNKP was recently identified in an early-onset neurodegenerative disorder that manifests with polyneuropathy , cerebellar atrophy , microcephaly , epilepsy and intellectual disability [49] . Disease-causing point mutations ablate either the kinase or phosphatase activities of PNKP in vitro [50] . These findings explain how the loss of function of essential DNA repair enzymes and subsequent defective DNA repair and accumulation of DNA damage results in neurological abnormalities . Recent studies also indicate that persistent accumulation of DNA damage and inappropriate activation of the DDR pathway may contribute to the pathogenic mechanism of fragile X mental retardation syndrome ( Fragile X syndrome ) , a common form of inherited mental retardation caused by the loss of the fragile X mental retardation protein , FMRP [51 , 52] . Accumulating evidence suggests that in addition to the translational regulation in the cytoplasm , FMRP is also present in the nuclei , where it strongly associates with the chromatin and plays an important role in the regulation of DDR pathway , maintenance of genomic DNA sequence integrity and neuronal survival [52 , 53] . A FMRP mutant Drosophila has been shown to be hypersensitive to genotoxic stress , and fails to survive to adulthood when exposed to stress [51] . The FMRP mutant fly also shows the presence of DNA damage and activation of the p53-dependent apoptotic pathways after irradiation [51] . These findings suggest that FMRP plays an important role in the maintenance of genomic DNA sequence integrity and neuronal survival . It is likely that the loss of FMRP may impair the efficacy of DNA repair , resulting in the persistent accumulation of neuronal DNA damage and inappropriate activation of the DNA damage response p53-dependent pro-apoptotic pathways to elicit neuronal death . However , further molecular and interventional studies are required to identify the interacting protein partners of FMRP in the nuclei to establish the exact role of FMRP in DNA repair , regulation of DDR pathway and maintenance of genomic DNA sequence integrity and to determine whether the loss of FMRP function contributes to aberrant activation of the DDR pathway and neurodegeneration in fragile X syndrome . In the present study , we show that PNKP is inactivated via its interaction with the mutant ATXN3 , and also in part due to its recruitment into the insoluble polyQ aggregates in SCA3 brain . Our data , together with the data presented in the accompanying manuscript by Chatterjee et al . , strongly support our interpretation that interaction of PNKP with mutant ATXN3 and/or trapping of PNKP in the polyQ aggregates markedly abrogate PNKP’s enzymatic activity and DNA repair efficacy , resulting in persistent accumulation of strand breaks in SCA3 . Decreased PNKP activity and the presence of high levels of strand breaks in the SH-SY5Y cells expressing ATXN3-Q84 , in SCA3 patients’ brain and SCA3 transgenic mouse brains expressing mutant ATXN3 , strongly support this idea . Furthermore , we demonstrate that mutant ATNX3 potently activates the DNA damage-response ATM signaling pathway in SCA3 , while increased phosphorylation of ATM , H2AX , Chk2 and p53 , and the formation of 53BP1 and γH2AX foci in the ATXN3-Q84-expressing cells , SCA3 patients’ brains and SCA3 transgenic mouse brains suggest that mutant ATXN3 induces genomic DNA damage and chronically activates the ATM pathway in SCA3 . Moreover , amelioration of ATXN3-Q84-mediated phosphorylation of p53 , c-Abl and PKCδ by pharmacological inhibition of ATM suggests that mutant ATXN3 activates the pro-death signaling cascades via activating ATM in SCA3 . The occurrence of higher levels of genomic DNA damage has been reported in several neurodegenerative diseases such as Huntington’s disease , Parkinson’s disease , Alzheimer’s disease , and ALS [54–58] . However , it remains to be determined whether higher genomic DNA damage and aberrant activation of the DNA damage-response pathway contributes to neurodegeneration and the etiology of these diseases . Our data described in the present manuscript establish a mechanistic link between mutant ATXN3 expression and aberrant p53 pathway activation in SCA3 , as previously reported [16 , 22] . The transcription factor p53 regulates the cell cycle , DNA damage-response repair and cell death [25 , 26 , 59] . Activated p53 initiates neuronal death by activating the expression of BAX , BBC3 and PMAIP1 [26 , 59–64] , and these factors stimulate apoptosis by enhancing mitochondrial membrane permeabilization that facilitates the release of cytochrome c and Smac/DIABLO [65–67] . Mutant polyQ-containing proteins have been shown to activate p53-dependent apoptosis in SCA3 , SCA7 and Huntington’s disease [15 , 16 , 28 , 29] . Our data show elevated mRNA levels of BAX , BBC3 and PMAIP1 in ATXN3-Q84-expressing and PNKP-depleted cells . The amelioration of apoptosis by pharmacological inhibition of ATM and p53 , suggest that mutant ATXN3-mediated aberrant activation of the DNA damage-response pathway facilitates the apoptotic demise of neuronal cells in SCA3 . Moreover , in response to DNA damage , the protein tyrosine kinase c-Abl is phosphorylated by ATM and DNA-dependent protein kinase ( DNA-PK ) [30–32] . Activated c-Abl in turn phosphorylates and facilitates the nuclear translocation of PKCδ [33 , 34] , whose cytosolic retention is required to maintain cell survival , whereas phosphorylation and nuclear translocation of PKCδ activates the apoptotic pathway [34–36] . Phosphorylation of PKCδ allows its association with importin-α , resulting in nuclear translocation of PKCδ and activation of apoptosis [33–36] . Consistent with these reports , our data show that mutant ATXN3-mediated activation of ATM→c-Abl pathway enhanced the phosphorylation and facilitated the nuclear translocation of PKCδ in cells , and in SCA3 transgenic mouse brains . It has been suggested that nuclear PKCδ phosphorylates p73 and DNA-PK to facilitate apoptosis [68]; however , it is not yet clear how PKCδ triggers apoptosis . We are currently investigating whether mutant ATXN3 enhances the phosphorylation of p73 and DNA-PK to induce apoptosis in SCA3 . In conclusion , our current study provides compelling evidence of how mutant ATXN3 impedes the enzymatic activity of PNKP , and induces DNA damage that manifests with activation of the pro-apoptotic signaling pathways in SCA3 . Our data suggest that in addition to activating the DNA damage-induced p53 pathway as described earlier in SCA3 [15 , 16] , mutant ATXN3 also activates the ATM-dependent cAbl→PKCδ pro-apoptotic pathway in parallel to cause neuronal dysfunction and eventually facilitating systemic neuronal degeneration in SCA3 brain ( Fig . 8 ) . Understanding the aberrant interaction between PNKP and mutant ATXN3 that results in the sustained activation of the pro-death signaling pathways may provide important insights to develop novel , mechanism-based therapeutic strategies for SCA3 . Specific modulation of mutant ATXN3-mediated atypical activation of the DNA damage-response p53 and PKCδ pathways , or enhancing the efficacy of in vivo DNA damage repair may be effective strategies to combat the pathways leading to systemic neurodegeneration in SCA3 . However , further investigation and interventional studies are required to device strategies to block this deleterious protein-protein interaction to rescue neuronal dysfunction and demise of neuronal cells in SCA3 . Finally , CAG repeat instabilities and expansions are causal factors for several other poly-Q expansion-related neurodegenerative diseases e . g . , SCA1 , SCA2 , SCA6 , SCA7 , SCA17 , DRPLA , SBMA and Huntington’s disease [2 , 69] . Is has been challenging to understand why these repeats show a pronounced region-specific instability pattern in brain . However , a recent study has clearly shown significantly elevated expression levels of various DNA repair proteins in the cerebellum compared to the striatum , and consequent higher repeat instability in the striatum of HD mouse model [70] . This study suggests that lower activities of various DNA repair enzymes might be responsible for the higher instability of the CAG repeats observed in the striatum in HD brain compared to other regions of the brain . These data strongly suggest that optimal activities of various DNA repair proteins act as a safeguard against repeat instability and thus reduce somatic instability of the repeats in the specific brain region , dictating the severity of disease pathologies [70] . It will be interesting to determine whether the expression levels and/or activity of PNKP vary in various brain regions , which may provide important insight to understand the molecular basis of region-specific repeat instability and differential vulnerability of specific brain regions in different poly-glutamine expansion-associated neurological diseases .
Plasmids pEGFP-Ataxin3-Q28 , pEGFP-Ataxin3-Q84 and pFLAG-Ataxin3-Q80 were kindly provided by Dr . Henry L . Paulson ( Addgene plasmids 22122 , 22123 and 22129 ) . Expression plasmid ATXN3-Q72 was kindly provided by Dr . Randall Pittman ( University of Pennsylvania ) . The wild-type and mutant ATXN3 cDNAs were sub-cloned in pAcGFPC1 ( Clontech , USA ) to construct plasmids pGFP-ATXN3-Q28 , pGFP-ATXN3-Q84 and pGFP-ATXN3-Q80 respectively . The plasmids pGFP-ATXN3-Q28 , pGFP-ATXN3-Q80 and pGFP-ATXN3-Q84 were digested with AgeI and MluI , and the GFP-ATXN3-Q28 , GFP-ATXN3-Q80 and GFP-ATXN3-Q84 fragments were sub-cloned into the Tet-inducible plasmid pTRE-3G ( Clontech , USA ) using appropriate linkers . The trans-activator plasmid pTet-ON-3G ( Clontech , USA ) and responder plasmids pTRE-GFP-ATXN3-Q84 , GFP-ATXN3-Q80 or pTRE-GFP-ATXN3-Q28 was co-transfected into SH-SY5Y cells , and positive clones were selected with G418 . Stable SH-SY5Y clones inducibly expressing GFP-ATXN3-Q84 , GFP-ATXN3-Q80 and GFP-ATXN3-Q28 were incubated with medium containing doxycycline ( 500 ng/ml ) , and expression of the transgene was assessed by Western blotting using anti-ATXN3 antibody . The PNKP cDNA was PCR-amplified from plasmid pWZL-Neo-Myr-Flag-PNKP ( kindly provided by Drs . William Hahn and Jean Zhao; Addgene plasmid 20594 ) and sub-cloned into pcDNA3 . 1-Hygro ( Invitrogen , USA ) to construct plasmid pRP-PNKP . The catalase cDNA was PCR-amplified from a cDNA clone with appropriate primers and was sub-cloned into plasmid pcDNA3 . 1-Hygro to construct plasmid pRP-Catalase . Plasmid pRP-PNKP or pRP-Catalase was transfected into SH-SY5Y stable cell lines encoding inducible ATXN3-Q28 and ATXN3-Q84 , and the clones were selected against hygromycin resistance . The effective expression of the exogenous PNKP and catalase in these cells were assessed by Western blot analyses with appropriate antibodies . Anti-PNKP mouse monoclonal antibody was a kind gift from Prof . Michael Weinfeld ( University of Alberta , Canada ) and anti-catalase antibody ( Cat # SC-50508 ) was purchased from Santa Cruz Biotechnology , USA . The PNKP cDNA was PCR-amplified from plasmid pWZL-Neo-Myr-Flag-PNKP and the PCR product was sub-cloned into XhoI- and BamHI-digested pmCherryC1 ( Clontech , USA ) to construct pCherry-PNKP expressing Cherry-tagged PNKP . SH-SY5Y cells were purchased from ATCC and cultured in DMEM medium containing 15% FBS , and 1% B-27 supplement , and differentiated in DMEM medium containing 10% FBS , 1% B-27 supplement ( Invitrogen , USA ) and 20 μM retinoic acid . The SH-SY5Y stable cells encoding inducible GFPC1-ATXN3-Q28 , GFPC1-ATXN3-Q72 , GFPC1-ATXN3-Q80 and GFPC1-ATXN3-Q84 were differentiated for 7 days and transgene expression in the differentiated cells was induced by adding doxycycline to the medium to a final concentration of 500ng/ml . The siRNA duplexes for PNKP and control scrambled siRNA duplexes with same base composition were purchased from Sigma , USA , and transfection of the PNKP-siRNA duplexes into SH-SY5Y cells or differentiated SH-SY5Y cells were performed using Lipofectamine RNAi-MAX reagent ( Invitrogen , USA ) . Plasmids encoding micro-RNA-based PNKP-shRNAmir and control-shRNAmir were purchased from Thermo Scientific , USA , and transfected into SH-SY5Y cells using Lipofectamine 2000 reagent ( Invitrogen , USA ) . Human autopsy specimens were obtained from SCA3 patients and control subjects in accordance with local legislation and ethical rules . Control brain samples were collected from age-matched individuals who were deemed free of neurodegenerative disorders . The SCA3 brain tissue samples used for this study were obtained from SCA3 patients who were clinically characterized by cerebellar ataxia , opthalmoplegia , dysarthria and dysphagia . The molecular diagnosis of SCA3 was established by analyzing genomic DNA extracted from peripheral blood using a combination of PCR and Southern blotting . The exact lengths of the expanded CAG repeat sequences in ATXN3 gene were established by sequencing the CAG repeat expansion loci of the mutant allele . All brain autopsies were frozen in liquid nitrogen immediately after surgery , and stored in a −80°C freezer until further analysis . The MJD transgenic mice used in this study were previously described [21] . CMVMJD135 mice express the human ATXN3 carrying 135 glutamines and develop a progressive neurological phenotype with onset at 6 weeks , which includes loss of strength , impairment of motor coordination , loss of balance and altered reflexes . At late stages they show an overall reduction in brain weight , with reduced volume and/or total cell number in pontine nuclei and deep cerebellar nuclei , and intranuclear ATXN3 inclusions in several disease-relevant regions of the brain and spinal cord . Transgenic mice and control non-transgenic littermate mice ( n = 4–5 pools of two animals per genotype ) with a mean age of 20 weeks were sacrificed by decapitation , and brain slices were obtained for the macrodissection of the deep cerebellar nuclei using a stereomicroscope ( Model SZX7 , Olympus America Inc . , USA ) and frozen at −80ºC . For immunofluorescence assays , transgenic and wild-type littermate mice ( mean age: 24 weeks ) were deeply anesthetized and transcardially perfused with sterile PBS followed by 4% paraformaldehyde ( PFA ) in PBS . Brains were post-fixed overnight in fixative solution and embedded in paraffin . Slides with 4-μm-thick paraffin sections were processed for immunostaining with anti-PKCδ , -ATXN3 and—PNKP antibodies . The SCA3 transgenic mice ( CMVMJD135 transgenic mice ) were sacrificed and the brain tissues were collected according to the standard approved procedure and national and international guidelines and animal protocols were strictly followed . Alkaline comet assays were performed using a Comet Assay Kit ( Trevigen , USA ) . The brain tissue was homogenized in PBS at 4°C and sifted through a 300 μm sieve . Cells were suspended in 85 μL of ice-cold PBS and gently mixed with an equal volume of 1% low-melting agarose . The cell suspension was dropped onto an agarose layer , and incubated in lysis buffer for 1 hour . After lysis , slides were incubated in buffer containing 0 . 3 M NaOH , 1 mM EDTA ( pH 13 ) for 40 min , and electrophoresed for 1 hour . After neutralization , slides were stained and analyzed with a fluorescent microscope . To assess genomic DNA damage after treatment with genotoxic agents , cells were treated with 10 μM hydrogen peroxide ( H2O2 ) for 20 minutes in serum-free medium , washed twice with ice-cold PBS and subjected to comet analysis as described above . The antibodies for p53 ( Cat # 9282 ) , P-p53-S15 ( Cat # 9286 ) , P-p53-S20 ( Cat # 9287 ) , P-p53-S46 ( Cat # 2521 ) , Chk2 ( Cat # 2662 ) , P-Chk2-T68 ( Cat # 2661 ) , c-Abl ( Cat # 2862 ) , P-cAbl-T735 ( Cat # 2864 ) , PKCδ ( Cat # 2058 ) , P-PKCδ-T311 ( Cat # 2055 ) , p-53BP1-S1778 ( CAT # 2675 ) and caspase-3 ( Cat # 9668 ) were from Cell Signaling , USA; anti-H2AX ( Cat # ab11175 ) and P-γH2AX-S139 ( Cat # ab11174 ) were from Abcam , USA; anti-ATM ( Cat # 1549–1 ) and P-ATM-S1981 ( Cat # 2152–1 ) were from Epitomics , USA; anti-ataxin-3 rabbit polyclonal antibody ( cat # 13505–1-AP ) was from Protein tech , USA; anti-ataxin-3 mouse monoclonal antibody ( Cat # Mab5360 ) was from Millipore , USA; and anti-polyQ diseases marker antibody , 5TF1–1C2 ( cat # Mab1574 ) was from Millipore , USA . Cell pellets or mouse brain tissues were homogenized and total protein was isolated using a total protein extraction kit ( Millipore , USA ) . The cytosolic and nuclear fractions were isolated from SH-SY5Y cells expressing ATXN3-Q84 and ATXN3-Q28 using a NE-PER nuclear protein extraction kit ( Thermo Scientific , USA ) . The Western blot analyses were performed according to the standard procedure and each experiment was performed a minimum of 3 times to ensure reproducible and statistically significant results . Bi-molecular fluorescence complementation assays were performed as described previously by Shyu et al [19] . Plasmids pBiFC-VN173 ( encoding 1 to 172 N-terminal amino acids of modified GFP ) and pBIFC-VC155 ( encoding 155 to 238 C-terminal amino acids of modified GFP ) were kindly provided by Dr . Chang-Deng Hu , Purdue University ( Addgene plasmids 22011 and 22010 ) . The ATXN3 cDNA ( encoding 28 and 84 glutamines ) were cloned in-frame with the C-terminal amino acids of modified GFP in plasmid pBiFC-VC155 and the PNKP cDNA was cloned in-frame with the N-terminal amino acids of modified GFP in plasmid pBIFC-VN173 . SH-SY5Y cells ( 2×104 cells ) were grown on chamber slides and transfected after 24 hours of plating . Plasmids pVN173-PNKP and pVC155-ATXN3-Q28 or pVN173-PNKP and pVC155-ATXN3-Q84 were co-transfected into SH-SY5Y cells and reconstitution of green/yellow fluorescence was monitored by fluorescence microscopy to assess bimolecular protein-protein interactions . Transfections of pVC155-ATXN3-Q28 , pVC155-ATXN3-Q84 and pVN173-PNKP as single plasmids into SH-SY5Y cells were used as negative controls . Expression of ATXN3-Q28 and ATXN3-Q84 in SH-SY5Y cells was induced by incubating the cells with doxycycline ( 500 ng/ml ) , and after 48 hours of incubation , the cells were fixed with 4% paraformaldehyde in PBS for 30 minutes . For the PNKP depletion experiment , SH-SY5Y cells were grown on cover slips and transfected with PNKP-siRNA; 48 hours after transfection , the cells were fixed with 4% paraformaldehyde for 30 minutes . The fixed cells were immunostained with anti-p-53BP1 , anti-γH2AX or anti-PKCδ antibodies . Frozen brain sections from SCA3 patients and control subjects were fixed in 4% paraformaldehyde , washed with PBS , and immunostained with anti-p-53BP1 and γH2AX antibodies . Paraffin-embedded transgenic and control mouse brain sections were deparaffinized and rehydrated , fixed in 4% paraformaldehyde for 30 minutes , washed , and immunostained with anti-p-53BP1 , anti-γH2AX , and PKCδ antibodies . Slides were washed according to our standard protocol and the nuclei stained with DAPI ( Molecular Probe , USA ) and photographed under a confocal microscope . TUNEL staining of the SH-SY5Y cells transfected with PNKP-siRNA and control-siRNA was performed using an in situ Apoptosis Detection Kit per the manufacturer’s protocol ( Calbiochem , USA ) . SH-SY5Y cells or differentiated SH-SY5Y cells were incubated with 5mM of N-acetyl cysteine ( NAC ) , the ATM inhibitor Ku55933 , p53 inhibitor Pifithrin-α or c-Abl kinase inhibitor STI-571 for 3 hours before the expression of ATXN3-Q28 and ATXN3-Q84 . The ATM inhibitor Ku55933 was purchased from EMD Biosciences , USA and Pifithrin-α and STI-571 were purchased from Santa Cruz Biotechnology , USA . Drugs were added to the cell culture medium to a final concentration of 1 µM , 2 µM or 5 μM and incubated for 3 hours before transgene induction; fresh medium with drugs was replaced after 12 hours . Cells were harvested at various time points for Western blot analyses and for isolating total RNA and qRT-PCR analyses . Images were collected using a Zeiss LSM-510 META confocal microscope with 40X or 60X 1 . 20 numerical aperture water immersion objective . The images were obtained using two different lines of excitation ( 488 and 543 nm ) by sequential acquisition . After excitation with 488 nm laser line emission was measured with a 505–530 nm filter and after excitation with 543 laser line emission was measured with a 560–615 nm filter . All images were collected using 4-frame-Kallman-averaging with a pixel time of 1 . 26 μs , a pixel size of 110 nm and an optical slice of 1 . 0 μm . Z-stack acquisition was done at z-steps of 0 . 8 μm . All orthogonal views were done with LSM 510 software at the Optical Microscopy Core Laboratory of UTMB . Caspase-3 activities were measured using a Caspase-3 activity assay kit ( BD Biosciences , USA ) . The Caspase 3 assay kit is based on the hydrolysis of the substrate , acetyl-Asp-Glu-Val-Asp p-nitroanilide ( Ac-DEVD-pNA ) by caspase 3 , resulting in the release of the p-nitroaniline ( pNA ) moiety from the substrate , and released p-Nitroaniline ( pNA ) is detected at 405 nm . Comparison of the absorbance of pNA from the sample with the control allowed determination of the fold increase in caspase-3 activity and the relative caspase-3 activities are expressed in arbitrary units . SH-SY5Y cells encoding ATXN3-Q28 and ATXN3-Q84 were cultured in DMEM ( Invitrogen , USA ) containing 15% FBS and were cultured on 96 well dishes in DMEM ( Invitrogen , USA ) containing 15% FBS . Expression of ATXN3-Q28 and ATXN3-Q84 were induced in presence or absence of the drugs Ku55933 ( 2 μM ) , Pifithrin-α ( 10 μM ) or STI-571 ( 5 μM ) with doxycycline ( 500 ng/ml ) . The cells were harvested 3 days after induction and caspase-3 activities were measured . For measuring caspase-3 activities in the PNKP and control-siRNA-treated cells , the SH-SY5Y cells were cultured in 96-well dishes and transfected with PNKP-siRNA or control-siRNA in the presence or absence of Ku55933 ( 2 μM ) , Pifithrin-α ( 10 μM ) or STI-571 ( 5 μM ) . The cells were harvested 48 hours after transfection , and caspase-3 activities were measured . Total RNA was extracted from SH-SY5Y cells expressing ATXN3-Q28 , ATXN3-Q84 , PNKP-siRNA and control-siRNA using an RNA extraction kit ( Qiagen , USA ) and purified using the TURBO DNA-free DNAse Kit ( Ambion , USA ) . Brain tissue ( deep cerebellar nuclei ) from SCA3 transgenic mouse expressing ATXN3-Q135 was homogenized in trizol reagent ( Invitrogen , USA ) and RNA was isolated as above . 1μg of total RNA was reverse-transcribed using an RT-PCR kit ( Clontech , USA ) . A cDNA aliquot from each reaction was quantified and 500ng of cDNA from each reaction was used for real-time qRT-PCR . The qRT-PCR reactions were repeated three times; primers used for the analyses ( BAX: PPH00078B; BBC3: PPH02204C; PMAIP1: PPH02090F; BCL2L11: PPH00893 ) were purchased from Qiagen , USA , and tested for accuracy , specificity , efficiency and sensitivity by the manufacturer . PLA assays were performed by the method we described previously [18] . In brief , SCA3 and normal brain sections were fixed with 4% paraformaldehyde , permeabilized with 0 . 2% Tween-20 and washed with 1X PBS . Brain sections were incubated with primary antibodies for PNKP ( mouse monoclonal ) and ATXN3 ( anti-ATXN3; rabbit polyclonal ) or PNKP ( mouse monoclonal ) and DNA ligase 3 ( rabbit polyclonal ) . These samples were subjected to PLAs using the Duolink PLA kit from O-Link Biosciences ( Uppsala , Sweden ) . The nuclei were counterstained with DAPI , and the PLA signals were visualized in a fluorescence microscope ( Nikon ) at 20× magnification . All tabulated data are expressed as mean ± SD , except where otherwise indicated . Differences between mean values of two groups were analyzed by Student’s t tests after checking for variance distribution via Levene’s test . We tested all data for normal distribution using the Kolmogorov-Smirnov test , followed by two-way ANOVA test to evaluate overall group differences . This was followed by Tukey’s post-hoc test to determine pair-wise significance if the ANOVA test indicated that a significant difference was present in the data set . In all cases , probability values of 0 . 05 or less were considered to be statistically significant . | Spinocerebellar ataxia type 3 ( SCA3 ) is an untreatable neurodegenerative disease , and the most common dominantly inherited ataxia worldwide . SCA3 is caused by expansion of a CAG tri-nucleotide repeat sequence in the ATXN3 gene’s coding region . The expanded CAG sequences encode a run of the amino acid glutamine; the mutant ATXN3 interacts with multiple proteins in vivo to create insoluble aggregates in SCA3 brains . It is thought that the loss of function of the aggregated proteins contributes to cellular toxicity and neurodegeneration in SCA3 . Despite significant progress in understanding SCA3’s etiology , the molecular mechanism by which the mutant protein triggers the death of neurons in SCA3 brains remains unknown . We now report that the mutant ATXN3 protein interacts with and inactivates PNKP ( polynucleotide kinase 3’-phosphatase ) , an essential DNA strand break repair enzyme . This inactivation results in persistent accumulation of DNA damage , and chronic activation of the DNA damage-response ATM signaling pathway in SCA3 . Our work suggests that persistent DNA damage/strand breaks and chronic activation of ATM trigger neuronal death in SCA3 . Discovery of the mechanism by which mutant ATXN3 induces DNA damage and amplifies the pro-death pathways provides a molecular basis for neurodegeneration in SCA3 , and perhaps ultimately for its treatment . | [
"Abstract",
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"Methods"
] | [] | 2015 | Inactivation of PNKP by Mutant ATXN3 Triggers Apoptosis by Activating the DNA Damage-Response Pathway in SCA3 |
Many bacterial pathogens achieve resistance to defensin-like cationic antimicrobial peptides ( CAMPs ) by the multiple peptide resistance factor ( MprF ) protein . MprF plays a crucial role in Staphylococcus aureus virulence and it is involved in resistance to the CAMP-like antibiotic daptomycin . MprF is a large membrane protein that modifies the anionic phospholipid phosphatidylglycerol with l-lysine , thereby diminishing the bacterial affinity for CAMPs . Its widespread occurrence recommends MprF as a target for novel antimicrobials , although the mode of action of MprF has remained incompletely understood . We demonstrate that the hydrophilic C-terminal domain and six of the fourteen proposed trans-membrane segments of MprF are sufficient for full-level lysyl-phosphatidylglycerol ( Lys-PG ) production and that several conserved amino acid positions in MprF are indispensable for Lys-PG production . Notably , Lys-PG production did not lead to efficient CAMP resistance and most of the Lys-PG remained in the inner leaflet of the cytoplasmic membrane when the large N-terminal hydrophobic domain of MprF was absent , indicating a crucial role of this protein part . The N-terminal domain alone did not confer CAMP resistance or repulsion of the cationic test protein cytochrome c . However , when the N-terminal domain was coexpressed with the Lys-PG synthase domain either in one protein or as two separate proteins , full-level CAMP resistance was achieved . Moreover , only coexpression of the two domains led to efficient Lys-PG translocation to the outer leaflet of the membrane and to full-level cytochrome c repulsion , indicating that the N-terminal domain facilitates the flipping of Lys-PG . Thus , MprF represents a new class of lipid-biosynthetic enzymes with two separable functional domains that synthesize Lys-PG and facilitate Lys-PG translocation . Our study unravels crucial details on the molecular basis of an important bacterial immune evasion mechanism and it may help to employ MprF as a target for new anti-virulence drugs .
In order to combat increasingly antibiotic-resistant bacteria such as Staphylococcus aureus , Mycobacterium tuberculosis , Pseudomonas aeruginosa , and enterococci new antimicrobial strategies based on compounds with anti-virulence or anti-fitness properties are increasingly in the focus of research efforts [1] , [2] . Bacterial immune evasion mechanisms such as the mprF or dltABCD-encoded pathways are conserved over a wide range of bacterial species thereby representing attractive targets for broadly active antimicrobial compounds that would not kill the bacteria directly but render them susceptible to endogenous host defense molecules [3] , [4] . The occurrence of closely related immune evasion factors in many bacterial pathogens is reflected by the conserved nature of the most critical antimicrobial host defense molecules . Defensins , cathelicidins , kinocidins , and related cationic antimicrobial peptides ( CAMPs ) are essential components of the antimicrobial warfare arsenals in humans , vertebrate and invertebrate animals , and even plants [5] , [6] . Although peptide structures vary , overall structural features ( cationic , amphipathic properties; often with γ-core motif ) and modes of action ( damage of microbial membrane-associated processes ) are shared by most of these peptides [7] . CAMPs appear to take advantage of the fact that bacterial membranes are formed mostly by anionic phospholipids [4] . Conversely , the MprF and DltABCD proteins protect many bacterial pathogens against CAMPs by reducing the negative net charge of bacterial cell envelopes [3] , [8] . The dltABCD operon products neutralize polyanionic teichoic acid polymers by esterification with d-alanine in many Gram-positive bacteria [9] . Detailed investigations on this pathway have recently led to the development of specific DltA inhibitors , which proved to be very effective anti-virulence drugs for eradication of bacterial infections [10] , [11] . Much less is known on the MprF protein , which represents a particularly interesting antimicrobial drug target because of its presence in both , Gram-positive and Gram-negative bacteria [3] . MprF is a large integral membrane protein catalyzing the modification of the negatively charged lipid phosphatidylglycerol ( PG ) with l-lysine thereby neutralizing the membrane surface and providing CAMP resistance [12]–[14] . The resulting lysyl-phosphatidylglycerol ( Lys-PG ) , described in pioneering biochemical studies in the 1960es [15] , [16] , is produced by an unusual pathway that uses PG and Lys-tRNA as substrate molecules [17]–[19] . The Lys-PG-biosynthetic enzyme has been identified only recently in Staphylococcus aureus and named multiple peptide resistance factor ( mprF ) because mprF mutants lacking Lys-PG are highly susceptible to CAMPs [12] , [13] . The loss of Lys-PG in mprF mutants also led to CAMP susceptibility in Listeria monocytogenes [20] , Bacillus anthracis [21] , and Rhizobium tropici [22] thereby demonstrating a general role of MprF in bacterial immune evasion . Recently , mprF point mutations or alterations in Lys-PG content became notorious for spontaneous resistance of S . aureus to daptomycin [23] , [24] . This antibiotic has recently been approved as an antibiotic of last resort for the treatment of methicillin-resistant S . aureus ( MRSA ) , which are responsible for a large proportion of hospital and , increasingly , community-acquired bacterial infections [25] . Daptomycin has a negative net charge but it is believed to have CAMP-like properties and mode of action upon binding of calcium ions [26] . In addition , MprF has been implicated in S . aureus susceptibility to the cationic antibiotics vancomycin , gentamycin , and moenomycin [27] . mprF expression is upregulated in staphylococci upon contact with CAMPs by the sensor/regulator system ApsRS [28] , [29] , which has also been named GraRS [30] , [31] . Deletion of mprF has led to profoundly reduced virulence of several bacterial pathogens in animal models , which underscores the pivotal role of Lys-PG in bacterial fitness during colonization and infection [12] , [20] , [32] , [33] . Accordingly , it is tempting to elucidate the molecular functions of MprF as a prerequisite for the development of small inhibitory molecules that would block Lys-PG biosynthesis and render a large number of bacterial pathogens highly susceptible to innate host defenses and cationic antibiotics such as daptomycin , glycopeptides , or aminoglycosides . Here we demonstrate that MprF is a bifunctional protein composed of distinct and separable domains . While the C-terminal part of MprF is sufficient to synthesize Lys-PG the N-terminal hydrophobic protein domain is essential for efficient translocation of Lys-PG from the inner to the outer leaflet of the cytoplasmic membrane to reduce the bacterial affinity for CAMPs such as α-defensins , LL-37 , daptomycin , or gallidermin .
Most MprF-like proteins are composed of large N-terminal hydrophobic domains followed by hydrophilic C-terminal domains [34] ( Fig . S1 ) . The hydrophilic portions exhibit much higher degrees of sequence similarity between different members of the MprF protein family [12] suggesting that this domain may play the most crucial role in Lys-PG biosynthesis . The hydrophobic domain of S . aureus MprF ranging from amino acid 1 to 509 is predicted to consist of 14 TMSs ( Fig . 1A ) . In order to study whether the hydrophobic domain plays a role in Lys-PG biosynthesis the protein was shortened from the N-terminus in a step-wise manner by removing two TMSs at a time ( Fig . 1B ) . The shortened proteins were expressed as N-terminal His-tag fusions and evaluated for their capacity to mediate Lys-PG production in E . coli BL21 ( DE3 ) . Deletion of the first eight TMSs of MprF from the N-terminus did not affect the ability of the protein to mediate Lys-PG production ( Fig . 2A ) . However , further truncations abrogated Lys-PG production indicating that at least 6 TMSs are required for maintaining a functional enzyme and that the N-terminal domain of MprF may have a separate function . The presence and stability of the proteins was verified by Western-blotting with a His-tag-specific antibody . The shorter versions of MprF with no , two , four , or six predicted TMSs were detectable as singular similarly pronounced bands indicating that these proteins are largely stable ( Fig . 2B ) . Longer versions of MprF including the full-length protein could not be visualized by Coomassie Blue staining or Western blotting even upon extensive variation of expression , isolation , and detection methods ( data not shown ) , possibly because of inaccessibility of the N-terminal His-tag in these proteins . However , since all proteins ranging from MprF to MprF ( −8 ) yielded similar levels of Lys-PG production the protein amounts and activities are unlikely to exhibit major differences . Taken together , our data indicate that the N-terminal eight TMSs are dispensable for full-level Lys-PG synthesis while any further shortening completely abrogates the functionality of MprF . Alignment of C-terminal MprF domains from different bacterial species revealed several conserved sequence motives , which may represent essential amino acids for substrate binding , enzymatic reaction , or folding into a stable protein of the Lys-PG synthase domain ( Fig . S2 ) . In order to evaluate the essential nature of such positions , eight highly conserved amino acid residues were exchanged with alanine residues by site-directed mutagenesis of the pET28mprF ( −8 ) plasmid . Exchange of K547 , K621 , E624 , D731 , R734 , and K806 led to complete abrogation of Lys-PG production ( Fig . 2C ) . In contrast , replacement of E685 or D546 with alanine resulted in strongly or only slightly reduced Lys-PG production , respectively . The same results were obtained when the mutations were introduced into the full-length MprF protein ( Fig . S3A ) . All the MprF ( −8 ) -derived mutant proteins were detectable in Western Blots as singular protein bands that corresponded to the MprF ( −8 ) protein ( Fig . S3B ) indicating that even the inactive proteins were stably produced in E . coli . Taken together , these data demonstrate essential roles of K547 , K621 , E624 , D731 , R734 , and K806 for the enzymatic activity of MprF and less critical but important roles of D546 and E685 . In order to investigate if MprF ( −8 ) also mediates Lys-PG production in S . aureus , genes encoding the full-length and the MprF ( −8 ) proteins were cloned in the E . coli/Staphylococcus shuttle expression vector pRB474 [35] . All the resulting plasmids led to Lys-PG production in S . aureus SA113 ΔmprF ( Fig . 3A ) thereby reflecting the E . coli results . However , the ΔmprF mutant with plasmid-encoded MprF or MprF ( −8 ) did not reach the same level of Lys-PG as the wild-type strain . When the S . aureus strains were compared for susceptibility to CAMPs such as the α-defensins human neutrophil peptides 1–3 ( HNP 1–3 ) , the human cathelicidin LL-37 , the bacteriocin gallidermin , or the antibiotic daptomycin , the mprF mutant was much more susceptible than the wild-type strain ( Fig . 3B ) , which is in agreement with previous findings [12] , [23] . The strain containing the pRB474mprF ( −8 ) plasmid was as susceptible to daptomycin as the mprF deletion mutant or exhibited only slightly decreased susceptibilities as in the case of HNP1-3 , LL-37 , and gallidermin . However , only the full-length mprF gene led to full resistance to the four peptides . This result indicates that the N-terminal hydrophobic domain of MprF is necessary for mediating efficient CAMP resistance despite the fact that it is dispensable for Lys-PG biosynthesis . The presence of a basic level of Lys-PG seemed to be sufficient for full-level CAMP resistance provided that the N-terminal hydrophobic domain of MprF was not absent , while the total amounts of Lys-PG did not correlate with the levels of CAMP susceptibility ( compare Lys-PG amounts and MIC values for WT and ΔmprF containing plasmid pRBmprF ) . In order to verify this notion we cloned the minimal Lys-PG synthase domain MprF ( −8 ) in the inducible staphylococcal expression vector pTX15 , which has a higher copy number than pRB474 and permits xylose-inducible gene expression [35] , [36] . S . aureus ΔmprF with the resulting plasmid pTX15mprF ( −8 ) had a 2 . 5–3 . 5-fold increased Lys-PG content as with the above described pRB474mprF ( −8 ) ( Fig . 3C ) . However , the two strains were inhibited by similarly low concentrations of daptomycin thereby confirming that Lys-PG production per se does not necessarily cause CAMP resistance , irrespective of the produced amounts of Lys-PG . In order to explore the role of the N-terminal domain of MprF in CAMP resistance the mprF ( −C ) gene encoding only the 14 TMSs without the hydrophilic C-terminal domain was expressed in S . aureus ΔmprF . Of note , the resulting strain did not show resistance to any of the tested CAMPs compared to the ΔmprF mutant ( Fig . 3B ) indicating that this protein domain alone cannot protect the bacteria from CAMPs and depends on the Lys-PG synthase . In order to evaluate if the two domains need to be fused or can be separated to achieve CAMP resistance , the mprF ( −C ) gene was cloned in pTX15 , which is compatible with pRB474-derived plasmids . The resulting plasmid pTX15mprF ( −C ) or the empty control plasmid pTX16 were introduced into S . aureus ΔmprF bearing pRB474mprF ( −8 ) . The MIC values of daptomycin reached much lower levels in the presence of two plasmids compared to the experiments described above , which is probably due to increased stress imparted on the two plasmids-containing bacteria . Notably , when MprF ( −C ) was co-expressed with MprF ( −8 ) in trans it conferred full CAMP resistance , which reached the same level as the unchanged MprF protein ( Fig . 4B ) . Thus , the hydrophobic domain of MprF can only mediate CAMP resistance if the synthase domain is present but the two proteins can be separated and do not need to be covalently linked . While Lys-PG is synthesized at the inner leaflet of the cytoplasmic membrane where the Lys-tRNA donor substrate is available , the lipid can only exert its role in CAMP resistance when present at the outer leaflet of the membrane , where the antimicrobial peptides are encountered . In order to evaluate the possibility that the N-terminal hydrophobic domain of MprF facilitates the translocation and exposure of Lys-PG at the outer leaflet of the membrane , we first investigated the impact of MprF ( −C ) on surface charge neutralization and concomitant repulsion of cationic peptides [12] . A previously described assay based on the bacterial binding capacity of the small red-coloured cationic protein cytochrome c was used for this approach [37] . As expected , the mprF mutant had a profoundly higher capacity to bind cytochrome c as the wild-type strain , which reflects the highly negatively charged membrane surface in the absence of Lys-PG ( Fig . 5A ) . Likewise , expression of MprF ( −C ) or of the synthase domain MprF ( −8 ) in S . aureus ΔmprF led to substantially reduced repulsion of cytochrome c compared to the unaltered MprF . However , when the two protein parts were simultaneously expressed in trans they led to the same level of cytochrome c repulsion as expression of the unaltered MprF protein ( Fig . 5A ) . These results parallel the inability of MprF ( −8 ) and MprF ( −C ) to confer CAMP resistance individually and they confirm that the two proteins have complementary functions that can be physically separated . The ability of the N-terminal hydrophobic domain of MprF to facilitate the translocation of Lys-PG from the inner to the outer leaflet of the cytoplasmic membrane was verified by comparing the capacity of Lys-PG to be modified by the aminogroups-reactive , membrane-impermeable fluorescent dye fluorescamine in the absence or presence of MprF ( −C ) . This assay has been developed to analyze the distribution of amino-phospholipids between inner or outer leaflets of membranes [38] , [39] and has been successfully used to compare Lys-PG distribution in spontaneously CAMP-resistant S . aureus mutants [24] , [40] . When only the synthase domain of MprF was expressed in S . aureus ΔmprF , only a small fraction of total Lys-PG was found in the outer leaflet ( Fig . 5B ) . However , when MprF ( −C ) was coexpressed with the synthase domain , the amount of Lys-PG in the outer leaflet was strongly increased and reached a similar level as in the inner leaflet . Thus , the N-terminal hydrophobic domain of MprF is required for efficient translocation of Lys-PG .
While the anionic phospholipids PG and cardiolipin are produced by virtually any bacterial species , zwitterionic or cationic lipids such as PE or Lys-PG , respectively , are produced only by certain groups of bacteria [41] . Despite extensive research efforts the actual roles of the various phospholipids , their biosynthesis , turnover , and regulation , have remained incompletely understood . Of note , the same holds true for the identity , specificity , and mode of action of proposed bacterial translocator proteins required to flip the lipids , which are generated at the inner cytoplasmic membrane leaflet , to the outer leaflet . MprF represents the paradigm of a new class of bifunctional lipid-biosynthetic enzymes mediating the transfer of amino acids to anionic phospholipids . While the S . aureus MprF mediates exclusively the biosynthesis of Lys-PG , the MprF homolog from L . monocytogenes seems to confer both , Lys-PG and Lys-cardiolipin biosynthesis [20] . MprF homologs from C . perfringens and P . aeruginosa have been shown to mediate Ala-PG production [34] , [42] . Our study represents a basis for investigating the determinants of substrate specificity of MprF . Six of the 14 TMSs plus the hydrophilic C-terminal domain were sufficient to mediate Lys-PG production in E . coli or S . aureus . The levels of Lys-PG production varied between S . aureus strains with different plasmid vectors and promoters used to express MprF or MprF variants but the level of Lys-PG did not correlate with the level of CAMP resistance indicating that only a basic amount of Lys-PG is sufficient for repulsing antimicrobial peptides provided that the lipid is translocated to the outer leaflet of the membrane . It is amazing that the Lys-PG synthase whose active center is probably located in the hydrophilic domain of MprF with its many conserved amino acid positions requires so many TMSs to function since one or two such segments should be enough to anchor the hydrophilic C-terminus in the membrane . One might speculate that six TMSs are required to embrace a PG substrate molecule and fit it into a position that may allow its lysinylation . It should be noted that even the MprF homolog with the shortest integral membrane domain found in Mycobacterium tuberculosis is predicted to harbor six TMSs ( data not shown ) , which suggests that the dependence on six TMSs is a general property of MprF-like enzymes . Previous studies on in vitro Lys-PG biosynthesis with artificially altered aminoacyl tRNAs have demonstrated that the Lys-PG synthase recognizes features of both , the tRNA and of the bound amino acid [17] , [19] . Accordingly , the lysyl group could not be transferred to PG when it was attached to a cysteinyl tRNA . However , it did not matter whether the tRNA came from S . aureus or from another bacterial species such as E . coli [18] . We identified six conserved amino acids in the C-terminal domain of MprF as essential for Lys-PG biosynthesis while exchange of two other amino acid positions led to reduced Lys-PG production . All these positions are also conserved in MprF homologs with Ala-PG synthase activity ( Fig . S2 ) , which suggests that they are not involved in specific recognition of the aminoacyl tRNA precursor and may rather play crucial roles in the enzymatic process or in non-specific binding of the substrate . Irrespective of the tRNA structure the substrate-binding domain of MprF may need basic properties to interact with the polyanionic ribonucleic acid . Accordingly , four of the six identified essential amino acid position represent cationic arginine or lysine residues that may participate in binding of tRNA phosphate groups . A most intriguing finding of our study was the fact that Lys-PG production on its own did not lead to CAMP resistance but depended on the large N-terminal integral membrane domain of MprF . Lys-PG mediates CAMP resistance by repulsing the cationic peptides from the outer surface of the membrane , which is only possible upon translocation of the lipid to the outer leaflet ( Fig . 6 ) . Of note , Lys-PG could only alter the membrane surface charge considerably in the presence of the N-terminal integral membrane domain indicating that this part of MprF is required for this lipid to reach the outer leaflet of the membrane . Moreover , Lys-PG could only be labeled efficiently by the membrane-impermeable dye fluorescamine in the presence of the N-terminal hydrophobic domain of MprF , which confirms the critical role of this protein part in Lys-PG translocation . Thus , MprF does not only synthesize Lys-PG but also accomplishes translocation of Lys-PG from the inner to the outer surface of the membrane . These two functions are allocated in the C-terminal and N-terminal domains of MprF , respectively , and can be separated into two functional proteins ( Fig . 6 ) . While lipid translocators have been investigated to some extent in eukaryotic cells [43] , such proteins have been proposed but hardly described in bacteria . It is possible that the bacterial house-keeping translocator ( s ) are more specific for the standard anionic phospholipids PG and cardiolipin , while a cationic lipid such as Lys-PG may require a dedicated translocator . It remains unclear why a small fraction of Lys-PG was detectable in the outer leaflet of the cytoplasmic membrane even in the absence of the flippase domain of MprF . Phospholipids may be able to flip spontaneously with low efficiency as proposed recently [44] or one of the house-keeping flippases may have residual activity for Lys-PG . Lipid translocators have been classified into energy-dependent ( flippases or floppases ) and energy-independent ( scramblases ) transporters [43] . MprF does not contain conserved ATP-binding or other sequence motives indicative of energy consumption . Therefore , it remains unclear if MprF can accomplish an asymmetric distribution of Lys-PG . Nevertheless , recent studies suggest that Lys-PG can be asymmetrically distributed between the inner and outer leaflets of the membrane in S . aureus depending on the individual strain background [24] . The increasing resistance of major bacterial pathogens raises the specter of untreatable infections as in the pre-antibiotics era . MRSA are now more and more prevalent in the community and only a few antibiotics of last resort such as daptomycin have remained effective against such highly pathogenic S . aureus clones . As S . aureus can overcome even daptomycin by simple point mutations in mprF new strategies for antibacterial chemotherapy are urgently needed . Inhibitors for highly conserved immune evasion factors such as mprF that would render a wide range of bacteria susceptible to endogenous human defense mechanisms and cationic antibiotics such as daptomycin should be increasingly considered . Our study represents a basis for more detailed investigations on the structure and mode of action of MprF-like aminoacylphospholipid synthases and they should enable the systematic search for inhibitors for this class of enzymes .
Q2G2M2: Staphylococcus aureus MprF; Q5HPI1: Staphylococcus epidermidis MprF homolog; C0H3X7: Bacillus subtilis MprF homolog; C0X347: Enterococcus faecalis MprF homolog; Q8DWT2: Streptococcus agalactiae MprF homolog; Q71YX2: Listeria monocytogenes MprF homolog; Q88YQ7: Lactobacillus plantarum MprF homolog; Q8FW76: Brucella suis MprF homolog; Q9I537: Pseudomonas aeruginosa MprF homolog; Q0SSM7 and Q0STHJ7: Clostridium perfringens MprF homologs . | Certain bacterial immune-evasion factors such as the MprF protein are highly conserved in many bacterial pathogens and represent attractive targets for new ‘anti-virulence’ drugs . MprF , initially discovered in the major human pathogen Staphylococcus aureus , protects bacteria against ‘innate human antibiotics’ such as the defensin peptides . In addition , MprF has recently been implicated in resistance to the new defensin-like antibiotic daptomycin . MprF modifies bacterial membrane lipids with the amino acid l-lysine , which leads to electrostatic repulsion of the membrane-damaging peptides . The molecular mechanism of MprF has remained largely unknown . We demonstrate that MprF represents a novel bifunctional type of enzyme . The N- and C-terminal domains of MprF are both required for mediating antimicrobial peptide resistance but they can be expressed as two separate proteins without loss of function indicating that they represent distinct functional modules . While the C-terminal domain accomplishes lipid lysinylation the N-terminal membrane-embedded domain is required to expose the lysine lipid at the outer surface of the bacterial membrane where it is able to repulse the antimicrobial peptides . These findings unravel the molecular basis of an important bacterial immune evasion mechanism and they may help to employ MprF as a target for new anti-virulence drugs . | [
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] | 2009 | The Bacterial Defensin Resistance Protein MprF Consists of Separable Domains for Lipid Lysinylation and Antimicrobial Peptide Repulsion |
Uncomplicated infections of the urinary tract , caused by uropathogenic Escherichia coli , are among the most common diseases requiring medical intervention . A preventive vaccine to reduce the morbidity and fiscal burden these infections have upon the healthcare system would be beneficial . Here , we describe the results of a large-scale selection process that incorporates bioinformatic , genomic , transcriptomic , and proteomic screens to identify six vaccine candidates from the 5379 predicted proteins encoded by uropathogenic E . coli strain CFT073 . The vaccine candidates , ChuA , Hma , Iha , IreA , IroN , and IutA , all belong to a functional class of molecules that is involved in iron acquisition , a process critical for pathogenesis in all microbes . Intranasal immunization of CBA/J mice with these outer membrane iron receptors elicited a systemic and mucosal immune response that included the production of antigen-specific IgM , IgG , and IgA antibodies . The cellular response to vaccination was characterized by the induction and secretion of IFN-γ and IL-17 . Of the six potential vaccine candidates , IreA , Hma , and IutA provided significant protection from experimental infection . In immunized animals , class-switching from IgM to IgG and production of antigen-specific IgA in the urine represent immunological correlates of protection from E . coli bladder colonization . These findings are an important first step toward the development of a subunit vaccine to prevent urinary tract infections and demonstrate how targeting an entire class of molecules that are collectively required for pathogenesis may represent a fundamental strategy to combat infections .
The urinary tract is among the most common sites of bacterial infection . Over half ( 53% ) of all women and 14% of men experience at least one urinary tract infection ( UTI ) in their lifetime [1] , [2] , leading to an average of 6 . 8 million physician office visits , 1 . 3 million emergency room visits , and 245 , 000 hospitalizations per year , with an annual cost of over $2 . 4 billion in the United States alone [3] . Escherichia coli is the infectious agent in more than 80% of uncomplicated UTIs , which occur in patients with an anatomically normal urinary tract devoid of structural abnormalities or inflammatory lesions [4] . In addition to symptoms of acute cystitis and pyelonephritis caused by UTI , a number of more serious conditions are often associated with these infections . Upper UTIs in young children can cause permanent kidney damage . An estimated 57% of children with acute pyelonephritis develop renal scarring [5] . UTIs are classically treated with trimethoprim/sulfamethoxazole or ciprofloxacin to eradicate the infecting strain . However , there is documentation of increasing resistance to these antibiotics [6] . Furthermore , following successful primary treatment , recurrent infections frequently occur , with an estimated 27% of women experiencing a recurrence within six months of the original infection and 2 . 7% experiencing a third infection during this time [7] . The reservoir for reinfection remains unclear , with same-strain episodes making up between 25–100% of recurrent UTI cases [reviewed in [8]] . Consequently , these complications pose a significant challenge to UTI treatment and suggest that a vaccine to prevent UTI would alleviate this major source of morbidity and economic burden . Indeed , a number of groups have sought to stimulate protective immunity against UPEC . Early studies utilized various capsular and LPS core antigens and heat-killed bacteria to elicit protective immune responses [9] , [10] . Recently , whole cell or cell extract preparations have been shown to provide modest short-term protection in some individuals [11] , [12] . Because of their abundance on the cell surface and demonstrated role in UPEC pathogenesis [13] , fimbriae have been attractive targets for defined protein subunit vaccines . For example , immunization with the type 1 fimbrial adhesin , FimH , conjugated to its periplasmic chaperone , FimC , reduced murine bladder colonization by 99 . 9% , as well as provided protection in a primate model [14] , [15] . Additionally , subunit vaccines based on several other surface-exposed molecules such as P fimbriae ( PapDG complex ) , alpha hemolysin , Dr fimbriae , the salmochelin receptor IroN , and a conjugation of capsule polysaccharide K13 with diphtheria toxoid have been shown to induce at least some immune response in immunized animals [16]–[20] . However , although much research has focused on the development of a vaccine against UPEC , none are available in the United States . Large-scale reverse vaccinology approaches offer an alternative to traditional vaccine design . Pioneered by successful work using Neisseria meningitidis , this technique applies genomic and bioinformatic methods to identify novel vaccine targets [21] . Recently applied to extraintestinal pathogenic E . coli ( ExPEC ) , a pathotype to which UPEC belongs , a subtractive hybridization study identified surface-exposed antigens specific to ExPEC and found that several of these proteins protected immunized mice from lethal sepsis [22] . Due to the limited success of previous UTI vaccine design strategies , we hypothesized that a functional vaccinology approach would identify vaccine targets of UPEC in an unbiased manner that could elicit protective immunity . Here we describe the use of previously established genomics and proteomics data to identify six pathogen-associated outer membrane iron receptors ( ChuA , Hma , Iha , IreA , IroN and IutA ) as putative vaccine targets of UPEC . Each of these 71–84 kDa proteins is predicted to form a transmembrane beta-barrel in the outer membrane , with a series of loops extending extracellularly [23] . Facilitating import of specific iron sources , these receptors mediate uptake of siderophores , secreted bacterial iron-chelating molecules , or host heme-derived iron . Because iron acquisition is necessary for bacterial pathogenesis and it is well known that the urinary tract is an iron-limited environment , iron acquisition via these receptors is crucial for UPEC infection [24] . Consequently , deletion of the siderophore receptor IreA , heme receptors ChuA or Hma , enterobactin receptor Iha , salmochelin receptor IroN , or aerobactin receptor IutA all decrease the fitness of UPEC in the murine urinary tract [24]–[28] . In this study , we demonstrate that an unbiased , rational vaccinology approach consistently identified a class of molecules involved in iron acquisition as vaccine candidates and that intranasal immunization with these UPEC outer membrane iron receptors provides protection from UTI . Additionally , we show that antigen-specific antibody and cytokine responses are generated in response to vaccination with iron receptor proteins , of which , the former correlated with protection . Therefore , we propose that this class of molecules is promising as protective vaccine targets against UPEC and , because of their conserved function of iron acquisition for pathogenesis , could potentially be adopted for the development of vaccines against other Gram-negative bacterial infections .
To identify bacterial proteins that could be used as vaccine targets against UPEC infection , we utilized a functional vaccinology approach , combining both genomics and proteomics techniques . To begin , criteria defining UPEC vaccine targets were established and data from our previously-described studies assembled to identify proteins meeting these requirements . Of the 5379 predicted proteins in E . coli pyelonephritis strain CFT073 , only six proteins ( Table 1 ) met all five of our established criteria: high in vivo expression , induction during growth in human urine , surface exposure , antigenicity , and pathogen-specificity . Transcriptomic and proteomic data were evaluated to identify candidates meeting the expression and antigenicity criteria . Data from an in vivo transcriptome study indicated that genes encoding iron acquisition system components were among those most highly upregulated in CFT073 isolated from the urine of experimentally infected CBA/J mice [29] . When all genes were ranked in order of expression level in vivo , these iron acquisition genes , specifically outer membrane iron receptors , were among the top 18% most highly expressed in the murine urinary tract ( Table 1 ) . Similarly , when outer membrane proteins ( OMPs ) , which are partially surface-exposed , were isolated from CFT073 cultured in human urine ex vivo and compared with OMPs isolated from bacteria cultured in Luria broth , these iron receptors were the most highly induced proteins [30] . Further , the vaccine candidates listed in Table 1 comprised six of the top seven human urine-induced OMPs . In addition to bacteria isolated from urine , our and other groups have observed expression of these outer membrane iron receptors by bladder cell-associated UPEC , both in vitro [31] and in vivo [32] . Finally , an immunoproteomics study identified these iron receptors as antigenic; that is , they reacted with antisera from mice chronically infected with UPEC strain CFT073 , indicating that these proteins elicited a humoral response during experimental UTI [31] . As UPEC strains represent a subset of strains that are genetically distinct from commensal E . coli , a vaccine directed against UPEC should specifically target pathogenic strains . Toward this end , a comparative genomics hybridization study identified 131 genes that were present in all UPEC strains analyzed ( n = 10 ) , but none of the fecal-commensal E . coli isolates tested ( n = 4 ) [33] . Among these UPEC-specific genes were two encoding outer membrane heme receptors , chuA and hma . Furthermore , dot blot analysis of a collection of UPEC and fecal-commensal E . coli isolates identified several of these iron OMP genes ( chuA , hma , iroN , and iutA ) as present more frequently among pathogens than non-pathogens [31] . Even genes that were not statistically more frequent among uropathogens ( iha and ireA ) were nonetheless present at relatively low frequencies in commensals . Of the 5379 predicted proteins in UPEC strain CFT073 , six candidate antigens , all outer membrane iron receptors , emerged from our series of genomics and proteomics studies as uniformly highly ranked potential vaccine targets ( Table 1 ) . This screening process strongly suggested that broadly targeting an entire class of molecules involved in iron acquisition could be an effective strategy to develop a protective UTI vaccine . The six iron receptor vaccine candidates , ChuA , Hma , IutA , IreA , Iha , and IroN were expressed and purified as affinity-tagged recombinant proteins . Consistent with the predicted structure of these antigens , the CD spectrum of refolded purified Hma displayed a trough at 218 nm , which is characteristic of a β-sheet-rich conformation ( Fig . S1 ) . The six purified protein antigens were each biochemically cross-linked to the adjuvant cholera toxin ( CT ) at a ratio of 10∶1 ( antigen∶CT ) and groups of mice ( n = 15–20 ) were intranasally inoculated with either an antigen-CT complex or CT alone . Following primary immunization ( day 0 ) and booster doses ( days 7 and 14 ) , the animals were transurethrally challenged with UPEC strain CFT073 and protection was assessed at 48 h post infection ( hpi ) by determining CFUs in the urine , bladder , and kidneys . Of the six candidates , three conferred protection against experimental challenge with UPEC . The heme receptor , Hma , protected mice against colonization of the kidney . Hma-vaccinated mice demonstrated nearly a 3-log reduction in median CFU/g in the kidney ( P = 0 . 008 ) and 13/20 mice had undetectable levels of bacteria ( <100 CFU/g ) in the kidneys ( Fig . 1B ) . The putative siderophore receptor IreA showed significant protection and demonstrated a 3-log reduction in median CFU/g in the bladder ( P = 0 . 035 ) ( Fig . 1D ) . For IreA , 9/15 vaccinated mice had undetectable levels of bacteria in the bladder . The siderophore receptor for aerobactin , IutA , conferred significant protection against UPEC challenge in both the bladder and kidneys . Mice vaccinated with IutA displayed one-log CFU/g reduction in both the bladder ( P = 0 . 009 ) and kidneys ( P = 0 . 007 ) ( Fig . 1E ) . This showed that mucosal immunization in the nares generates a protective effect at distal sites , the bladder and kidneys . Not all antigens selected as candidates provided protection against experimental UTI . Both ChuA and Iha recombinant proteins when cross-linked to cholera toxin failed to elicit significant protection against challenge with UPEC strain CFT073 ( Fig . 1A and C ) . All of the native protein vaccines were well tolerated in immunized mice and no animals died following vaccination , with the exception of ChuA , which was lethal in 11/30 mice ( surviving mice were not protected ) . Since a significant reduction in post-challenge CFU was observed for Hma and IreA vaccinated mice , these antigens were tested to determine if similar levels of protection could be generated following heterologous challenge with another UPEC isolate . Groups of 20 mice were immunized as described with either Hma , IreA , or CT alone and CFU were determined at 48 hpi following challenge with UPEC strain 536 . In these experiments , Hma vaccinated mice were significantly protected from heterologous challenge and displayed >10-fold reduction in median CFU/g in the bladder ( P = 0 . 0287 ) ( Fig . 2 ) . Vaccination with IreA significantly protected mice from infection with UPEC strain 536 and these mice demonstrated a log-fold decrease in median CFU/g in the kidneys ( P = 0 . 0379 ) ( Fig . 2 ) . Peptides ( 30 aa ) corresponding to single predicted extracellular loops in both the salmochelin siderophore receptor IroN ( aa 491–520 ) and aerobactin receptor IutA ( aa 467–498 ) were also assessed to determine their use as potential immunogens . Extracellular loops were selected based on their predicted topology to direct an antibody response against surface exposed residues . These peptides also represent highly conserved loops within the salmochelin and aerobactin receptors; the IroN peptide has >90% identity to 37 siderophore receptor sequences including urinary tract isolates 536 , UTI89 , and 83972 . The IutA peptide has >76% identity ( 23/30 aa ) among 15 aerobactin receptor sequences present in various pathogenic E . coli , including uropathogenic and extraintestinal isolates UMN026 [34] , IAI39 , and S88 [35] . Groups of mice ( n = 15 ) were inoculated as previously described with either peptide mixed with CT or CT alone and protection was assessed at 48 hpi following infection with UPEC strain CFT073 . These peptides failed to elicit significant protection in the urine , bladder , or kidneys of mice , however , there was nearly a 2-log reduction in CFU/g in the kidneys for both IroN ( P = 0 . 053 ) and IutA ( P = 0 . 078 ) peptides , demonstrating a strong trend towards protection ( Fig . 1F ) . These results imply that peptides may be suitable for development of a UTI vaccine but may be more efficacious if cross-linked or fused to a carrier molecule . Together , these findings show that targeting an entire functional class of molecules involved in iron acquisition is an effective strategy to identify protective vaccine candidates that significantly reduce bacterial colonization during ascending UTI following experimental challenge with UPEC . Proinflammatory cytokines are crucial for orchestrating protective immune responses against pathogens . Secretion of two major proinflammatory cytokine mediators , IFN-γ and IL-17A ( IL-17 ) , were measured from the splenocytes of mice immunized with adjuvant alone ( CT ) , IreA ( a protective antigen ) , or Iha ( a non-protective antigen ) following vaccination . Cells were analyzed both pre- and post-challenge to gauge the immune response to antigenic stimulation in vivo . Splenocytes were cultured in vitro in the presence of 1 µg/ml of the corresponding purified antigen used for immunization . Cytokines were measured in the supernatant by ELISA after 48 h incubation . Splenocytes from Iha-vaccinated and IreA-vaccinated mice collected both before ( − ) and after ( + ) challenge demonstrated significant antigen-specific secretion of IFN-γ and IL-17 when compared to the corresponding splenocytes from CT control mice ( P<0 . 05 ) ( Fig . 3A and B ) . Unstimulated splenocytes from any group of mice lacked detectable levels of IFN-γ or IL-17 ( data not shown ) . Interestingly , splenocytes derived from Iha- and IreA-vaccinated mice post-challenge secreted less pro-inflammatory cytokines than pre-challenge cells ( P<0 . 003 ) ( Fig . 3A and B ) . Both IFN-γ and IL-17 secreting splenocytes were significantly decreased post-challenge ( P<0 . 003 ) in IreA-vaccinated mice ( Fig 3B ) , whereas only IL-17 secreted splenocytes were significantly decreased ( P = 0 . 0007 ) in mice vaccinated with Iha ( Fig . 3A ) . Overall , these results indicated that vaccinated mice generate antigen-specific cells that are capable of secreting IFN-γ and IL-17 , two important pro-inflammatory cytokine mediators , in response to in vitro restimulation . No significant correlation was found between cytokine production and reduction in CFU post-challenge . However , the decrease in both IFN-γ and IL-17 secretion from vaccinated mice post-challenge as compared to pre-challenge was only observed following immunization with antigens that protected mice from infection ( Fig . 3B ) and was not seen following immunization with non-protective antigens ( Fig . 3A ) . To evaluate the humoral immune response at the primary site of infection , the bladder mucosa , levels of antigen-specific IgA in urine were measured by ELISA . To account for variability in the amount and concentration of urine from each mouse , collections were pooled for use in an indirect ELISA to measure antigen-specific IgA . Urine from IreA- ( Fig . 4A ) and IutA-vaccinated ( Fig . 4B ) cohorts , which had significantly decreased bladder colonization upon challenge , had the highest fold increases in IgA ( 34-fold and 6 . 2-fold , respectively ) post-vaccination . Antigens that did not generate significant decreases in colonization in the bladders of vaccinated mice had more modest fold-increases in urine IgA post-vaccination ( 2 . 2-fold for Hma , 2 . 0-fold for ChuA , and 1 . 7-fold for Iha ) ( Fig . 4C–E ) . Correspondingly , peptide antigens representing extracellular loops of IroN and IutA did not significantly protect from infection in the bladder , and IgA was at background levels in the urine of these animals ( Fig . 4F ) . These findings demonstrate that vaccination with antigens , IreA and IutA , which provide significant protection in the bladder from experimental challenge with UPEC , generate significant induction of antigen-specific IgA secretion that is detectable in urine of immunized animals . To evaluate the systemic humoral immune response to our vaccine candidates , the levels of serum antigen-specific antibodies generated by vaccinated mice were compared to those of CT control mice . Serum was collected by infraorbital ocular bleed before vaccination and after vaccination prior to transurethral challenge with UPEC strain CFT073 . For each protein and loop peptide antigen tested , there was a significant increase of antigen-specific IgG in post-vaccination serum compared to the corresponding pre-immune serum ( P = 0 . 0002 ) ( Fig . 5A–F ) . In most cases , there was no difference in IgG levels between the pre- and post-vaccinated sera from CT control mice . Additionally , all post-vaccination sera had significantly higher levels of IgM than pre-vaccination sera ( P<0 . 05 ) ( Fig . 5A–F ) . Although both IgG1 and IgG2a increased from pre- to post-vaccination , there was no skew toward production of IgG1 or IgG2a in any group ( data not shown ) . This phenomenon is not unusual for protein antigens , as they can stimulate production of both Th1 and Th2 cells by virtue of their broad MHC class II peptide repertoire [36] . None of the samples tested showed appreciable increases in serum IgA ( data not shown ) . These findings show that vaccinated mice generate target-specific antibodies , both innate IgM and class-switched IgG in response to intranasal immunization with iron-receptor antigens . IgG and IgM are often monitored to determine the level of class switching undergone by B cells . In our studies , all vaccinated animals demonstrated significant increases in both serum IgG and IgM from pre- to post-vaccination . However , Hma- , IreA- , and IutA-vaccinated ( protected ) animals displayed more dramatic IgG increases than IgM when compared to ChuA- , Iha- , and peptide loop antigen-vaccinated ( unprotected ) animals ( compare Fig . 5B , D , and E to Fig . 5A , C , and F ) . This finding suggested that these animals have been sufficiently stimulated to class switch to more effective antibody isotypes . To more quantitatively assess this trend and the relationship of serum IgG and IgM to protection from UTI , we first calculated a Class Switch Index using the data from all of the immunized mice ( n = 203 ) . The Class Switch Index is the ratio of the median change in sera IgG to the median change in sera IgM for each group of vaccinated mice . To account for an increase in non-specific antibodies , the median changes in sera IgG and IgM of CT-treated mouse cohorts were subtracted from the corresponding antigen-vaccinated group values . The class switch indices were then plotted against the normalized post-challenge median bladder CFU/g to determine if any relationship existed between antibody class-switching and protection from cystitis . Because infectivity can vary between experiments , the median CFU/g from each antigen-vaccinated group was divided by the median CFU/g of the CT control group for normalization . Finally , both the Class Switch Index and normalized median CFU/g values were log10 transformed for comparison on a linear scale . This analysis demonstrated that there was a significant correlation between the Class Switch Index and the CFU/g in the bladder ( P = 0 . 0014 ) ( Fig . 6A ) , suggesting that a decrease in bladder colonization may be attributed to the relative amount of antibody class-switching from IgM to IgG in mice vaccinated with protective antigens . No significant correlation was found between antibody class-switching from IgM to IgG and CFU/g in the kidneys . However , as predicted , there is also a strong correlation between the amount of antigen-specific IgA in urine and protection from UPEC infection in the bladder ( Fig . 6B ) ; specifically , increases in urine IgA corresponded to decreases in bladder CFU ( P = 0 . 0165 ) . These findings show that antibody class-switching and urinary IgA are each an immunological correlate of protection against UTI caused by E . coli .
UTIs caused by UPEC represent a significant healthcare burden that could be alleviated by the development of a vaccine that would provide protection from these infections . Toward this aim , we described the use of a multi-pronged , functional vaccinology approach that uniformly singled out one class of molecules , those involved in iron acquisition , as potential targets . The screening process selected six vaccine candidates from the 5379 predicted proteins encoded within the E . coli CFT073 genome . The six vaccine candidates meet all of the following criteria: predicted to be surface-exposed , present in the bacterial outer membrane [30] , [31] , conserved among UPEC strains [31] , [33] , transcriptionally upregulated in vivo [29] , induced during culture in human urine [30] , and antigenic [31] . These vaccine targets , ChuA , Hma , Iha , IreA , IroN , and IutA , are all outer membrane β-barrel proteins that function as receptors for iron-containing compounds . Of these , we found that intranasal immunization with Hma , IreA , or IutA generates an antigen-specific humoral response , antigen-specific production of IL-17 and IFN-γ , and provides significant protection against experimental infection with UPEC . Site-specific protection was observed for the antigens that provided the greatest reduction in bacterial counts , Hma and IreA . Mice immunized with the IreA vaccine were significantly protected from CFT073 colonization only in the bladder , with >2-log reduction in the median CFU/g and 60% of mice having undetectable levels of bacteria within that organ . The dramatic reduction in the level of bacterial colonization within the bladder may have resulted in reduced numbers of bacteria ascending to the kidneys that could account for the modest reduction in bacteria seen in the kidneys in the IreA-vaccinated mice following challenge with either UPEC strain CFT073 or 536 . In contrast to the bladder protection seen with IreA , Hma significantly reduced the number of bacteria colonizing the kidneys and , in over half of the animals , prevented kidney colonization completely . Despite the significant protection in the kidney , immunization with the Hma vaccine did not reduce the level of bacteria able to colonize the bladder . The kidney-specific protection of the Hma vaccine may reflect the biological function of Hma for UPEC during colonization of the urinary tract , UPEC that are unable to produce Hma have reduced fitness only within the kidney during experimental UTI [28] . The site-specificity for the Hma vaccines suggests that the immune response may perturb the normal function of this outer membrane heme receptor , perhaps by antibody interference with ligand-binding domains or selective immune targeting of bacteria that exhibit tissue-specific expression of Hma . Induction of the cytokines IL-17 and IFN-γ suggests that the cellular response may be important for the generation of a protective immune response . To assess cellular responses to immunization , we analyzed antigen-specific production of two cytokines known to be critical for mediating anti-bacterial activities within the host , IFN-γ and IL-17 , from splenocytes post-immunization both before and after challenge . Production of IFN- γ has been previously shown to be important for the control of infection within the urinary tract [37] and IL-17 has been shown to promote the recruitment of neutrophils in response to bacterial infection [38] . IL-17 has been recently appreciated as an important mediator to control infection by Salmonella , Listeria , pathogenic Mycobacterium , E . coli , and Klebsiella [39]–[43] . Both IFN- γ and IL-17 were produced in response to immunization with IreA and Iha . Splenocytes obtained from vaccinated mice post-challenge showed a reduction in antigen-specific cytokine secretion of IFN- γ and IL-17 , suggesting that antigen-specific lymphocytes may be homing from the spleen to the site of infection . Further , the post-challenge reduction in both antigen-specific cytokines tested was only significant for the IreA vaccine , which generates a protective response in the bladder . Mucosal immunization is considered the most effective means to develop a UTI vaccine and we have shown previously that intranasal immunization with MR/P fimbria is effective in protecting mice against UTI caused by Proteus mirabilis , an agent of complicated UTI [44] . Because local immunization of the urethra is not practical , the migration of immune cells between mucosal sites can be exploited during intranasal inoculation with antigen [45] . We reasoned that intranasal immunization would generate a distant mucosal response in the genitourinary tract against UPEC in vaccinated animals . Consistent with this , we observed that the two vaccines , IreA and IutA , which conferred significant protection in the bladder , had the greatest antigen-specific production of secretory IgA detectable in their urine . For the IreA vaccine , the increase in IgA in urine provides evidence that may account for the bladder-specific protection seen in mice immunized with this vaccine . Conversely , antigens that did not induce protective immunity within the bladder did not generate a similar increase in the level of IgA . Based upon these findings , relative levels of IgA in the urine significantly correlated with protection in the bladder . That is , when examining all of the vaccine candidates and bacterial counts within the bladder , there is a direct relationship between a reduction in CFU in the bladder and increased IgA in the urine . This immunological correlate suggests that a mucosal response and vaccine that generates IgA is sufficient to provide protection from UPEC colonization in the bladder . This finding is consistent with other studies that have shown that antibodies specific for the infecting E . coli strains leads to resolution of cystitis and that oral immunization with outer membrane proteins generates an antigen-specific IgA mucosal response against UPEC [46] , [47] . The finding that IgA in the urine is produced in response to intranasal immunization indirectly shows that class-switching of antibody isotypes is occurring in vaccinated animals . Analysis of serum antibodies from immunized mice shows that antigen-specific IgM is produced in response to all the vaccine candidates tested . Further , antigen-specific IgG is markedly increased in response to each vaccine when compared to pre-immune sera . For the Hma and IutA vaccines , which provided significant protection in the kidney , it is possible that circulating IgG or antigen-specific plasma cells contribute to the observed reduction of bacterial colonization . Interestingly , the vaccines that significantly protected mice against UPEC infection , Hma , IreA , and IutA , displayed a dramatic increase in antigen-specific IgG relative to IgM . This suggests that class-switching of antibody isotypes is indicative of a protective immune response . To assess this effect , we defined a Class Switch Index by comparing the ratio derived from the median changes in antigen-specific IgG to that of IgM , normalized to CT and plotted those values against the CT-normalized log-ratio of CFU/g in the bladder post-challenge . By plotting normalized CFU/g values against the Class Switch Index , we found a significant correlation between class-switching antibody isotypes and protection from bacterial colonization in the bladder . There has been limited success to develop an efficacious UTI vaccine that would provide protection from infection by UPEC . Immunization with Solco-Urovac , a vaccine formulation that is comprised of inactivated uropathogenic bacteria , generates urinary IgA [48] and vaginal immunization with this vaccine provides protection that lasts 8–12 weeks in humans [11] . If administered more frequently , vaccination with Solco-Urovac can increase time to recurrence to six months [49] . This suggests this vaccine might be useful to prevent recurrent UTIs in susceptible populations . The major Type 1 fimbrial adhesin of UPEC , FimH , has also been used as a vaccine candidate and provided protection in mice [14] and prevented bacteriuria in primates [15] . One of the vaccine candidates we identified and tested , IroN , has been used previously to immunize mice , and similar to our results with IroN , was shown to generate antigen-specific IgG but not IgA [17] . In contrast to our findings , this group found that IroN protected mice against renal infection . This difference could be accounted for by the fact that we used an IroN extracellular loop-derived peptide mixed with CT and the previous study used denatured protein without adjuvant [17] . More recently , it has been shown that intranasal immunization with formalin-killed UPEC lacking capsular polysaccharides and O antigen generates a specific humoral response in mice; however , the protective efficacy of this vaccine is not known [50] . Lastly , using a lethal challenge model of extraintestinal pathogenic E . coli infection , it was found that vaccination with IroN , but not ChuA , increased survival in immunized mice [22] . Despite these advances , a UTI vaccine that confers long-term protection against uncomplicated UTIs is currently lacking . The rational large-scale screening process we described identified six surface-exposed outer membrane receptors for iron compounds . These represent vaccine candidates because they are conserved among uropathogenic strains and largely absent from commensal bacteria , induced during growth in human urine and during experimental UTI , and are antigenic . Iron acquisition is well known to be a common trait necessary for bacterial pathogenesis and by targeting receptors involved in this process it may be possible to disrupt this critical function in addition to pathogen neutralization and opsonization . Intranasal inoculation with three of six vaccine candidates ( IreA , Hma , IutA ) provided protection from challenge with uropathogenic E . coli and this study provides the basis for the development of a subunit vaccine that would incorporate these protective antigens to provide broader efficacy within the urinary tract and across uropathogenic isolates . Importantly , we have shown that focusing on an entire class of proteins that are involved in a singular function necessary for pathogenesis rather than a single protein may be fundamental strategy that could be generally adopted during the development of vaccines against pathogens .
E . coli strain CFT073 was isolated from the blood and urine of a patient with acute pyelonephritis [51] . E . coli strain 536 was isolated from a patient with acute pyelonephritis [52] . Unless otherwise noted , bacteria were cultured in Luria broth ( LB ) containing appropriate antibiotics ( 100 µg/ml ampicillin , 25 µg/ml kanamycin , and/or 20 µg/ml chloramphenicol ) at 37°C with aeration . Female CBA/J mice were transurethrally inoculated as previously described [53] . Prior to inoculation , overnight E . coli CFT073 cultures were harvested by centrifugation ( 3000×g , 30 min 4°C ) and resuspended in PBS to an OD600 of 4 . 0 , equivalent to 4×109 CFU/ml . Bacterial suspension ( 50 µl/mouse ) was delivered transurethrally using a sterile 0 . 28 mm inner diameter polyethylene catheter connected to an infusion pump ( Harvard Apparatus ) , with total inoculum of 1×108 CFU/mouse . For determination of CFUs , organs were harvested from euthanized animals at 48 h post-inoculation and homogenized in PBS with a GLH homogenizer ( Omni International ) . Bacteria in tissue homogenates were enumerated by plating on Luria-Bertani agar containing 0 . 5 g/L NaCl using an Autoplate 4000 spiral plater ( Spiral Biotech ) . Colonies were enumerated using a QCount automated plate counter ( Spiral Biotech ) . Blood was collected as necessary from anesthetized mice by an infraorbital bleed using 1 . 1 to 1 . 2 mm Micro-Hematocrit Capillary Tubes ( Fisher ) and serum was separated using Microtainer Serum Separator Tubes ( Becton Dickinson ) . Six- to eight-week old mice were used for these studies and animals were ≤15 weeks old at the conclusion of all experiments . All procedures were conducted according to protocols approved by University Committee on the Care and Use of Animals at the University of Michigan . Genes encoding the selected antigens were PCR-amplified from CFT073 genomic DNA and cloned into either pBAD-myc-HisA ( Invitrogen ) or pET30b+ ( Novagen ) . Recombinant protein expression from pBAD ( Hma , IutA , ChuA ) was induced in E . coli TOP10 cultured to OD600 = 0 . 8 by addition of L-arabinose to 100 µM for 4 h . Proteins expressed from pET ( Iha , IreA ) were over-expressed in E . coli BL21 ( DE3 ) pLysS cultured in Terrific broth ( 12 g/L tryptone , 24 g/L yeast extract , 2 . 3 g/L KH2PO4 , 12 . 5 g/L K2HPO4 , 4% glycerol ) to OD600 = 1 . 0 at 37°C and induced overnight with 1 mM isopropyl β-D-1-thiogalactopyranoside ( IPTG ) . Induced cultures were harvested by centrifugation ( 8 , 000×g , 4°C , 10 min ) , resuspended in 10 mM HEPES , pH 7 , and 100 U Benzonase nuclease ( Sigma ) . Bacteria were lysed by two passages though a French pressure cell ( 20 , 000 psi ) and the lysate was cleared by centrifugation ( 8 , 000×g , 4°C , 10 min ) . Bacterial membranes were pelleted from the cleared lysate by ultracentrifugation ( 112 , 000×g , 4°C , 30 min ) and the membrane pellet resuspended in 5 ml 100 mM NaH2PO4 , 10 mM Tris-HCl , 8 M urea , 1% ASB-14 , pH 8 . 0 . His6-tagged proteins were purified on nickel-nitriloacetic acid-agarose columns ( Qiagen ) under denaturing conditions according to the manufacturer's instructions ( The QIAexpressionist ) . Eluted purified proteins were renatured by dialysis at 4°C into a final solution containing 0 . 05% Zwittergent in PBS , pH 7 . 5 and quantified using the BCA protein assay ( Pierce ) . Putative extracellular loops of IroN and IutA were predicted using the PRED-TMBB program ( http://biophysics . biol . uoa . gr/PRED-TMBB/ ) . 30-mer peptides corresponding loop 6 of IutA and loop 7 of IroN ( IroN: YLLYSKGNGCPKDITSGGCYLIGNKDLDPE; IutA: VDDIDYTQQQKIAAGKAISADAIPGGSVD ) were synthesized to ≥96% purity by Invitrogen . Purified antigens were chemically cross-linked to cholera toxin ( CT ) ( Sigma ) at a ratio of 10∶1 using N-succinimidyl 3- ( 2-pyridyldithio ) propionate ( SPDP ) ( Pierce ) according to the manufacturer's recommendations . Peptide antigens were dissolved in 1 mM EDTA in PBS , mixed with reduced CT , and incubated at 4°C for 18 h . All immunizations were administered intranasally in a total volume of 20 µl/animal ( 10 µl/nare ) . Animals received a primary dose on day 0 of 100 µg crosslinked antigen ( containing 10 µg CT ) or 10 µg CT alone . Two boosts of 25 µg antigen ( crosslinked to 2 . 5 µg CT ) or 2 . 5 µg CT alone were given on days 7 and 14 , and mice were challenged as described above . Single-cell suspensions were made from spleens by forcing organs though 40 µm Cell Strainers ( BD Falcon ) . Red blood cells were lysed for 2 min using 8 . 02 mg/ml NH4Cl , 0 . 84 mg/ml NaHCO3 , 0 . 37 mg/ml EDTA in distilled water . Final suspensions were made in RPMI ( supplemented with L-Glutamine , Gibco ) with 1% sodium pyruvate , 1% L-glutamine , 1% penicillin/streptomycin , 1% non-essential amino acids , 10% fetal bovine serum ( FBS ) , 0 . 001% 50 mM β-mercaptoethanol . Splenocytes ( 1 . 5×106 cells/ml ) were cultured with either medium alone or with 1 µg/ml purified antigen . After incubation of cells at 37°C , 5% CO2 for 48 h , supernatants were harvested and stored at −20°C . For indirect serum ELISA , EIA/RIA medium binding 96-well ELISA plates ( Corning ) were coated at rt overnight with 5 µg/ml purified protein ( for serum ) or 10 µg/ml purified protein ( for urine ) diluted in carbonate buffer , pH 9 . 8 . Non-specific binding sites were blocked with with 10% FBS , 0 . 04% NaN3 in PBS at room temp for 1 h . 1∶128 dilutions of mouse serum in blocking buffer or 50 µl of pooled undiluted urine were applied to wells in two to five replicates . Goat anti-mouse IgA , IgG , and IgM were obtained conjugated to alkaline phosphatase ( Southern Biotech ) . Alkaline phosphatase substrate , p-nitrophenyl phosphate ( 1 mg/ml ) ( Sigma ) , was diluted in carbonate buffer and applied to wells at rt until color developed . The reaction was stopped with NaOH and read with a μQuant plate reader ( Bio-Tek Instruments , Inc . ) at a wavelength of 405 nm . For cytokine ELISA , purified IL-17A , IFN-γ , and their corresponding matched antibody pairs were obtained from R&D Systems and used according to the manufacturer's recommendations . For detection , OPD Easy-tablets ( 2 mg/tablet , Acros Organics ) were diluted and applied until color developed . The reaction was stopped by addition of 100 µl 6 N H2SO4 and read with a plate reader at a wavelength of 490 nm . Plates were washed by flooding all wells four times with wash buffer between all incubations . All graphing and statistical analyses were done using GraphPad Prism 5 . Significance was determined using Mann-Whitney tests . Correlates of protection were determined using the Pearson correlation coefficient with linear regression to generate a best fit line . All statistics were conducted using 95% confidence intervals where applicable . | Because urinary tract infections ( UTIs ) are a significant healthcare burden , it would be beneficial to develop a vaccine to prevent uncomplicated UTI caused by Escherichia coli . Using a large-scale screening process we uniformly identified proteins involved in iron uptake as potential vaccine candidates against E . coli . Iron acquisition is a critical function required by bacteria in order to cause infections . In uropathogenic Escherichia coli , this function is mediated by a repertoire of systems that scavenge iron from the host during infection . We found that vaccination with certain iron receptors from these systems is sufficient to elicit protective immunity from experimental urinary tract infection . Induction of an antibody response played a key role in protection from infection because antibody class-switching and the production of antibodies in urine correlated with reduced numbers of bacteria in the bladder . By targeting an entire class of molecules involved in iron acquisition instead of a single protein , it was possible to successfully identify components of a protective UTI vaccine . This strategy could be a useful approach in the development of vaccines to prevent infections caused by other pathogenic bacteria . | [
"Abstract",
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"Results",
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] | [
"infectious",
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] | 2009 | Mucosal Immunization with Iron Receptor Antigens Protects against Urinary Tract Infection |
There are a huge number of pathogens with multi-component transmission cycles , involving amplifier hosts , vectors or complex pathogen life cycles . These complex systems present challenges in terms of modeling and policy development . A lethal tick-borne infectious disease , the Brazilian Spotted Fever ( BSF ) , is a relevant example of that . The current increase of human cases of BSF has been associated with the presence and expansion of the capybara Hydrochoerus hydrochaeris , amplifier host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum . We introduce a stochastic dynamical model that captures the spatial distribution of capybaras and ticks to gain a better understanding of the spatial spread of the R . rickettsii and potentially predict future epidemic outcomes . We implemented a reaction-diffusion process in which individuals were divided into classes denoting their state with respect to the disease . The model considered bidirectional movements between base and destination locations limited by the carrying capacity of the environment . We performed systematic stochastic simulations and numerical analysis of the model and investigate the impact of potential interventions to mitigate the spatial spread of the disease . The mobility of capybaras and their attached ticks was significantly influenced by the birth rate of capybaras and therefore , disease propagation velocity was higher in places with higher carrying capacity . Some geographical barriers , generated for example by riparian reforesting , can impede the spatial spread of BSF . The results of this work will allow the formulation of public actions focused on the prevention of BSF human cases .
Stochastic epidemic models have been used to guide control policies for tick-borne infectious diseases [1–3] . These models typically assume that vector and host populations are homogeneous , disregarding the movement of infected individuals and the consequent spatial spread of infectious diseases [4] . Nonetheless , reaction-diffusion equations can be used to incorporate the spatial movement of individuals into stochastic epidemic models and predict the spatial advance of a disease [5–14] . In this approach , individuals are divided into a set of subgroups , each of which has its own stochastic dynamics described by a differential equation system , and adjacent subgroups are coupled by individual random movements with constant velocity [15 , 16] . A remarkable example of a spatial spread system dependent on amplifier hosts is the Brazilian Spotted Fever ( BSF ) , a highly lethal zoonotic disease caused by the bacteria Rickettsia rickettsii , transmitted by the tick Amblyomma sculptum Berlese , 1888 [17] , ( Amblyomma cajennense complex ) ( Ixodida: Ixodidae ) , and whose basic reproduction number ( R0 ≈ 1 . 7 ) was recently calculated through a next-generation matrix approach [18] . Specifically , in the transmission of this disease , the vector A . sculptum is unable to maintain the R . rickettsii transmission cycle by transovarial transmission so that amplification by a reservoir host is required [19] . In Brazil , the maintenance of R . rickettsii depends primarily on the constant introduction of susceptible capybaras Hydrochoerus hydrochaeris [20 , 21] , which act as amplifiers and guarantee the constant creation of new cohorts of infected ticks [19 , 22 , 23] . Additionally , since ticks are limited in their mobility , R . rickettsii can spread over geographical areas by the movement of infected capybaras carrying either infected ticks from endemic areas or by transmitting the disease directly to susceptible ticks in neighboring regions . Currently , in agricultural endemic BSF areas , population densities of capybaras have reached numbers up to 40 times higher than those recorded in natural environments such as the Amazon and Pantanal [24] and thus , the risk of human infection has increased significantly over the last three decades [22 , 25] . Notwithstanding the average abundance index of the groups of capybaras in southeastern Brazil has been reported in 50 . 55 individuals [26] . In southeastern Brazil , genetic analyses have confirmed a rapid spatial expansion of capybaras with evidence of secondary contacts between phylogroups [27] . In this region , the formation of capybaras subgroups and their migration occurs chiefly when they leave in search of food [27–29] . However , young capybaras can also migrate after the occurrence of agonistic behaviors [29 , 30] and at the beginning of the sexual maturity [31] . The maximum and mean dispersal distances of capybaras have been reported in 5600 m and 3366 m , respectively [32 , 33] . Moreover , it has been found that the home range of capybara groups differs in the different countries of South America . For instance , it covers from 6 to 16 ha in Venezuela [34] , 11 . 3 to 27 . 6 ha in Argentina [35] , 56 ha in Colombia [36] although up to 183 ha in Paraguay [37] or even from 196 ha [38] to 200 ha in Brazil [39] . The infection by R . rickettsii among different populations of capybaras and ticks in a homogeneous space was previously modeled [3] . In this preceding approach , two main risk factors for the R . rickettsii dissemination were identified: the current high birth rate of capybaras in endemic areas and the straightforward generation of new endemic areas due to the fact that a single infected capybara with just one infected tick attached is enough to trigger the disease in a non-endemic area . However , the risk of dissemination may be greater if it is considered: i ) the current increase of the carrying capacity , determined by the abundance of sugarcane crops , the main food source of capybaras in São Paulo [40] , ii ) the ubiquitous distribution of the vector A . sculptum in the state of São Paulo [17 , 41 , 42] and iii ) the large number of rivers in the region , through which capybaras can migrate [40] . This work aims to model a reaction-diffusion system that considers the spatial structure of capybaras to predict the spatial diffusion of the BSF in São Paulo and to assess potential preventive and control interventions . We calculate the BSF propagation and verify if the model describes the reported spatial-temporal spread of BSF . In addition , we create different scenarios to evaluate the effectiveness of preventing the capybaras’ exodus to control the spatial spread of the R . rickettsii and consequently prevent BSF human cases . This work contributes to the development of forthcoming mathematical and computational studies focused on the dynamics and prevention of vector-borne infectious diseases .
We developed a reaction-diffusion system for the spread of an infectious disease by considering the spatial structure and migration of amplifier hosts . Our results indicate that as we vary the amount of food , the velocity at which the disease advances is roughly proportional to the carrying capacity , hence proportional to the local risk of zoonotic infection . Since our reaction-diffusion model considered a reasonably realistic spatial structure of capybaras and ticks and allowed to represent accurately the spatial dynamics of the Brazilian Spotted Fever in the state of São Paulo , it can allow the formulation of public actions focused on the prevention of these diseases and potentially other vector-borne diseases . The results of the sensitivity analysis can be used to focus prevention strategies on the birth rate of capybaras , as this analysis identified that this parameter ( do to their estimation uncertainty ) is the most important in the prediction of infected migratory capybaras . Some geographical barriers , generated for example by riparian reforesting , can generate positive ecological impacts and can impede the spread of BSF to humans .
Fig 5 schematically summarizes the BSF transmission dynamics for each subgroup of capybaras and ticks . Individuals are represented by Xk , where X stands for the infectious state ( susceptible S , infected I , and recovered R ) , k = C for capybaras or k = T for ticks . Ticks were classified according to their life cycle stages as larvae ( L ) , nymphs ( Y ) and adults ( A ) . Thus , T = L± , Y± , A± , where − represents detached from a capybara or + attached to it . In this way , the total capybara population is given by NC = SC + IC + RC and the total tick population by NT = SL− + SL+ + SY− + SY+ + SA+ + SA− + IL− + IL+ + IY− + IY+ + IA+ + IA− . In order to consider the seasonal one-year generation pattern of the tick A . sculptum , the model was adjusted to a semi-discrete time dynamics [60] . We refer to a semi-discrete dynamics as the particular class of hybrid dynamical system that undergoes continuous dynamics in ordinary differential equations most of the time and experiences discrete dynamics at some time instants [61] . In our model , larvae exclusively quest and feed from April to July for 110 days , nymphs from July to October for 104 days and adults particularly quest , feed and reproduce from October to March for 151 days [3 , 60] . Thus , within each tick season the transmission dynamics is continuous and between the seasons it is discrete . Dynamic quantities of the R . rickettsii ransmission stochastic system are presented in Table 1 . Susceptible capybaras SC can be infected by an attached tick at a rate λ . All capybaras have the same susceptibility and there is no increased death rate δC of infected individuals due to disease . Once capybaras are infected , they keep the R . rickettsii in the bloodstream for 7 to 10 days [21] , during which the infection of new susceptible ticks that feed on it can occur at rate β . After this period , capybaras recovered at a rate γ and become immune to the disease . As capybaras natality depends primarily on the availability of food sources , as is typically the case of rodents [62] , in the proposed model the birth rate μC of the capybara population was determined by the amount of sugarcane in the region obeying the function: μ C = [ μ 0 + δ μ ( 1 - e - c ( r ) / c ¯ ) ] , ( 1 ) where μ0 is the reproduction rate in the absence of sugarcane and δμ is the increase in birthrate to its maximum if the sugarcane concentration c ( r ) at location r exceeds the spatial mean c ¯ . A birth rate close to zero was considered in areas without sugarcane , and a maximum birth rate , μC = 1/136 d−1 was considered in areas with a maximum amount of sugarcane , as described below . This value considers a maximum litter size of capybaras reported in 6 . 1 pups [63 , 64] . As it is also shown in Fig 5 , ticks can attach at a rate α , detach at a rate θT and die at a rate δT . The production rate ρ of NT is assumed to be proportional to the total number of susceptible and infected attached ticks of the previous generation . Infected adult ticks have a lower production rate ρI than susceptible adult ticks ρS , and the fraction of offspring by infected ticks is given by aS = 305/532 and aI = 228/532 . The definition of the rates involved in the non-spatial transmission dynamics is specified in Table 2 . This system of reactions can also be described by a coupled differential equation system , For ticks: S ˙ T - = ρ S S + + θ S T S T + - α S T - - δ T S T - , I ˙ T - = ρ I I + + θ I T I T + - α I T - + β j C θ S T S T + - δ T I T - , S ˙ T + = α S T - - β j C θ S T S T + - θ S T S T + - δ T S T + , I ˙ T + = α I T - - θ I T I T + - δ T I T + , ( 2 ) For capybaras: S ˙ C = μ C N C - λ s C I T + - δ C S C I ˙ C = λ s C I T + - γ I C - δ C I C , R ˙ C = γ I C - δ C R C , ( 3 ) which has been previously studied [3] not only for the stationary state but also on the effect of rates changes . The proposed reaction-diffusion system was implemented in the R language using the Gillespie algorithm [65 , 66] . All parameters were estimated using data generated from ex situ field works in southeastern Brazil . A full list of the model’s reactions and parameters used in the simulations is given in Table 1 . Groups of capybaras comprise a maximum of 50 individuals [24 , 26 , 67 , 68] in all simulations . | Complex systems as the Brazilian Spotted Fever ( BSF ) , present challenges in terms of modeling and policy development . BSF human cases have been associated with the presence and expansion of the capybara Hydrochoerus hydrochaeris , amplifier host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum . We developed a reaction-diffusion system for the spread of BSF by considering the spatial structure and migration of amplifier hosts to gain a better understanding of the spatial spread of the R . rickettsii and potentially predict future epidemic outcomes . We performed stochastic simulations and numerical analysis to investigate the impact of potential interventions to mitigate the spatial spread of the disease . Our results indicate that as we vary the amount of capybaras’ food sources , the velocity at which the disease advances is roughly proportional to the carrying capacity , hence proportional to the local risk of zoonotic infection . Some geographical barriers , generated for example by riparian reforesting , can generate positive ecological impacts and can impede the spread of BSF to humans . | [
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] | 2018 | Hosts mobility and spatial spread of Rickettsia rickettsii |
Monitoring Trypanosoma spread using real-time imaging in vivo provides a fast method to evaluate parasite distribution especially in immunoprivileged locations . Here , we generated monomorphic and pleomorphic recombinant Trypanosoma brucei expressing the Renilla luciferase . In vitro luciferase activity measurements confirmed the uptake of the coelenterazine substrate by live parasites and light emission . We further validated the use of Renilla luciferase-tagged trypanosomes for real-time bioluminescent in vivo analysis . Interestingly , a preferential testis tropism was observed with both the monomorphic and pleomorphic recombinants . This is of importance when considering trypanocidal drug development , since parasites might be protected from many drugs by the blood-testis barrier . This hypothesis was supported by our final study of the efficacy of treatment with trypanocidal drugs in T . brucei-infected mice . We showed that parasites located in the testis , as compared to those located in the abdominal cavity , were not readily cleared by the drugs .
Human and animal African trypanosomoses are important protozoan infections endemic in Africa , Latin America and Asia , caused by several species such as Trypanosoma brucei , T . evansi , T . equiperdum , T . congolense and T . vivax . Different species , strains within the species and clones within various strains show different tissue tropism that may further vary within hosts [1] . Currently no vaccines against human and animal trypanosomoses are available; and a limited range of drugs exist to treat these diseases . Moreover , most of the drugs used in second stage sleeping sickness show a high toxicity while in animal trypanosomosis drug resistance becomes more and more problematic [2] . Our current knowledge on tissue tropism , mechanisms by which trypanosomes invade and spread into tissues , the temporal course of invasion and the drug accessibility to trypanosomes in tissues , is incomplete . To complement classical anatomopathological examinations , real-time biophotonic imaging seems straight forward . Bioluminescence in vivo imaging allows longitudinal monitoring of an infection in the same animal , a desirable alternative to analyzing a number of animals at many time points during the course of the infection . To date , most bioluminescence models have been generated to monitor pathogenic bacterial infections , such as Salmonella , and bacterial meningitis [3] , [4] . Among pathogenic protozoa only Plasmodium berghei , Leishmania amazonensis and Toxoplasma gondii have been engineered to express the firefly luciferase and used in bioluminescence imaging [5]–[7] . To our knowledge , no bioluminescent model for trypanosomes has been developed . Here we report the generation of recombinant Renilla luciferase expressing parasites , and the validation of the use of a real time biophotonic detection of parasites to study the dissemination of African trypanosomes in mice in vivo and the efficiency of treatment with trypanocidal drugs in vitro and in vivo .
The Rluc gene was PCR-amplified from pGL4 . 70 ( Promega ) and cloned into the pHD309 plasmid [8] using the In-Fusion PCR cloning kit ( ClonTech ) . Plasmids were screened via HindIII/BamHI double restriction-digestion , sequenced , and those with the correct insert in frame were selected and propagated in E . coli . Ten µg of the Rluc-pHD309 plasmid was linearized using NotI ( 10 U , 3 hours at 37 C ) . T . brucei bloodstream forms ( Lister 427 host cell line 90-13 and AnTat 1 . 1E ) were cultured at 37°C , 5% CO2 in IMDM medium ( Gibco ) supplemented with 10% ( v/v ) heat-inactivated fetal calf serum , 36 mM sodium bicarbonate , 136 µg . ml−1 hypoxanthine , 39 µg . ml−1 thymidine , 110 µg . ml−1 NaPyruvate , 28 µg . ml−1 bathocuproine , 0 . 25 mM β-mercaptoethanol , 2 mM L-cystein and 62 . 5 µg . ml−1 kanamycin [9] . A pellet of 2×107 parasites was resuspended in 400 µl warm cytomix ( 2 mM EGTA , 120 mM KCL , 0 . 15 mM CaCl2 , 10 mM K2HPO4/KH2PO4 pH 7 . 6 , 25 mM Hepes , 0 . 5%Glucose , 1 mM Hypoxanthine , 100 µg/ml BSA , 5 mM MgCL2 ) [10] and transferred into a 4 mm cuvette; 10 µg of linearized DNA construct was added and left for one minute at 37°C . Subsequently the mixture was pulsed once in a Gene Pulse Xcell square wave electroporator at 1250 V , 25 Ohm , 50 µF and transfected cells were added to 12 ml of preheated IMDM , plated in a 24-well plate ( 24-time 500 µl ) and incubated at 37°C for 24 h . Next , 500 µl of preheated IMDM containing 10 µg/ml hygromycin were added to obtain a final selection concentration of 5 µg/ml . Positive clones were evident at 6 days post transfection . Transfected Trypanosoma brucei brucei AnTat 1 . 1E bloodstream form trypanosomes were grown for 3 days in mice . Ten microlitres of blood were spread over a microscope slide and fixed with acetone for 15 minutes . The fixed cells were incubated at room temperature with primary and secondary antibodies for 1 h and 30 min , respectively , and washed two times for 5 min with PBS after each of the incubations . The primary antibody , monoclonal mouse anti-Renilla luciferase ( Millipore ) , was diluted 1∶2 in PBS . The secondary antibody , fluorescein isothiocyanate ( FITC ) -conjugated goat anti-mouse ( Jackson ) , was diluted 1∶100 in a solution of 0 . 1 mg . ml−1 Evans Blue and 1 µg . ml−1 DAPI in PBS . Cells were analyzed on an Olympus BX-41 UV microscope , and images were captured by a Colorview II camera ( Soft Imaging Systems ) and Cell_D software ( Soft Imaging Systems ) was used for analysis . The Renilla Luciferase Assay System ( Promega ) was used to measure in vitro luciferase activity . Non-transformed T . brucei Lister 427 and T . brucei 427–Rluc-pHD309 clones were grown up to a total of 1×107 parasites ( 10 ml of 1×106 cells/ml ) , spun down at 1500 g for 10 minutes , resuspended in 20 µl IMDM medium and subsequently added to 100 µl of Renilla Luciferase Assay ( 1 µl of 100× Renilla Luciferase Assay substrate dissolved into 100 µl of Renilla Luciferase Assay Buffer ) . The level of Renilla luciferase activity ( RLU ) from 1×106 samples was monitored at different time points after substrate addition in a luminometer . To monitor the signal of lysed cells , the same amount of cells was lysed and measured in the same system according to manufacturers instructions . Mice were anaesthetized with 2 . 3% isoflurane . At different days after infection , mice were injected intraperitoneally with 100 µL of coelenterazine ( 2 µg/µl dissolved in methanol ) ( Synchem ) diluted with 90 µL PBS pH 7 , anaesthetized with isoflurane and light emission in photons/second/cm2/steradian ( p/sec/cm2/sr ) was recorded in an IVIS Imaging System 100 ( Xenogen LifeSciences ) and Living Image® 2 . 20 . 1 software ( Xenogen ) for 180 seconds . Measurements started 3–5 minutes after substrate injection to allow the spread of the coelenterazine . Mice at 25 days after infection were deeply anaesthetized with isoflurane , sacrificed and testes were dissected . To examine presence of trypanosomes within and outside blood vessels in the testis , sections were cut , mounted , fixed and immunostained with anti-AnTat 1 . 1 VSG ( 1∶5 . 000 ) and goat polyclonal anti-glucose transporter 1 ( 1∶40; GLUT-1 , Santa Cruz Biotechnology , Santa Cruz , CA , USA ) as described previously [11] . Glut 1 usually used to stain cerebral blood vessels has also been shown to be expressed by testicular endothelial cells [12] . Sections were examined and analysed using a Nikon fluorescence microscope . Photomicrographs were taken with a Zeiss AxioCam digital camera . WST-1 ( tetrazolium salt ) salts are cleaved to formazan by cellular oxidoreductases . The augmentation in enzyme activity lead to an increase in the amount of formazan dye formed . The viable cells were quantified by the formazan dye produced by metabolically active cells . To measure the drug sensitivity of cordycepin and other drugs , 25000 parasites were cultured in 100 µl in vitro in a 96 well culture plate with serial drug dilutions . Viability of the parasites was measured by adding 10 µl of WST reagent and further incubation for 2 hours . Readings were taken by a multiwell scanning spectrophotometer at excitation wavelength of 450 nm . In order to measure single cell proliferation trypanosomes at different days of culture CFSE labeling was performed as described for mammalian cells [13] . To each milliliter of cell suspension , 2 µl of carboxyfluorescein diacetate , succinimidyl ester or CFDA-SE ( CFSE ) 5 mM stock solution was added and immediately mixed to ensure uniform staining , resulting in a final concentration of 10 µM CFSE . The cells were incubated 15 min at 37 C and the cells were quenched by adding 5 volumes of culture medium . Cells were analysed by flow cytometry with logarithmic detection of green fluorescence . All mice were housed in filter-top cages and maintained in SPF barrier facilities in individual ventilated cages at the Karolinska Institute , Stockholm , or at the Institute for Tropical Medicine Antwerp . Animal ethics approval for the infection of live animals with recombinant trypanosomes was obtained from the respective Animal Ethical Committees of the Karolinska Institute ( Sweden ) and the Institute of Tropical Medicine , Antwerp ( Belgium ) .
For stable transfection of Renilla luciferase ( Rluc ) into the β-tubulin region of the bloodstream form of monomorphic T b . brucei Lister 427 and pleomorphic T . b . brucei AnTat 1 . 1 , the Rluc gene was PCR-amplified and cloned into the pHD309 plasmid [8] . Plasmids were screened via HindIII/BamHI double restriction-digestion , sequenced , and those with the correct insert in frame were selected and propagated in E . coli . For transfection , 2×107 parasites were electroporated with NotI linearized DNA construct in a BioRad Gene Pulse Xcell square wave electroporator . Two independent transfections were performed and three clones from each population were selected for further luminescence experiments The kinetics of luciferase activity of T . brucei Lister 427 and AnTat 1∶1 clones showed a fast reaction and prolonged response during time . Both live and lysed cells showed a high relative luciferase units ( RLU ) activity , although the RLU signals for lysed cells were about 5 to 10 times higher ( Figure 1A and data not shown ) . A linear relationship between concentration of live parasites and the RLU could be observed ( Figure 1B ) . The Renilla Luciferase Assay System ( Promega ) was used to measure in vitro luciferase activity of live and lysed parasites . Subsequently , we verified whether the RLU signal measured from live cells was due to substrate uptake and not residual activity of free luciferase released from damaged or live cells during manipulation . First , cells were spun down , the supernatants collected and the cell pellet resuspended and luciferase activity measured in supernatants and cell pellets . Over 70% of the original light emission was generated by the cell pellet whereas a negligible signal was detected in the supernatant ( data not shown ) . As a second control , FACS analysis performed on 106 non-lysed parasites incubated with propidium iodide , a marker for non-viable cells , showed no incorporation of the dye , indicating that over 99% of the cells were intact after manipulations ( data not shown ) . Taken together , these results suggest that the luciferase substrate coelenterazine penetrates or is taken up by live trypanosomes and that the detected luciferase is not secreted or released by the trypanosomes . Renilla luciferase was expected to locate in the cytoplasm . Indeed , luciferase was immunostained throughout the whole cell with a slightly higher concentration around the flagellum ( Figure 1C ) . We then investigated if coelenterazine is toxic for parasites since this could hamper the follow up of the infection in vivo . Parasites were grown in vitro in the presence of different concentrations of coelenterazine and parasite growth was measured during 72 hours . Coelerenterazine at concentrations required for in vivo usage did not inhibit parasite proliferation ( Figure 1D ) . T . brucei undergoes a life cycle stage differentiation from a long slender to a short stumpy form [14] ) . We analysed whether slender and stumpy forms of T . brucei express luciferase activity and cleave WST-1 . Parasites were alive in our culture condition until day 4–5 of culture . Exponential growth of parasites was observed during the first 48 h in cultures whereas at day 3–4 similar parasite concentrations were observed . Confirming previous data [14] , the lack of increase in parasite density in the cultures was due to an arrest in proliferation rather than to an increased parasite death , as visualized by the dilution of CFSE by parasites during the days 1 and 2 but not 3 and 4 of culture ( Figure 1 E ) . Long slender had lower WST-1 cleavage ability per cell than stumpy forms ( Figure 1 G ) , whereas stumpy forms showed negligible luciferase activity compared to long slender forms ( Figure 1 F ) . The outcome of infection with the monomorphic T . brucei Lister 427 in female mice was then studied . Mice infected i . p . with 10 , 100 or 1000 parasites were inoculated i . p . with 20 µg/kg coelenterazine 2–4 minutes before light measurement . All mice died 5 days after infection with 1000 T . b . brucei , while when inoculated with 10 or 100 parasites mice survived up to day 11 after infection ( Figure 2A ) . A fraction of mice survived that inoculation . With exception of one animal , none of the surviving animals showed detectable parasitemia . Light emission , usually located in the peritoneal cavity , was observed in all mice showing positive parasitemia ( Figure 2A ) . The inoculation of BALB/c male mice with 2 . 104 pleomorphic luciferase tagged T . b . brucei AnTat 1 . 1E resulted in a prolonged survival , similar to that observed after infection with the isogenic non-recombinant parasites ( data not shown ) . Mice showed signs of morbidity circa 3 weeks after infection but no increased light emission or parasitemia . The intensity of light emission was not always associated with parasitemia levels . Interestingly , a preferential localization of parasites in the testis was detected in several animals infected with T . b . brucei AnTat 1 . 1E ( Figure 2B ) , an observation that was reproduced when infecting male BALB/c mice with T . brucei Lister 427 ( data not shown ) . When performing bioluminescence experiments in female mice , no apparent sequestration to the sexual organs ( in casu the ovaries ) was observed ( data not shown ) . We studied if the pressure exerted by the adaptive immune responses determined preferential localization in the testis . For this purpose we infected B- and T cell-deficient RAG1−/− mice with 100 T . b . brucei Lister 427 recombinant parasites . RAG1−/− mice also showed testis localization of T . b . brucei after infection indicating that testis localization is probably due to parasite tropism for testis or enhanced parasite growth in this organ ( Figure 3A ) . The immunostaining of trypanosomes in the testis of mice 25 days after infection with T . b . brucei AnTat 1 . 1E confirmed the information provided by the bioluminescent technique . Trypanosomes were observed within and outside blood vessels , in the interstitial stroma between seminiferous tubules ( Figure 3B ) . In the experiments described above , biophotonic emission could be mainly detected in the abdominal cavity , and less frequently in the thorax and head of infected animals . Whether such localization was due to a preferential dissemination of the parasite in the abdomen and pelvis or to a non-homogenous distribution of coelenterazine in vivo was investigated . To analyze these possibilities mice infected with T . b . brucei AnTat 1 . 1E were sacrificed and light production measured in organs after incubation with the substrate ex-vivo . Light was detected in the brain , spleen , lung and testis and to a lesser extent in the liver of infected mice . No light emission was detected in uninfected control animals ( Figure 4A ) . Thus , a non-homogeneous distribution of coelenterazine after inoculation probably accounted for the light production pattern observed in vivo . Hence , we compared the light production after intraperitoneal ( ip ) and intravenous ( iv ) inoculation of coelenterazine into mice infected with T . b . brucei AnTat 1 . 1E . While an abdominal localization of light emission was detected in mice inoculated i . p . ( Figure 4B ) with coelenterazine , the iv inoculation of the substrate resulted in a thorax and cranial localization , suggesting an incomplete body distribution of the substrate by either route ( Figure 4C ) . Whether recombinant parasites could be used for testing the efficiency of trypanocidal compounds in vitro was then studied . Light detection and parasite viability at different time points after incubation with the trypanocidal adenosine analogue cordycepin showed similar kinetics ( Figure 5A , B ) . Parasites were also incubated with different concentrations of cordycepin and both , luciferase activity and parasite viability were equally diminished at similar concentrations of cordycepin ( Figure 5C ) . Subsequently , the luciferase-labeled parasites were used to validate the biophotonic method for testing of trypanocidal compounds in vivo . Treatment with 7 doses of cordycepin and the adenosine deaminase inhibitor deoxycoformycin cures experimental infections with T . b . brucei [15] . A sub-curative treatment with cordycepin and deoxycoformycin in RAG1−/− mice infected with luciferase tagged strains resulted in waning of biophotonic emission ( Figure 5D ) . Several days after treatment , light production and parasitemia were detectable . Some mice showed light production in testis suggesting that T . brucei are protected by the testis-blood barrier from suboptimal doses of trypanocidal drugs ( Figure 5D ) . In contrast , neither parasitemia or light emission were detected in luciferase-tagged T . b . brucei infected BALB/c mice treated daily for 7 days with cordycepin and deoxycoformycin starting 5 days after infection ( Figure 6 ) .
In this paper , we demonstrate for the first time the feasibility of detecting live trypanosomes through real-time in vivo and ex vivo luminescence imaging . We opted to use Renilla luciferase rather than firefly luciferase since previous studies in procyclic trypanosomes ( insect stage ) showed that the firefly luciferase accumulated in glycosomes [16] . This may impede the growth of bloodstream mammalian forms due to major changes in the energy metabolism and thereby hamper in vivo bioluminescence studies ( George Cross , personal communication ) . There may be two reasons why the Renilla luciferase worked so well in vivo ( i ) the substrate coelenterazine is less polar than d-luciferin , and might pass through the cell membranes more readily and ( ii ) the C-terminus of Renilla luciferase ( VLKNEQ ) does not appear to have a peroxisomal targeting sequence , whereas firefly has the classic GGKSKL . Hence , we showed that Renilla luciferase was located in the cytoplasm where the substrate accumulates and does not hamper energy metabolism in the glycosome . A dose of 20 µg coelenterazine was used as a substrate , as described previously for the monitoring of metastasis in mice using bioluminescence [17] . Of importance is the stage-dependent luciferase activity , being significantly lower in stumpy than in slender forms . The transition of slender into stumpy bloodstream forms includes cell cycle arrest and a decrease in protein synthesis , probably due to decrease polysome formation [18] that could account for lower luciferase activity in this life stage . On the contrary , the stumpy forms showed increased WST-1 reduction probably attributed to the increased levels of oxidoreductases in this form compared to long slender forms [19] . Analogous to other models [20] , live T . b . brucei produced light after addition of substrate and distinct temporal differences in light production were revealed following intravenous or intraperitoneal delivery . Bhaumik and Gambhir [21] stated in their discussion that biodistribution of coelenterazine and the potential toxicity of repetitively using coelenterazine in living mice should be further investigated . They hypothesized that is was likely that coelenterazine will be accessible to many tissues because of its diffusible nature . We found that repeated injection of coelenterazine did not show toxic effects on the mice . However , the distribution of coelenterazine in vivo seemed not homogenous and depended largely on the way of administering the substrate . This is in accordance with recent findings [22] which showed that intranasal administration of luciferin rather than intraperitoneal injection increased the sensitivity of detecting nasal and pulmonary airway infections by a 30-fold . Hence the route of substrate administration should be considered in the interpretation of the real time images . According to the tissues of interest , either intraperitoneal , intravenous , or a dual injection , should be considered . Another possibility would be to increase the dose of substrate to verify if the local tissue concentration of coelenterazine is sufficient to give a detectable signal . According to the toxicity assays ( Figure 1D ) it would be possible to increase the dose by a 10-fold . The lack of toxicity of coelenterazine for parasites and the host at the doses used in vivo , and the lack of light emission by killed recombinant parasites support the strength of luciferase-tagged parasites to study in vivo parasite dissemination as well as drug compound screening , both in vitro and in vivo . The Rluc-pHD309 plasmid integrates at the conserved β-tubulin of the Trypanosoma species , hence other T . brucei strains and taxa can easily be transfected with the Renilla luciferase marker resulting in new models to monitor drug sensitivity and the spread of parasites in a murine model . A very interesting finding was the abundance of parasites in the testis . T . b . brucei parasites could be observed extravascularly in testis but not in the seminiferous duct , suggesting sexual transmission is unlikely . Accordingly , we observed that no female immunodeficient mice became infected when mated with T . brucei- infected BALB/c mice . Of interest , the natural transmission of Trypanosoma equiperdum closely related to T . brucei , occurs during copulation [23] . The distribution of trypanosomes in the testicular tissue is in accordance with a previous study showing that trypanosomes were present in the intertubular tissues , but never crossed the basal lamina of seminiferous tubules [24] . In that study , necrosis of cells in the seminiferous tubule and a mononuclear infiltration in the interstitium was noted . It might be that in T . equiperdum infections in equines this may contribute to disease transmission . Biophotonic real time detection of parasite dissemination will be useful to study T . equiperdum models to examine tissue tropisms and transmission routes . We should note that the current model uses intraperitoneal injection which may somehow bias the observed dissemination of the parasites . In future models it may be interesting to perform subcutaneous infections which mimic tsetse delivery . The possibility that parasites have a preferential tropism for testes can also be of importance when considering drug development , since parasites might be protected from many drugs by the blood-testis barrier . In line with this , parasites were detected in testes upon reactivation of the infection in mice treated with sub-curative doses of cordycepin and deoxycoformycin . It could be further speculated that the proximity of parasites to Leydig cells located in the interstitial tissues might affect the endocrine balance , contributing both to the pathology of disease . In line with this idea , testosterone levels , testicular responsiveness to exogenous gonadotropin and number of testicular LH receptors were reduced in T . b . brucei infected rats indicating gonadal imbalance [25] . Decreased concentrations of testosterone were detected in patients with human African trypanosomiasis [26] . In accordance , we observed that no offspring was generated after mating 4 male mice 20 days after infection with T . brucei AnTat1 . 1E with 2 uninfected females each for 10 days . All females remained uninfected , suggesting male sterility and absence of sexual transmission of the parasites . The preference of parasites for the testes does not appear to be a result of immune pressure since it also occurred in RAG1−/− mice , lacking B and T cells . In conclusion , this bioluminescent model opens new avenues to examine the dissemination of parasites of different Trypanosoma species into different organs , and the in vivo monitoring of drug efficiency . | Human African trypanosomiasis or sleeping sickness , caused by two subspecies of Trypanosoma brucei , is endemic in Subsaharan Africa . There is no vaccine and the currently used drugs are toxic and can cause severe side effects and even death . At present , we do not know how and when parasites can leave the blood and penetrate into organs ( especially the brain ) . Such knowledge will be very helpful to develop and validate new drugs that can clear the parasite from both the blood and the tissues . In this study , we developed a novel technique allowing us to track the parasites in a live animal by the use of light signals . By following the luminescent parasites in the mouse we showed that , interestingly , the organisms migrate very early in infection to the testes . Here , they may be protected from the immune system and from drugs . Indeed when treating the mice with a sub-optimal dose of medicine , the parasites in this location were not cleared and subsequently could cause a reinvasion into the blood of the host . | [
"Abstract",
"Introduction",
"Materials",
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"genetics",
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] | 2009 | Bioluminescent Imaging of Trypanosoma brucei Shows Preferential Testis Dissemination Which May Hamper Drug Efficacy in Sleeping Sickness |
A gold standard of antiviral vaccination has been the safe and effective live-attenuated 17D-based yellow fever virus ( YFV ) vaccines . Among more than 500 million vaccinees , only a handful of cases have been reported in which vaccinees developed a virulent wild type YFV infection . This efficacy is presumed to be the result of both neutralizing antibodies and a robust T cell response . However , the particular immune components required for protection against YFV have never been evaluated . An understanding of the immune mechanisms that underlie 17D-based vaccine efficacy is critical to the development of next-generation vaccines against flaviviruses and other pathogens . Here we have addressed this question for the first time using a murine model of disease . Similar to humans , vaccination elicited long-term protection against challenge , characterized by high neutralizing antibody titers and a robust T cell response that formed long-lived memory . Both CD4+ and CD8+ T cells were polyfunctional and cytolytic . Adoptive transfer of immune sera or CD4+ T cells provided partial protection against YFV , but complete protection was achieved by transfer of both immune sera and CD4+ T cells . Thus , robust CD4+ T cell activity may be a critical contributor to protective immunity elicited by highly effective live attenuated vaccines .
Live-attenuated vaccines ( LAV ) generally provide the highest level of protection against infectious diseases . The most effective LAVs duplicate the pathogen-specific conditions of natural infection but have their replication curtailed by the innate and adaptive immune responses prior to the onset of clinical disease . A well-balanced combination of authentic antigen expression and control can induce a prolific adaptive immune response and the formation of long-lived memory . The development of LAVs is generally a results-driven empirical process controlling first for attenuation and subsequently for protection . Although the broad immunological response to these vaccines is often times examined exquisitely , the immunity that directly contributes to protection is more difficult to define . Exploring the protective immunity elicited by LAVs would require the use of human subjects , which is often not appropriate , or animal model systems which may not accurately represent immunity or disease . However , understanding the immune properties that are required for protection is crucial to the rational design of vaccines against pathogens for which empirical production of a LAV has failed or for which usage of a LAV is prevented by current vaccine standards . One of the most successful lines of LAVs uses the 17D-based vaccine strains of yellow fever virus ( YFV ) . Since its introduction in the 1930s [1] the 17D-based vaccines ( substrains 17D-204 and 17DD ) have proven themselves to be amongst the most successful and efficacious vaccines created [2] . Centuries prior to the introduction of the 17D line of YFV vaccines , yellow fever ( YF ) was one of the most feared and widespread epidemic diseases in Africa , Europe , and the Americas . More than 500 million people have been vaccinated with the 17D-based vaccines and only 12 known cases of vaccine failure have resulted in YF [3] . The 17D line of vaccines also has an excellent safety record resulting in extremely rare severe adverse events [4] . Immunization with the 17D line of vaccines remains a mainstay in the YF endemic zones of Central/South America and Sub-Saharan Africa where sylvatic YFV reservoirs still seed endemic disease and outbreaks , offering the only protection to over 900 million people world-wide [5] . The strong and enduring response from a single vaccination has led to the recommendation that only a single dose is required for life-long immunity [6 , 7] . As such , the human response to immunization with the 17D line of vaccines has been used to identify gene signatures that correlate with desirable vaccine traits like immunogenicity [8] , with the prospect of improving the designs of other vaccines . Neutralizing antibodies elicited by the 17D-based vaccines have long been considered a correlate of protection against YFV . Titers are detected in humans as early as six days post vaccination and have been recovered after forty years [9 , 10] . Antisera protects non-human primates ( NHPs; [11] ) and intracranially ( i . c . ) inoculated mice [11 , 12] against challenge . Neutralizing antibodies rise to maximum levels around 2 weeks post-vaccination [13] . There is robust activation of CD4+ and CD8+ T cell responses that appear to transition into stable , polyfunctional memory [14–17] . Virus-specific CD4+ ( conventional and T regulatory ) and CD8+ T cells peak between 10 [17] and 11–30 [16 , 18 , 19] days post-vaccination , respectively . The magnitude of the CD8+ T cell response is influenced by viral load , peaking shortly after virus in the blood falls below detectable levels [19] . CD8+ T cells degranulate and produce IFNγ , IL-2 , and TNFα [16 , 17] . CD4+ T cells predominantly produce IFNγ and express CXCR3 , indicating a largely TH1 polarization [20] . Circumstantially , T cells appear to be capable of killing virus-infected cells [17] . Although it is widely speculated that YFV-specific T cells contribute to the superior efficacy of the 17D line of vaccines [21] , this remains unproven as such questions cannot be addressed in human subjects . Progress toward understanding , optimizing and exploiting 17D-based virus-elicited immunity has been hindered by the lack of a tractable small animal that accurately models severe YF disease and 17D-based vaccination . Few studies of naturally acquired wild type infections have examined immunologic parameters [22–24] , and experimentally controlled studies in humans are virtually impossible . Therefore , human studies of the 17D line of vaccines have been limited to the evaluation of blood circulating factors [14–18 , 20 , 25 , 26] . NHP models have proven advantageous for studies modeling human disease and protection [11 , 27 , 28] , but the cost of these studies is prohibitive . The resources and flexibility for immunologic studies in inbred rodent models are superior to NHPs . Unfortunately , normal and acquired immune-deficient rodents are refractory to infection and disease with both the 17D-based viruses and wild type YFV ( wtYFV ) , with the exception of i . c . infection where both viruses are equally virulent [29 , 30] . Previously , we determined that subcutaneous ( s . c . ) infections with wtYFV were strongly restricted by the type I IFN response in mice [30] , whereas in severe human or NHP infections , the virus appears relatively unhindered by the type I IFN system . Although the 17D-based viruses can elicit an immune response in immunocompetent mice [31 , 32] , they are also restricted by type I IFNs making studies of immune development in these animals less relevant to humans where they actively replicate and spread from the site of inoculation . In mice lacking the receptor to type I interferon ( IFNAR-/- ) , the 17D-204 vaccine strain replicates and disseminates from the site of s . c . inoculation , which functionally mimics human vaccination . 17D-204 is cleared in all mice following only minor clinical signs of infection . In contrast to 17D-204 , infection with the wild type Asibi virus reproduces remarkably human-like disease [30] , accompanied by a substantial cytokine response with high levels of IL-6 and MCP-I . This coincides with the viscerotropic dissemination of virus and severe liver and splenic pathologies similar to those found in post-mortem studies of YF patients [22–24 , 33] . Furthermore , wtYFV is uniformly lethal in these mice , reproducibly modeling the most severe aspects of YF disease . Here , we demonstrate that vaccine substrain 17D-204 vaccinated C57BL/6 IFNAR-/- ( AB6 ) mice are completely protected against an otherwise lethal infection with wtYFV from 3 weeks to at least 1 year post-vaccination . Using this model , we have evaluated the formation of adaptive immunity to the 17D-204 virus in a context that closely resembles human vaccination , in that it is a self-limiting attenuated infection . Similar to human studies , 17D-204 infection of AB6 mice resulted in the induction of neutralizing antibodies and a large polyfunctional 17D-204-specific CD4+ and CD8+ T cell response . Passive and/or adoptive transfer of immunity into naïve mice implicated both humoral and cellular immunity for conferring protection against infection with wtYFV . 17D-204-specific CD4+ T cells conferred partial protection against challenge with wtYFV whereas complete protection was achieved only when anti-sera and CD4+ T cells were provided together . Virus-specific CD8+ T cells produced cytokines and were cytolytic but surprisingly offered no protective effect upon challenge . Our data provide evidence , for the first time , that some T cell subsets elicited by 17D-based vaccination can play a role in protection against wtYFV infection and disease , suggesting that T cells may contribute to the unparalleled efficacy of the 17D line of vaccines .
We hypothesized that immunity generated against 17D-204 in AB6 mice would be protective against infection with the virulent Ang71 strain of YFV . To test this , naive 5–6 week old AB6 mice were vaccinated s . c . with 1x104 PFU of 17D-204 or virus diluent ( mock ) in both rear footpads . Mice were then challenged 21 days following vaccination by s . c . injections in both rear footpads with 2x104 PFU of Ang71 ( Fig 2B ) . The challenge with Ang71 in mice having received a mock vaccination resulted in disease and required 100% of animals to be euthanized by 9d p . i . In contrast , vaccination of mice with 17D-204 immunized them against challenge with Ang71 as evidenced by continued weight gain and the absence of clinical signs of disease . All 17D-204 immunized animals survived challenge ( Fig 2B ) with no clinical signs of disease for up to three months prior to being euthanized . Furthermore , AB6 mice having received a single 17D-204 immunization at five to six weeks of age were completely protected against clinical signs of infection when challenged one year later ( Fig 2C ) . Thus , immunization with the live-attenuated 17D-204 YFV vaccine strain resulted in long-term protective immunity against challenge with a highly virulent , genetically divergent isolate of wtYFV . We previously reported that YFV infection of mice resulted in rapid and transient induction of high levels of the proinflammatory cytokines IL-6 and MCP-1 in serum [30] , consistent with human studies of YF [22] , YF vaccine-associated viscerotropic disease [37] and NHP infection with the wild type Asibi virus [IL-6 only , [38]] . We screened 18 additional serum cytokines in addition to IL-6 and MCP-1 ( Fig 3 ) in mice following Ang71 infection and found that numerous cytokines with adaptive immunomodulatory roles were elevated including: proinflammatory and effector cytokines IFNγ and TNFα [39 , 40] , IL-12—a proinflammatory T cell and IFNγ stimulating protein [41] , IL-2 –a T cell growth factor [42] , and the B-cell differentiation and growth factor IL-5[43] . All reached peak levels around 4d p . i . , declining by d5 . IL-12p70 levels were high on d2 through d4 p . i . before declining by d5 . The immune cell chemoattractant proteins IP-10 and MIG peaked on d4 p . i . and remained at similarly high levels through 5 d p . i . Several additional cytokines were found to be largely non-responsive to Ang71 infection in non-immunized animals ( S1 Fig ) . The peak of the cytokine storm coincided with the peak of viral titers in most tissues ( Fig 4A and 4B ) , the onset of weight loss ( Fig 2B ) and the rapid progression of disease , suggesting that a broad cytokine response may be a biomarker for and a contributing factor to disease . Importantly , cytokine levels were not elevated in 17D-204-immunized animals , remaining similar to those recorded for mock-infected mice at d4 post challenge ( Fig 3 ) . The lack of disease observed in 17D-204-immunized mice when challenged with a lethal dose of Ang71 suggested the induction of a rapid and long-lived adaptive immune response that was efficient at controlling infection and/or dissemination of Ang71 . To determine the degree to which replication and dissemination of Ang71 was restricted in 17D-204 immunized mice , we infected mice with Ang71 and harvested tissues at 2 , 4 and 5 d post-challenge . In mock-vaccinated mice , infectious Ang71 was detected in the popliteal lymph node draining the inoculation site ( DLN ) , serum and spleen within 2d ( Fig 4A ) . DLN titers reached a sustained 2-5x103 PFU/LN . Serum viremia peaked on d2 p . i . at ~2 x 103 PFU/ml and fell below the LD in all but one animal on d4 and then in all animals by d5 . Virus was detected in the liver in all but one mouse by 2d p . i . and in all mice by d4 and d5 p . i . Two mice had detectable virus in the kidney at 2d p . i . and all mice had virus in the kidney on d4 and d5 p . i . By d4 and d5 p . i . the heart and brain in all mice had detectable virus ( Fig 4B ) . Generally , viral titers declined in the visceral tissues between d4 and d5 . In the brain , the titer rose by approximately 20-fold . Despite rising levels of virus in the brain , as previously reported [30] , the mice did not present signs of neurologic disease . No tissues harvested from mice immunized with 17D-204 and then challenged with Ang71 contained any detectable infectious virus above the limit of detection ( Fig 4C and 4D ) . For greater sensitivity , we compared viral GE by RT-qPCR in mock-vaccinated mice ( Fig 4E and 4F ) versus 17D-204-immunized mice ( Fig 4G and 4H ) after Ang71 challenge . RNA genomes for Ang71 were readily detected in unvaccinated AB6 mice . GE in the DLN and serum peaked on d4 p . i . and by d5 p . i . had decreased ( Fig 4E ) . GE in the spleen increased through d4 p . i . and remained at similar levels through d5 p . i . GE in the liver , kidney , and heart remained similar from d4 to d5 , whereas an increase in GE was observed in the brain from d4 to d5 ( Fig 4F ) . In 17D-204-immunized mice , however , Ang71 RNA was consistently detected only in the DLN ( Fig 4G ) but at more than 100-fold lower levels compared to mock-vaccinated mice ( Fig 4E ) at d2 p . i . and approximately 6 x104-fold lower by 4d p . i . In a subset of mice , the spleen [33%] , liver [17%] , kidney [17%] and brain [33%] showed low GE levels peaking at d3 p . i . and falling below the LOQ at 4d p . i . One mouse had low levels of detectable GE in the heart at 4d p . i . ( Fig 4H ) . The variation in GE to PFU ratio observed across tissues and time points likely reflects the cellular dynamics and formation of adaptive immune responses , primarily neutralizing antibodies , against Ang71 that obscure the detection of PFU but not GE . Sera collected from 17D-204-immunized mice were evaluated for 17D-204 neutralizing antibodies by plaque reduction neutralization test ( PRNT; Fig 5A ) . Consistent with the high seroconversion rate in human vaccinees of between 90% and 100% [44 , 45] , all mice tested between 19 days post immunization and 1 . 5 years post immunization demonstrated PRNT80 neutralizing antibody titers against both 17D-204 and Ang71 ( Fig 5A ) . We found that serum neutralizing titers were reduced by approximately nine-fold on average against Ang71 when compared with 17D-204 virus . The reduced titers were most likely explained by the amino acid divergence displayed between 17D-204 and Ang71 , as discussed above . To test whether 17D-204 antisera would protect against challenge , sera and magnetically enriched CD19+ B-cells - those responsible for antibody production - ( S2 Fig ) were harvested from 17D-204 immunized mice on d21 after immunization and transferred into naive AB6 mice 24 hours before challenge with Ang71 . To serve as positive and negative controls for protection , total splenocytes and sera from 17D-204-immunized or mock-vaccinated AB6 mice were transferred into naïve AB6 mice . Similar to the disease described in Fig 2 , all mice [6/6] receiving total splenocytes and sera from mock vaccinated animals experienced weight loss ( Fig 5B and 5C ) and had to be euthanized ( Fig 5D and Table 1 ) . On average , animals receiving total splenocytes and sera from 17D-204-immunized mice experienced mild disease indicated by significantly reduced weight loss following challenge ( Fig 5B and 5C ) and 100 percent survival [5/5] ( Fig 5D and Table 1 ) . On average , mice receiving only serum from 17D-204 immunized animals also experienced mild disease as illustrated by significantly reduced weight loss compared to animals receiving mock-vaccinated splenocytes and serum ( Fig 5B and 5C ) . Additionally , seventy-five percent [6/8] of mice receiving only serum survived challenge with Ang71 , a significant increase compared to mice receiving mock splenocytes and serum ( Fig 5D and Table 1 ) . Mice receiving CD19+ cells from 17D-204 immunized mice experienced weight loss similar to mice receiving mock splenocytes and sera ( Fig 5B and 5C ) . However , 37 . 5% [3/8] of mice receiving CD19+ cells from 17D-204 immunized mice survived challenge with Ang71 , a significant increase compared to mice receiving mock serum and splenocytes ( Fig 5D and Table 1 ) . These data suggest that convalescent serum may be more effective than CD19+ cells at preventing severe disease . However , both serum and CD19+ B-cell recall responses can lead to survival of mice following challenge with Ang71 . Acute viral infections , including the 17D-based vaccines , result in the proliferation of virus-specific CD4+ and CD8+ T cells responding to diverse epitopes . Once T cells become activated , they upregulate CD44 and downregulate CD62L ( CD44hiCD62Llo ) and represent circulating T cells . Although CD44 and CD62L comprise a conventional means of assessing T cell activation , CD11a is also upregulated on activated T cells in mice [46 , 47] and in humans [16] . Enhanced expression of CD11a on the surface of responding T cells is indicative of T cells responding to antigen-specific stimulus resulting from TCR cross-linking rather than bystander activation that can result from exposure to an inflammatory environment [46] . CD11a upregulation may constitute a more accurate means to assess total virus-specific T cell responses in systems where all possible T cell epitopes have not been defined [46] . Additionally , CD11a expression increases on YFV-specific CD8+ T cells in humans [16] and has been used to measure the broad T cell response to bacterial infection [46] , malaria [48 , 49] , and viruses [46 , 47] in mice . CD11a expression remains high for the life of a T cell following activation . To evaluate T cell immunity to 17D-204 , we harvested popliteal DLNs and spleens from 5–6 week old immunized mice at d7 p . i . At this time , 17D-204 was not detectable in the lymphoid organs by plaque assay following the peak of replication on d4 p . i . ( Fig 1 ) . CD4+ ( Fig 6A and 6B ) and CD8+ ( Fig 6F and 6G ) T cells in 17D-204-immunized mice demonstrated an expansion of the CD44hiCD62Llo subset commensurate with activation and proliferation . In addition , we evaluated T cells responding to 17D-204 by measuring CD11a upregulation . S3 Fig demonstrates the gating strategy for CD11ahi cells and that the majority of CD11ahi cells are CD44hiCD62Llo . Comparison of CD11a expression ( Fig 6C , 6D , 6H and 6I ) also demonstrated a significant increase in the percent of total CD4+ and CD8+ T cells over mock in the DLN and spleen . The increase in the percentage of activated cells corresponded to an increase in total numbers of CD11ahi CD4+ and CD8+ cells indicating a true expansion of activated T cells responding to immunization with 17D-204 ( Fig 6E and 6J ) . Following an acute T cell response to virus infection , T cells contract into memory , which can persist for the life of the animal . Memory cells can be broadly characterized as central ( TCM , CD62Lhi ) and effector ( TEM , CD62Llo ) memory [50] . TCM are characteristically found in the lymphoid compartments and are associated with the long-lived rapid recall responses that are most associated with adaptive immune memory [51–53] . TEM are relatively short-lived cells that remain in circulation and retain effector functions similar to those seen in the acute response [51–53] . Compared to CD4+ T cells , differentiation of CD8+ effector T cell subsets have been more thoroughly defined by monitoring the expression of the inhibitory C-type lectin , KLRG1 and the IL-7 receptor-α , CD127 [54 , 55] . Four subgroups of effector cells have been described that predict the formation of memory ( Fig 7D ) : early effector cells ( KLRG1loCD127lo , EEC ) which probably represent an early state of transition into the other subtypes; short lived effector cells ( KLRG1hiCD127lo , SLEC ) which have a limited duration; memory precursor effector cells ( KLRGloCD127hi , MPEC ) which give rise to long-lived memory and may be analogous to TCM; and double positive effector cells ( KLRG1hiCD127hi , DPEC ) which may be similar to TEM . On d7 after 17D-204 immunization ( acute T cell response ) CD4+ T cells were predominantly CD44hiCD62Llo ( Fig 7A ) . Following contraction , at d27 after immunization , TCM-CD44hiCD62Lhi cells predominated in the DLN and the spleen ( Fig 7B ) . As a proportion of total CD4+ T cells , TCM-CD44hiCD62Lhi cells were enriched from d7 to d27 post immunization . In contrast , the percent of total CD4+ T cells that were TEM-CD44hiCD62Llo was decreased ( Fig 7C ) . The acute CD8+ T cell response on d7 post immunization was predominated by EEC followed by SLEC ( Fig 7D and 7E ) . A population of MPEC was present at d7 following immunization , suggesting that a subset of T cells was beginning to transition to long-lived memory . By d27 post immunization ( Fig 7F ) , contraction of all cell types had taken place as indicated by the decrease in total numbers of all cell populations . The contraction corresponded to a decrease in the proportion of total CD8+ T cells of the SLEC and DPEC phenotypes in the DLN ( Fig 7G ) . The EEC phenotype was enriched in the DLN on d27 post immunization , whereas the proportion of the MPEC phenotype remained unchanged . In contrast to the DLN , the contraction observed on d27 post immunization in the spleen corresponded to decreases in the proportions of SLEC and EEC . An increase in the proportions of the DPEC and MPEC phenotypes were observed in the spleen . The enrichment of MPEC cells in the spleen but not the DLN suggests that the formation of long-lived CD8+ T cell memory to 17D-204 may be dependent on the environments of specific lymphoid organs . To verify that 17D-204 elicited a specific T cell response and to determine whether those cells were functional , we evaluated DLN and spleen cells from 17D-204-immunized mice by intracellular cytokine staining ( ICS ) . Cells were stimulated with the YFV MHC-II ( YFII-E; I-Ab ) and two MHC-I ( YFI-NS3; H2-Kb and YFI-E; H2-Db ) restricted determinants [31] . Stimulation with the YFII-E peptide resulted in CD4+ T cells producing IFNγ ( Fig 8A ) . Since polyfunctional 17D-based vaccine-specific T cells have been observed in humans , we evaluated the CD4+ T cells' ability to produce multiple cytokines ( IFNγ , IL-2 and IL-4 ) and grouped them by how many cytokines they produced ( single , double , triple ) . The majority of CD4+ T cells at d7 and d27 post immunization produced only one cytokine , dominated by IFNγ ( Fig 8B ) . The remaining cells produced IFNγ and IL-2 with no IL-4 detected above background levels . Stimulation of T cells with YFI-E or YFI-NS3 resulted in the majority of CD8+ T cell responders producing both IFNγ and CD107a ( LAMP-1 ) ( Fig 8C ) . CD107a is deposited at the cell surface during T cell degranulation and is linked with a T cell's ability to lyse targets [56] , suggesting that CD8+T cells were largely functional and capable of killing target cells . When we assessed CD8+ T cells , we found that nearly all cells responding with cytokines also produced CD107a . We gated on CD107a+ cells and grouped them according to their ability to produce combinations ( none , single , double , triple ) of IFNγ , TNFα or IL-2 in response to peptide stimulation ( Fig 8D ) . On d7 post immunization , CD8+ T cells responding to both YFV peptides demonstrated polyfunctional behavior with double and triple positive cells most predominant in the DLN while the spleen was comprised of mostly single and double cytokine producers . At d27 post immunization , cells from both tissues produced fewer cytokines . This effect was most dramatic from CD8+ T cells in the DLN and specifically those cells responding to the subdominant YFI-E epitope . The trend that T cell polyfunctionality becomes less diverse over time is consistent with the literature studying human vaccination with the 17D line of vaccines [17] . We tested whether 17D-204-specific T cells were cytolytic by examining in-vivo cytotoxicity against 17D-204 determinants . Mice were immunized with 17D-204 on d7 , d27 or 1 . 5 years prior to intravenous transfer of fluorescently labeled naive splenocytes loaded with control peptides from ovalbumin ( OVA-I; H2-Kb ) , SV40 large T-antigen ( SV40 TAg; SV40T-I; H2-Db ) , hepatitis B core ( HBV-Core; I-Ab ) or YFV peptides YFI-NS3 , YFI-E or YFII-E . Sixteen hours after transfer , spleens or popliteal draining lymph nodes were harvested and analyzed by flow cytometry to determine specific cytolytic activity ( Fig 9A ) . As a positive control for specific cytotoxicity , mice were immunized with SV40 virus-transformed cells and cytolytic activity was confirmed against the SV40T-I determinant of SV40 TAg [57] ( Fig 9A and 9B ) . During both the acute response ( d7 post immunization ) and the early memory response ( d27 post immunization ) , strong cytolytic activity was detected against all CD8+ T cell determinants with a significant decrease in activity between d7 and d27 post immunization ( Fig 9B ) . Although weaker than CD8+ T cell activity , cytotoxicity was detected against the CD4+ T cell determinant YFII-E during the same time frame . The activity was relatively strong in the DLN on d7 , showing a significantly higher signal than in the spleen . By d27 post immunization , the signal had increased in the spleen ( Fig 9B ) . Cytolytic activity was detected as early as d3 p . i . in the DLN for all determinants . In both the DLN and spleen , cytolytic activity was detected out to one and a half years following immunization ( Fig 9C and 9D ) . Activity against the YFI-NS3 and the YFII-E peptides showed no drop from peak levels during this time whereas activity against the subdominant YFI-E peptide decreased over time in both organs . To determine whether T cells could contribute to protection against challenge with Ang71 , we isolated serum and magnetically enriched CD4+ , CD8+ or CD19+ cells ( S2 Fig ) on d21 post immunization and adoptively transferred combinations of the enriched populations into naïve AB6 mice . Mice were challenged with Ang71 and monitored for weight loss ( Fig 10A , 10B and 10D and Table 1 ) and survival ( Fig 10C and 10E and Table 1 ) . Compared to mice receiving splenocytes and serum from mock vaccinated animals , mice receiving CD4+ T cells alone or in combination with CD8+ T cells experienced similar disease as indicated by weight loss . However , survival of both groups ( CD4 , [5/8]; CD4 , CD8 , [4/8] ) was increased compared to mice receiving splenocytes and serum from mock animals . Surprisingly , mice receiving only CD8+ T cells from 17D-204 immunized mice experienced similar disease and mortality as indicated by weight loss ( Fig 10A and 10B ) and survival [0/8] ( Fig 10C and Table 1 ) as animals receiving mock splenocytes and serum . Interestingly , the subset of animals that had to be euthanized after receiving CD4+ T cells from 17D-204 immunized mice experienced a significantly reduced AST , by approximately one day , compared to mice receiving mock vaccinated total splenocytes and serum ( Table 1 ) . Although overall the severity of clinical disease in this subset of mice was similar when comparing weight loss ( Fig 10A and 10B ) to what was observed in mice receiving mock-vaccinated splenocytes , the onset was earlier . This observation suggests that under as yet undefined conditions , CD4+ T cells may contribute to immunopathology following challenge with a wtYFV . Overall , these results suggest that in AB6 mice , 17D-204-elicited CD4+ T cells can impart protection against challenge with a wtYFV whereas CD8+ T cells are not protective . Since neither 17D-204 sera ( Fig 5B–5D ) nor T cells ( Fig 10A–10C ) alone were capable of completely protecting mice against Ang71 ( Table 1 ) , we adoptively transferred combinations of T cells , B cells and sera into naïve mice prior to challenge . When serum from 17D-204-immunized mice was transferred in addition to both CD8+ and CD4+ T cells , 100% of mice were protected against challenge with Ang71 compared to mice receiving total splenocytes and serum from mock vaccinated animals . These groups ( CD8 , CD4 , Serum and CD4 , CD8 , CD19 , Serum ) displayed reduced weight loss ( Fig 10A and 10D ) and increased survival ( [8/8] and [7/7] ) compared to animals receiving splenocytes and serum from mock vaccinated mice . Since CD8+ T cells did not contribute to protection ( Fig 10A–10C ) , these data suggest that CD4+T cells and sera from 17D-204 immunized mice can act together to confer protection against challenge with a wtYFV .
The success of the live-attenuated 17D line of YFV vaccines stems from the induction of long-lived , probably life-long , immunity against wtYFV . Due to the wide use of the 17D-based vaccines , volunteer vaccinees have in recent years contributed immensely to our understanding of vaccine-induced immunity in humans . These studies have shown that a single vaccination results in long-lived neutralizing antibodies [9 , 10] as well as long-lived [14 , 15] functional memory [16 , 17] following a robust CD4+ and CD8+ T cell response . Additionally , the use of systems biology approaches to track genomic signatures following immunization paints a picture that more thoroughly decodes the superior immunogenicity of the 17D line of vaccines and may lay groundwork for predicting the efficacy of other vaccines [8] . Despite these advances , studies linking humoral and T cell responses to protection against wtYFV have been lacking due to the absence of a cost-effective model that accurately recapitulates both vaccination and disease . In this study , we used an AB6 murine model to evaluate the immunity induced by 17D-204 immunization and its corresponding protection against challenge with a virulent wtYFV . Our results suggest that both neutralizing antibodies and CD4+ T cells elicited by 17D-204 can be protective against challenge with a virulent wtYFV . Infection of AB6 mice with wtYFV elicits a broad elevation in the cytokine profile reminiscent of natural wtYFV infection in humans or rare vaccine-associated viscerotropic disease ( YFV-AVD ) [22 , 37 , 58] . Elevation of MCP-1 , IL-6 ( [30] and this study ) , TNF-a and IP-10 in the AB6 model is consistent with studied cases of patients that develop a fatal case of YF [22] or YFV-AVD [37 , 58] . The role of these and other elevated cytokines following wtYFV infection and YFV-AVD is unknown . However , pathological cytokine responses including IFNγ , IL-6 , IL-10 , TNFα , and IP-10 [59] , all of which are elevated in AB6 mice during fatal Ang71 infection , have been implicated in inducing vascular permeability with the onset of hemorrhagic fever after infection with the related Dengue virus ( DENV ) . Incidentally , serum cytokine concentrations become elevated on d4 p . i . ( [30] and this study ) , marking the onset of clinical disease in AB6 mice . 17D-204-immunized AB6 mice show no signs of cytokine elevation following challenge with Ang71 possibly due to limited viral replication , which is mostly restricted to the DLN . We suggest that the cytokine response associated with high viral replication in unimmunized mice may contribute to disease . Future studies are warranted to assess whether suppressing these responses after Ang71 challenge of unvaccinated mice could prevent the onset of disease and perhaps lead to treatments for human YF . The adaptive immunity induced by the 17D line of vaccines in humans has been partially characterized in recent years [14–18 , 26 , 60] . However , little has been studied concerning the specific components of this response that are required for protection against wtYFV . Antibodies are a correlate of protection against wtYFV and are considered by the WHO as the primary measure of vaccine efficacy [61] . The importance of antibodies for protection against wtYFV is supported by reports that lower levels of YFV-specific antibodies correlate with severe and fatal cases of YF in contrast to mild non-fatal cases [22] . Additionally , lethal infection in rhesus monkeys produces necrotic B cell germinal centers [28] . Our serum transfer results support the importance of antiserum for protection against wtYFV and suggest that it may be required for protection from disease . However , our results indicate that even in fully 17D-204-immune mice , Ang71 was not immediately sterilized upon challenge since virus was detected in the DLNs of all mice . It remains unknown whether 17D-based vaccines produce sterilizing immunity in humans against challenge with a wtYFV . Many experimental studies that have assessed the importance of antisera for protection have challenged with the Asibi virus , the parent virus to the 17D vaccine line . Our use of the divergent Ang71 virus , which is less efficiently neutralized in 17D-204-immunized mice , may explain why antiserum is not entirely protective against challenge . Long-term studies are needed to determine whether neutralizing antibodies alone are sufficient to clear virus or whether neutralizing antibodies simply limit the spread of virus while T cells or other immune cells eliminate virus reservoirs . Our findings support a critical role for neutralizing antibodies for protection against wtYFV . As in humans , 17D-204 immunization of AB6 mice results in a robust expansion of polyfunctional CD8+ T cells that form functional memory . Our analysis shows that 17D-204-specific T cells produce IFNγ and a subset also produce combinations of TNFα and IL-2 . Additionally , CD8+ T cells express surface CD107a following specific stimulation and efficiently lyse target cells in-vivo at early and late ( memory ) time points following vaccination . These observations led us to hypothesize that in this model the cytolytic capacity of CD8+ T cells would be important for controlling Ang71 in adoptive transfer experiments . A similar mechanism of control is seen in a related mouse model following vaccination against DENV [62] and West Nile virus ( WNV ) [63 , 64] . Instead , CD8+ T cells played no detectable role in protection against Ang71 , as determined by the severity of disease or AST . Additionally , the fact that clinical disease and AST were not exacerbated also suggests that CD8+ T cells were not contributing to disease through immunopathologic mechanisms . The importance of CD8+ T cells for vaccine-related protection or challenge immunopathology in humans has never been tested . We found that 17D-204-specific CD4+ T cells were functional during the early and late time points post immunization . 17D-204-specific CD4+ T cells displayed a strong TH1 polarization during the acute response , and similar cytokine profiles were maintained following the formation of memory . In-vivo cytolysis of targets displaying 17D-204 derived MHC-II restricted peptides was detected with similar efficiencies during both the acute and long-term memory response . Importantly , adoptively transferred CD4+ T cells contributed to survival following Ang71 challenge , resulting in the recovery of a majority of infected mice . These results suggest that CD4+ T cells may functionally contribute to the superior efficacy of the 17D line of vaccines and as such constitute a critical component for effective vaccination against wtYFV . The mechanism by which CD4+ T cells exert their effect remains unknown . However , the MHC-II restricted in-vivo cytotoxicity suggests that direct cytolysis by YFV-specific CD4+ T cells may be an important mechanism . Perforin and Fas/FasL mediated mechanisms , as measured by in-vivo cytotoxicity are involved in the control of WNV [65] . The same mechanisms that contribute to the protective efficacy of CD4+ T cells may also be involved in the CD4-mediated immunopathology that we observed in a subset of mice . Bystander cytotoxicity was observed from CD4+ T cells responding to DENV [66] . Determining the specific mechanisms by which CD4+ T cells promote their effects is outside the scope of this study but remains an important question for future studies . In order to understand the implicit requirements for control of wtYFV , it will be important to study the mechanisms that lead to CD4+ T cell-mediated protection and the apparent inability of CD8+ T cells to limit disease . To conduct these studies , we have used a murine system that lacks type I interferon signaling . Type I interferon can act as a third signal [67] of T cell activation and is a pro-survival and proliferative cytokine [68] possibly affecting the responses in AB6 mice . Type I interferon plays a minimal role in T cell responses for some pathogens due to compensation by other third signal cytokines like IL-12 or as yet undefined pathogen-specific environments [68 , 69] . For example , Lymphocytic Choriomeningitis Virus ( LCMV ) -specific T cells lacking IFNAR have substantially inhibited proliferation whereas during Listeria monocytogenes ( LM ) infection , IL-12 acts as the predominant third signal [69–72] . The CD4+ and CD8+ T cell responses induced following 17D-204 vaccination were robust even in the absence of type I interferon signals , and were comparable in size to those seen against LCMV and LM in B6 mice [46 , 47] . Importantly , the size of the dominant CD4+ and CD8+ T cell responses in the IFNAR-/- mouse model accurately reflects the response to individual dominant epitopes in humans [16 , 17] . These observations suggest that the magnitude of activated T cell responses in 17D-204 vaccinated IFNAR-/- mice may accurately represent human responses . The influence of type I interferon on the adaptive immune response in humans to vaccinations with a 17D-based vaccine is unknown . Numerous publications indicate that human cells produce type I interferon in response to a 17D-based virus infection [73–78] . It is unknown what influence type I interferon has on human T cells during vaccination with the 17D line of vaccines , thus we cannot rule out the existence of deficiencies in the T cell phenotypes elicited by IFNAR-/- mice . To more carefully consider the role of type I interferon in humans , we assessed whether the 17D vaccine line induces a substantial type I interferon response in humans by independently analyzing gene expression data from PBMCs of human vaccinees published by Querec et al . [8] . This analysis indicated that immunization of humans with the 17D vaccine line does not result in significant increases in IFNα/β gene transcription in PBMCs ( S4 Fig ) . Our analysis does not rule out more localized production of type I interferons ( e . g . in the lymph nodes ) or in a small subset of PBMCs , and the original study did not measure levels of protein in the sera . However , should these transcription data be representative of the levels of type I interferon following 17D-based vaccination , it suggests that type I interferons may play a limited role physiologically for 17D based vaccine-specific T cells . Under the same scenario , the proliferation of 17D-based vaccine-specific T cells in humans may be driven by an undetermined third signal cytokine , or T cell expansion may be driven by abundant antigen from relatively high titers of virus in the lymphoid compartments [30] . In summary , we have used a murine model of YFV infection and disease to characterize the immune response to 17D-204 and determine empirically which immune constituents contribute to protection against wtYFV . The 17D-based vaccine strains constitute one of the world's most successful vaccines , demonstrating superior safety , efficacy and longevity compared to most subunit vaccines and LAVs . The characteristics of immune development and function seen following 17D-204 immunization in small animal models can serve as benchmarks for the development of other vaccines that aim to mimic its superior immunogenicity and long-lasting protection . Since we can now assess the role that cellular immunity plays in conferring protection , we can form a more complete picture of what contributes to vaccine efficacy in general . More specifically , 17D-204-elicited protection against wtYFV , defined by neutralizing antibodies and CD4+ T cell immunity , may be directly applied towards the development of vaccines against other flaviviruses like DENV and WNV . Continued study of 17D-204-elicited immunity may facilitate vaccine research by uncovering novel immune mechanisms of action , discovering innate immune correlates of protection , developing immunotherapies , or providing a platform for screening vaccine candidates .
Animals were maintained and procedures were performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Research Council . Protocols 1004668 , 1103456 , and 14033545 were approved by the University of Pittsburgh's IACUC committee . Approved euthanasia criteria were based on weight loss and morbidity . Mice deficient in receptors for type I interferons , ( IFNAR-/- , AB6 ) were bred under specific pathogen-free conditions . At 5–8 weeks of age , randomized male and female mice were transferred to the ABSL-2 or ABSL-3 facility for infection . Vaccination was administered subcutaneously ( s . c . ) in both rear footpads to 5–6 week old AB6 mice with 104 PFU of 17D-204 in a volume of 10ul in an ABSL-2 facility . Mock-vaccinated animals received 10uL of virus diluent ( PBS[with Mg+ , Ca+] containing 1% donor calf serum ) . Mice were observed for clinical disease and weighed daily . At 8–9 weeks of age , mice were transferred to an ABSL-3 facility and challenged s . c . in both rear footpads with 2x104 PFU Ang71 in a volume of 10uL . Mice were monitored daily for clinical disease and weight loss . Animals were euthanized based on morbidity or weight loss of 20% . For virus titers and qPCR , serum was separated from whole blood by centrifugation using microtainer tubes ( BD ) . Mice were perfused with 10mL of virus diluent prior to tissues being collected and frozen at -80C in virus diluent or Tri Reagent-LS ( MRC ) until the time of processing . 50uL of serum was frozen undiluted for titer or placed in Tri Reagent-LS for qPCR . Vero ( ATCC-CCL-81 ) , Huh7 ( Charles M . Rice , The Rockefeller University ) and B6/WT-19 ( Todd D . Schell , The Pennsylvania State University: College of Medicine ) cells were maintained in Dulbecco's modified Eagle's medium ( DMEM ) , supplemented with 10% fetal bovine serum ( FBS ) , 0 . 29 mg/mL L-glutamine , 100 U/mL penicillin and 0 . 05 mg/mL streptomycin ( 37C; 5% CO2 ) . B6/WT-19 cells are transformed by SV40 virus [79 , 80] . Stocks of YFV 17D-204 were produced from infectious clone [81] by electroporation of in-vitro transcribed ( IVT ) viral genomic RNA . 1ug of infectious clone DNA was linearized by restriction digest with Xho1 . Linear DNA was purified and used as a template for IVT ( mMESSAGE mMACHINE SP6 , Ambion ) . 20ug of IVT RNA was electroporated twice into vero cells during exponential growth phase harvested from three 50% confluent T175 tissue culture flasks using the following settings: 220V , 1uF , exponential decay . Electroporated cells were seeded into a single T175 flask in 15mL of media with HEPES ( 0 . 02M ) and sodium bicarbonate ( 0 . 15% ) and incubated for 7 days at 37C + 5% CO2 . Supernatant was harvested by centrifugation at 4000 RPM for 30 minutes and stored at -80C . The Ang71 ( 14FA [34 , 35] ) virus was amplified on vero cells as described previously [30] . Infectious virus titers were determined by a plaque assay on Huh7 cells , expressed as plaque forming units ( PFU ) /mL . RNA was isolated first by crushing tissue in Tri Reagent-LS and following the protocol provided by the manufacturer . Polyacryl carrier was added for serum isolation only . Reverse transcription of 100ng of purified RNA was performed for +-strand viral RNA using primer T7-YFV-antisense ( GCGTAATACGACTCACTATATACCATATTGACGCCCAGGGTTTT ) targeting a region of the 5'-non-coding region that is conserved between Ang71 and 17D-204 and 18s-antisense ( CGAACCTCCGACTTTCGTTCT ) using TaqMan reverse transcription reagents ( AB ) . Synthesis of cDNA consisted of 25C , 10 m followed by extension at 48C , 30 m and concluding with inactivation of RT at 95C , 5 m . Quantitative determination of YFV and 18s cDNA was performed using separate reactions in Maxima Probe qPCR Master Mix ( Thermo ) and read on a 7900HT Real-Time PCR System ( AB ) . Primers for YFV: T7 ( GCGTAATACGACTCACTATA ) , YFV-sense ( AATCGAGTTGCTAGGCAATAAACAC ) , and YFV-Probe ( CAGTTCTCTGCTAATCGCTCAACGAACG ) . Primers for 18s: 18s-antisense , 18s-sense ( CGCCGCTAGAGGTGAAATTCT ) and 18s-Probe ( CAAGACGGACCAGAGCGAAAGCATTTG ) . Cycling conditions consisted of: denaturing and polymerase activation at 95C , 10 m; followed by 40 cycles of denaturing at 95C , 15 s then extension at 60C , 1 m . Fluorescence intensity data was collected during the extension step . The YFV GE standard curve was based on 10 fold dilutions of 17D-204 IVT RNA . The LOQ was set to the GE represented by the greatest dilution of standard remaining on the logarithmic curve . We found that expression of 18s in 100ng of RNA varied among tissues , thus mean 18s Ct values were calculated for each tissue type ( e . g . spleen , brain , etc . ) and these values were used to correct for sample loading error . A mouse cytokine 20-plex panel kit was purchased from Invitrogen ( LMC0006 ) . According to the manufacturer's instructions , serum was diluted 1:1 with diluent and analyzed using a Luminex 100/200 instrument . Serial dilutions of control antibody or serum were incubated for 1 hour at 37C + 5% CO2 with approximately 100 PFU of 17D-204 or Ang71 . PFU of non-neutralized virus was determined using a standard plaque assay on Huh7 cells . Plaques remaining at all dilutions were counted and expressed as a percent of plaques remaining with mock serum samples . A best fit non-linear curve constrained to maximum 100 percent of mock and minimum zero percent of mock was used to calculate the 80 percent reduction in PFU . Peptides were ordered from GenScript at > 90% purity and resuspended in PBS + 5% DMSO at 1mM concentration . Peptides designated as YFI or YFII are respectively MHC-I or MHC-II restricted peptides originating in 17D-204 . The designations E or NS3 indicate the 17D-204 protein in which the peptide originates . Peptides: YFI-E ( 4–12 ) IGITDRDFI; YFI-NS3 ( 268–275 ) , ATLTYRML; YFII-E ( 231–245 ) , LVEFEPPHAATIRVL [31]; SV40T-I ( 206–215 ) , SAINNYAQKL [82]; OVA-I ( 255–262 ) , SIINFEKL; HBV Core ( 128–140 ) , TPPAYRPPNAPIL . All YFV peptides are conserved between 17D-204 and Ang71 . ICS and cell surface staining was performed on single cell suspensions from spleens or lymph nodes created by pushing the tissues through a 70uM nylon mesh ( Fisher ) . For ICS , up to 4x106 total cells were incubated in 200uL of T cell growth media ( RPMI 1640 containing 10% FCS , 100 U/mL penicillin , 20uM 2-ME , 1mM sodium pyruvate and 10mM HEPES ) supplemented with 1uM of peptide , monensin ( BD GolgiStop ) according to the manufacturer's instructions and 1:50 anti-CD107a-PE . Cultures were incubated for 5 hours at 37C and 5% CO2 . Staining for ICS: Cell were stained for 30 minutes on ice with 1:1000 dilution of Invitrogen Blue LIVE/DEAD stain in PBS . Cells were washed 1x in FACS buffer ( PBS supplemented with 2% FBS and 0 . 1% sodium azide ) . Cells were then incubated in a 1:200 dilution of rat anti-mouse CD16/CD32 on ice for 20 min then washed 1x with FACS buffer . Fluorophore conjugated antibodies ( 1:200 dilution ) were added to the cells and incubated for 30 minutes on ice than washed 3x with FACS buffer . Cells were then fixed and permeabilized using Cytofix/Cytoperm solution ( BD ) on ice for 20 minutes then washed 3x in Perm/Wash ( BD ) . Staining was completed with 1:200 dilutions of fluorophore conjugated antibodies in Perm/Wash for 15 min at room temperature then washed 3x with Perm/Wash . Cells were fixed in 4% PFA in PBS and stored at 4C O/N prior to analysis . Surface staining: Cells were stained for 15 minutes at 1:1000 dilution of Invitrogen Blue LIVE/DEAD stain in PBS . Cells were washed 1x in FACS buffer then incubated in a 1:200 dilution of rat anti-mouse CD16/CD32 for 15 minutes then washed 1x with FACS buffer . Fluorophore conjugated antibodies ( 1:200 dilution ) were added to the cells and incubated for 15 minutes at room temperature than washed 3x with FACS buffer prior to fixation in 4% PFA . FACS analysis was performed the following day . All data were collected using a LSR II or Fortessa flow cytometer ( BD ) administered by the University of Pittsburgh’s Unified Flow Core . If available , a minimum of 300 , 000 live events were collected based on FSC-A/SSC-A and live/dead gating . Data were analyzed using FlowJo software ( Tree Star ) . The following flow cytometry antibodies were purchased from eBiosciences or Tonbo biosciences: CD8α ( 53–6 . 7 ) , CD4 ( GK1 . 5 ) , CD19 ( eBio 1D3 ) , CD44 ( IM7 ) , CD62L ( MEL-14 ) , CD11a ( M17/4 ) , IFNγ ( XMG1 . 2 ) , TNFa ( MP6-XT22 ) , IL-2 ( JES6-5H4 ) , IL-4 ( 11B11 ) , KLRG1 ( 2F1 ) , CD127 ( A7R34 ) , CD107a-PE ( eBio1D4B ) . Splenocytes from naive AB6 mice were incubated for 1 hour at 37°C in complete media with 1uM of the indicated peptides . Free peptide was removed by washing three times in PBS . Each splenocyte population was fluorescently marked by staining with 1uM eFluor 450 or eFluor 670 Cell Proliferation Dye ( eBioscience ) and 5 , 0 . 5 or 0 . 05 uM CFSE ( eBioscience ) in PBS for 10 minutes at 37°C . Staining was halted by addition of T cell growth media then cells were washed 3 times in PBS , combined in equal ratios then transferred to infected mice . 16 hours following transfer , spleens and/or popliteal lymph nodes were harvested and stained with anti-CD19 prior to evaluation by flow cytometry . As a positive control for cytolytic T cell activity , a group of mice was immunized i . p . with 2x107 B6/WT-19 cells and evaluated on d7 following immunization for specific lysis against the SV40 TAg site I determinant ( SV40T-I ) . The number of splenocytes remaining in the MHC-I restricted peptide populations ( YFI-NS3 , YFI-E , OVA-I and SV40T-I ) was calculated from total splenocytes . The number of cells remaining in the MHC-II restricted peptide populations ( YFII-E and HBV-Core ) was calculated using total CD19+ splenocytes . Specific lysis was calculated by the following formula for the YFI-NS3 peptide: ( [Peptide in mock mice/OVA-I in mock mice]–[Peptide in immunized mice/OVA-I in immunized mice] ) / [Peptide in mock mice/OVA-I in mock mice] . Specific lysis was calculated by the following formula for the YFI-E peptide: ( [Peptide in mock mice/SV40T-I in mock mice]–[Peptide in immunized mice/SV40T-I in immunized mice] ) / [Peptide in mock mice/SV40T-I in mock mice] . Specific lysis for the YFII-E peptide was calculated using: ( [Peptide in mock mice/HBV-Core in mock mice]–[Peptide in immunized mice/HBV-Core in immunized mice] ) / [Peptide in mock mice/HBV-Core in mock mice] . Splenocytes and lymphocytes from 17D-204 immunized mice , on d21 post immunization , were pooled and stained with MicroBeads ( Miltenyi ) as per the manufacturer’s recommendations . Stained cells were subjected to positive selection using the AutoMACS automated sorting system . First the CD19 positive fraction was collected . Then the CD19 negative fraction was stained with CD8 MicroBeads and the positive fraction was collected . Finally , the CD8 negative fraction was stained with CD4 MicroBeads and the positive fraction was retained . Positive fractions were evaluated for purity ( S2 Fig ) and combined as indicated ( Figs 5 and 10 ) , washed two times with PBS and adoptively transferred into naive mice by intravenous injection . The number of each cell type transferred into each mouse was maximized resulting in each mouse from each experiment receiving approximately: CD4+ , 1 . 5x106 cells; CD8+ , 3 . 5x106 cells; CD19+ , 5 . 0x106 cells . In addition , a mix of serum pooled from all 17D-204 immune mice was injected i . p . into naive mice in a volume of 170ul . Twenty-four hours following transfer , mice were challenged with Ang71 . See each table or figure legends for statistical analysis . | The 17D line yellow fever virus ( YFV ) vaccines are some of the safest and most effective live-attenuated virus vaccines ever produced , protecting recipients for life against deadly yellow fever ( YF ) . As a testament to this safety and efficacy , the 17D line of live-attenuated vaccines has become an important model for the design of future vaccines . However , we still lack a fundamental understanding of the protective immunity elicited against the virulent YFV , a knowledge gap that must be overcome to inform the design of future live-attenuated and subunit vaccines . Humans develop robust antibody and T cell responses following vaccination , leading some to suggest that vaccine-elicited CD8+ T cells are important for protection against virulent YFV . Since this can never be tested in humans , we have used mice to model immunity to the 17D-204 vaccine strain . We found that CD4+ T cells elicited by 17D-204 contributed to protection against virulent YFV , but CD8+ T cells had no effect on the outcomes of survival or disease . Our study is the first to demonstrate that vaccine-elicited CD4+ T cells can protect against YFV infection . These results suggest that vaccine developers should consider the importance of CD4+ T cells when designing vaccines against viruses similar to YFV . | [
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] | 2016 | The 17D-204 Vaccine Strain-Induced Protection against Virulent Yellow Fever Virus Is Mediated by Humoral Immunity and CD4+ but not CD8+ T Cells |
Specific types of human papillomaviruses ( HPVs ) cause cervical cancer . Cervical cancers exhibit aberrant cellular microRNA ( miRNA ) expression patterns . By genome-wide analyses , we investigate whether the intracellular and exosomal miRNA compositions of HPV-positive cancer cells are dependent on endogenous E6/E7 oncogene expression . Deep sequencing studies combined with qRT-PCR analyses show that E6/E7 silencing significantly affects ten of the 52 most abundant intracellular miRNAs in HPV18-positive HeLa cells , downregulating miR-17-5p , miR-186-5p , miR-378a-3p , miR-378f , miR-629-5p and miR-7-5p , and upregulating miR-143-3p , miR-23a-3p , miR-23b-3p and miR-27b-3p . The effects of E6/E7 silencing on miRNA levels are mainly not dependent on p53 and similarly observed in HPV16-positive SiHa cells . The E6/E7-regulated miRNAs are enriched for species involved in the control of cell proliferation , senescence and apoptosis , suggesting that they contribute to the growth of HPV-positive cancer cells . Consistently , we show that sustained E6/E7 expression is required to maintain the intracellular levels of members of the miR-17~92 cluster , which reduce expression of the anti-proliferative p21 gene in HPV-positive cancer cells . In exosomes secreted by HeLa cells , a distinct seven-miRNA-signature was identified among the most abundant miRNAs , with significant downregulation of let-7d-5p , miR-20a-5p , miR-378a-3p , miR-423-3p , miR-7-5p , miR-92a-3p and upregulation of miR-21-5p , upon E6/E7 silencing . Several of the E6/E7-dependent exosomal miRNAs have also been linked to the control of cell proliferation and apoptosis . This study represents the first global analysis of intracellular and exosomal miRNAs and shows that viral oncogene expression affects the abundance of multiple miRNAs likely contributing to the E6/E7-dependent growth of HPV-positive cancer cells .
Oncogenic human papillomaviruses ( HPVs ) , such as HPV16 and HPV18 , cause cervical cancer . Infections with oncogenic HPV types are moreover closely linked to the development of additional human malignancies in the oropharynx and anogenital region [1] . The viral E6 and E7 oncoproteins are crucial both for the HPV-associated induction of transformation as well as for the maintenance of the tumorigenic phenotype of HPV-positive cervical cancer cells [2 , 3] . For example , E6 induces the proteolytic degradation of the p53 tumor suppressor protein [4] and stimulates telomerase activity [5] , whereas E7 interferes with the activity of the retinoblastoma tumor suppressor protein , pRb , and other pocket proteins [6] . As a consequence , E6 and E7 deregulate intracellular pathways involved in the control of cellular proliferation , senescence , apoptosis , and genetic stability . Importantly , at least some of these pathways are not irreversibly impaired by HPVs . Rather , inhibition of viral E6/E7 activities in HPV-positive cancer cells leads to the reactivation of dormant tumor suppressor pathways . For instance , several studies indicate that inhibition of E6 primarily results in apoptosis [7–11] , whereas combined inhibition of E6/E7 leads to growth arrest and cellular senescence [12–14] . The reversibility of the malignant phenotype of HPV-positive tumor cells is not only phenomenologically interesting but may also form a rational basis for therapeutic interference . This could , in principle , be achieved by blocking the E6/E7 oncogenes or , alternatively , by correcting downstream cellular pathways that are deregulated by the viral oncogenes . Therefore , it is important to uncover crucial cellular targets that are affected by viral E6/E7 oncogene expression and that support the growth of HPV-positive cancer cells . Micro ( mi ) RNAs are short ( 21–23 nt ) , non-coding , highly-conserved RNAs that post-transcriptionally regulate gene expression [15] . For several tumor entities , it has been shown that the deregulation of the cellular miRNA network plays a critical role for cancer development and maintenance [16 , 17] . The oncogenicity of miRNAs has been particularly well demonstrated for members of the miR-17~92 cluster ( also called “oncomir-1”; coding for miR-17 , miR-20a , miR-18a , miR-19a , miR-19b and miR-92a ) and of its paralog cluster miR-106b~25 ( coding for miR-106b , miR-93 and miR-25 ) [18] . Potential cellular target genes for members of the two miRNA clusters include p21 , which codes for a cyclin-dependent kinase inhibitor that plays a central role for growth control and induction of the senescence pathway in many cells [19 , 20] . In contrast to other tumor viruses , such as Epstein-Barr virus ( EBV ) or Kaposi’s sarcoma-associated herpesvirus ( KSHV ) , oncogenic HPV types presumably do not encode own viral miRNAs [21 , 22] . However , global miRNA analyses indicate an upregulation of oncogenic miRNAs and a decrease of tumor-suppressive miRNAs in cervical cancer biopsies [23–38] and in cervical cancer cell lines [39–41] , in comparison to normal cervical tissue . A contribution of HPVs to the deregulation of miRNA expression in cervical cancer was proposed , mainly based on comparisons between HPV-positive and -negative cell lines [41] , and on cell culture models upon introduction of HPV genomes [22 , 42 , 43] . More direct evidence that the HPV oncogenes have the potential to influence the cellular miRNA composition was provided by experiments that involved ectopic expression of the viral E6 and/or E7 genes in keratinocytes and subsequent global miRNA analysis [44] or investigation of selected miRNAs [45 , 46] . However , the miRNA species identified by these different experimental approaches vary substantially ( see Discussion ) . Most importantly , the crucial question whether the E6/E7-dependent maintenance of the growth of HPV-positive cancer cells is linked to specific alterations of the global miRNA network has not been addressed . To resolve this issue , we here performed a comprehensive analysis of the intracellular miRNA composition in HPV-positive cancer cells , upon silencing of endogenous E6/E7 oncogene expression . An interesting miRNA pool that recently gained interest in cancer research is the miRNA content of exosomes . Exosomes are small extracellular vesicles ( 50–100 nm in diameter ) of endosomal origin that are secreted by a variety of cells , including tumor cells [47] . Exosomes may play an important role for the intercellular communication of tumor cells since they can accelerate cancer growth and invasiveness by horizontally transferring proteins , mRNAs , and non-coding RNAs from tumor cells into recipient cells [48–50] . In the case of miRNAs , several studies showed specific target gene repression in recipient cells upon intercellular transfer of miRNAs via exosomes [51–55] . Also other human tumor viruses , EBV [51 , 56 , 57] and possibly KSHV [58] , may utilize exosomes to modulate the tumor microenvironment by transporting viral proteins and virus-encoded miRNAs . Due to the facts that exosomes can be isolated from different body fluids ( e . g . serum , saliva , urine ) and that their content allows conclusions about their cell of origin , exosomes are also intensively investigated as a source of novel biomarkers [59–61] . The above considerations raise two important issues concerning the interplay between HPVs and the miRNA network in cervical cancer cells . First , is the intracellular miRNA pool of HPV-positive tumor cells dependent on the sustained expression of the viral E6/E7 oncogenes ? Second , is the miRNA composition of exosomes that are secreted by HPV-positive cancer cells affected by the HPV oncogenes ? To answer these questions , we performed a comprehensive deep sequencing study in order to identify the influence of the endogenous E6/E7 oncogene expression on the global miRNA composition of HPV-positive cervical cancer cells , both at the intracellular and at the exosomal level .
In order to investigate the influence of the HPV oncogenes on the intracellular miRNA composition of HPV-positive cancer cells , endogenous HPV18 E6/E7 expression in HeLa cervical carcinoma cells was blocked by RNA interference ( RNAi ) for subsequent deep sequencing analyses . Treatment with E6/E7-targeting siRNAs ( si18E6/E7 ) led to efficient downregulation of E6/E7 mRNA levels as shown by qRT-PCR analyses , using primers recognizing all three transcript classes [8] coding for HPV18 E6 and E7 ( Fig . 1A , left panel ) . A substantial reduction of the HPV18 E6 and E7 protein levels 72 h after transfection with si18E6/E7 was observed ( Fig . 1B/C ) . This was linked to increased p53 protein levels ( Fig . 1B ) , as expected from the ability of E6 to induce the degradation of p53 [4] , and increased p21 mRNA and protein levels ( Fig . 1A/B ) , representing a downstream transcriptional target gene for p53 [62] . Further , E6/E7 silencing was associated with an increase of total pRb protein levels , consistent with the ability of E7 to induce pRb degradation [6] , as well as with decreased amounts of phosphorylated pRb and of Cyclin A1 , indicating reactivation of the pRb cascade ( Fig . 1C ) . cDNA libraries were generated from RNA samples isolated from cells in which the viral oncogene expression was silenced ( si18E6/E7 ) or which underwent control treatment ( siContr-1 ) . In order to capture a broad spectrum of E6/E7-modulated miRNAs—unbiased by a pre-selection—analyses of total miRNA contents were accomplished by small RNA deep sequencing using the Illumina platform . Sequencing of the libraries resulted in raw read counts that were pre-processed to remove adapter sequences and filtered to exclude low quality reads ( S1 Table ) . Mean read counts of cellular sequences mapping to known human miRNAs ranged from 1 to 1 , 170 , 975 ( S1 Dataset , Fig . 2A for a read count distribution of cellular miRNAs ) . For cross-library comparison , the read count of a given miRNA was normalized to the total number of uniquely mapped miRNA reads per library and expressed as reads per million ( RPM ) mapped reads . RPM values of the 15 most frequently sequenced cellular miRNAs are displayed in Fig . 2B . For stoichiometric reasons , it is assumed that mainly miRNAs with a high intracellular abundance can lead to the repression of their target genes , whereas low-abundant miRNAs , identified in deep sequencing studies with < 100 RPM , are frequently not functional [63] . Therefore , an arbitrary threshold of 1 , 000 RPM for an individual miRNA in each sample was set and , consequently , 52 cellular miRNAs were further analyzed . Deregulation was defined as a > 1 . 5-fold change between si18E6/E7- and siContr-1-treated samples . An overview on the number of deregulated cellular miRNAs is given in Fig . 2C , showing that endogenous E6/E7 silencing affected 23 of the 52 most abundant miRNAs in HeLa cells ( 15 down- and 8 upregulated ) . The relative expression upon E6/E7 silencing of each of the 52 miRNAs is displayed in Fig . 2D . The RPMmean values and fold changes of the 23 E6/E7-regulated miRNAs are indicated in S2 Table . The 23 miRNAs comprise several family members of the miR-378 family ( miR-378a-3p , miR-378c , miR-378d , miR-378f ) , as well as members of the miR-17~92 and miR-106b~25 clusters ( miR-17–5p , miR-19b-3p , miR-93–5p ) . Moreover , two seed families , the miR-23 family ( miR-23a-3p , miR-23b-3p ) and miR-27 family ( miR-27a-3p , miR-27b-3p ) , were upregulated . The E6/E7-mediated modulation of cellular miRNAs was subsequently validated by qRT-PCR analyses . For normalization , small nuclear RNA ( snRNA ) RNU6–2 was employed . Ct-values for RNU6–2 were consistent for si18E6/E7- or siContr-1-treated samples and across experimental conditions . Of the 23 abundant cellular miRNAs that were found to be affected in deep sequencing analyses , deregulation ( up or down ) upon silencing of endogenous E6/E7 expression was confirmed for 21 miRNAs ( 91% ) by qRT-PCR ( dark grey columns in Fig . 2E ) , 17 of which exhibited a fold change of > 1 . 5 ( Fig . 2E and S2 Table ) . This shows high agreement between the two methods . Statistical significance of the qRT-PCR data was obtained for ten of these 17 miRNAs: downregulation of miR-17–5p , miR-186–5p , miR-378a-3p , miR-378f , miR-629–5p and miR-7–5p and upregulation of miR-143–3p , miR-23a-3p , miR-23b-3p and miR-27b-3p , upon E6/E7 silencing ( Fig . 2E and indicated in bold in S2 Table ) . In summary , the combination of small RNA deep sequencing and qRT-PCR analyses identified ten abundant cellular miRNAs that are significantly affected in HeLa cells upon silencing of endogenous E6/E7 oncogene expression . Next , we analyzed the expression of these ten miRNAs upon repressing endogenous E6/E7 expression in SiHa cervical cancer cells ( Fig . 3 ) . In contrast to HPV18-positive HeLa cells , which are derived from an adenocarcinoma of the cervix , SiHa cells express HPV16 E6/E7 and originate from a cervical squamous cell carcinoma . As expected , silencing of endogenous HPV16 E6/E7 expression by RNAi in SiHa cells was linked to reduced E6/E7 protein expression and reconstitution of the p53 pathway ( Fig . 3A ) . Notably , both cell lines reveal a substantial overlap in the regulation patterns of the ten selected miRNAs , upon endogenous E6/E7 repression ( Fig . 2E and Fig . 3 ) . In specific , with the exception of miR-378f , the levels of nine of the ten selected miRNAs were modulated in the same direction ( up or down ) in both cell lines upon silencing of E6/E7 expression , with five of these changes also exhibiting statistical significance in SiHa cells ( Figs . 3B ) . Thus , although the two cell lines contain different HPV types and were established from cervical cancers with different histopathological backgrounds , there is a substantial similarity of the regulation of these miRNAs upon endogenous E6/E7 inhibition . The p53 protein can positively or negatively affect the expression of tumor-associated miRNAs [64] . Since p53 is strongly upregulated following E6/E7 repression ( Fig . 1B ) , we addressed the question whether the miRNA changes observed upon E6/E7 silencing are p53-dependent . For these analyses , we comparatively investigated the miRNA regulation in parental HeLa cells and in “p53-null” HeLa cells . In the latter cells , endogenous p53 expression is silenced by a stably integrated vector expressing a short hairpin ( sh ) RNA that targets the p53 mRNA [65] . HPV18 E6/E7 expression could be repressed by siRNA in both cell lines with a comparable high efficiency ( Fig . 4A , left panel ) . Basal p53 protein levels were undetectable in “p53-null” cells and remained extremely low even upon endogenous E6/E7 silencing , indicating that the system exhibits only a very minute degree of leakiness ( Fig . 4B ) . Consistently , expression of the p53 target gene p21 is not increased upon E6/E7 silencing in “p53-null” HeLa cells , both at the RNA and protein levels ( Fig . 4A , right panel , and Fig . 4B ) , corroborating that the p53 pathway is efficiently blocked in these cells . For miRNA analyses , we utilized miR-34a-5p as a positive control since it is well-documented as a p53-inducible miRNA [64] . In line , we found that miR-34a-5p amounts were also increased ( 6 . 2-fold ) in the deep sequencing analysis upon E6/E7 silencing , however , it did not reach the RPM threshold of > 1 , 000 ( RPMsiContr-1 = 64; RPMsi18E6/E7 = 385 ) . As shown in Fig . 4C , induction of miR-34a-5p upon E6/E7 silencing is clearly detectable by qRT-PCR analyses in parental HeLa cells but virtually abolished in “p53-null” HeLa cells . In contrast to miR-34a-5p , the intracellular levels of eight of the ten miRNAs that were defined as E6/E7-regulated in parental HeLa cells also exhibited statistically significant changes in “p53-null” HeLa cells ( Fig . 4C ) , with congruency in the direction of change ( up or down ) . Only two miRNAs , miR-186–5p and miR-378f , showed a discrepant regulation in that they were no longer repressed in “p53-null” HeLa cells upon E6/E7 silencing , suggesting that p53 may directly or indirectly reduce their expression . Taken together , these experiments indicate that a substantial proportion ( eight of ten ) of the most abundant and significantly affected cellular miRNAs is modulated by endogenous E6/E7 expression in a p53-independent manner . The 52 most abundant cellular miRNAs that were downregulated > 1 . 5-fold upon E6/E7 silencing in both deep sequencing and qRT-PCR analyses encompassed miR-17–5p and miR-19b-3p , two members of the miR-17~92 cluster , and miR-93–5p , a member of the paralog miR-106b~25 cluster ( Fig . 2D/E ) . Further qRT-PCR analyses revealed that all detectable additional members the miR-17~92 and miR-106b~25 clusters were also downregulated upon silencing of endogenous E6/E7 expression ( S3 Table ) . These findings indicate that continuous E6/E7 expression increases the intracellular concentrations of multiple miRNAs from both oncogenic miRNA clusters in HPV-positive cancer cells . Four miRNAs encoded by the miR-17~92 and miR-106b~25 clusters ( miR-17–5p , miR-20a-5p , miR-106b-5p , miR-93–5p ) are grouped into the miR-17 family , according to their identical seed sequence , and target two binding sites in the 3’ UTR of p21 [66 , 67] . All four miRNAs exhibited a > 1 . 5-fold downregulation in HeLa cells upon endogenous E6/E7 silencing in deep sequencing and/or qRT-PCR analyses ( S3 Table ) . This raises the question whether the E6/E7-dependent increase of p21-targeting miRNAs may lead to p21 repression in HPV-positive cancer cells and thereby contributes to their proliferative capacity and resistance towards senescence . In order to investigate this possibility , we first addressed the controversially discussed issue whether p21 is required for senescence induction upon E6/E7 silencing in HPV-positive cancer cells [13 , 68] . Therefore , siRNAs ( si18E6/E7 , siContr-1 and siP21 ) were utilized to achieve silencing of E6/E7 only , p21 only , or E6/E7 together with p21 . Inhibition of p21 alone had no effect on HPV18 E6/E7 expression ( Fig . 5A , left panel ) , whilst it efficiently counteracted the induction of p21 mRNA and protein levels upon E6/E7 inhibition ( Fig . 5A , right panel , and Fig . 5B ) . Cell cycle analyses revealed that E6/E7 silencing alone led to an increase in G1- and decrease in S-phase populations , indicative for a G1-arrest ( Fig . 5C/D ) . p21 silencing alone , led to an increase in S-phase and reduction in G1-phase populations ( Fig . 5C/D ) . Notably , the G1-arrest observed when inhibiting E6/E7 alone was diminished when silencing p21 in parallel , and S-phase populations doubled ( from 6 to 12% , p-value = 0 . 059 ) , 72 h post transfection . Moreover , 168 h after transfection only a fraction ( 15% ) of the cells stained positive for the senescence marker Senescence-Associated β-Galactosidase ( SA-β-Gal ) when p21 and E6/E7 were silenced together , whereas the majority of cells remained unstained ( Fig . 5E ) . This was in clear contrast to the results for E6/E7 silencing alone , where almost all cells ( 85% ) exhibited morphological signs of senescence ( cellular enlargement and flattening , long cytoplasmic projections and positive staining for SA-β-Gal ) , 168 h after transfection ( Fig . 5E ) . In conclusion , parallel silencing of E6/E7 and p21 strongly alleviated the induction of senescence that occurs upon mere E6/E7 repression . This indicates that p21 is a contributor to the senescence induction upon E6/E7 silencing in HPV-positive cancer cells . Next , it was studied whether an experimental increase of mir-17~92 expression , encoding two p21-targeting miRNAs , miR-17–5p and miR-20a-5p [18] , can contribute to keep basal levels of p21 expression low in HeLa cells . Transfection of a mir-17~92 expression vector led to an increase of miR-17–5p , miR-20a-5p , miR-19b-3p and miR-92a-3p levels , as expected , but not of miR-34a-5p , which served as a negative control ( Fig . 6A ) . Notably , basal p21 expression in HeLa cells was reduced by overexpression of the miR-17~92 cluster , both at the mRNA and protein level ( Fig . 6B/C ) . In reciprocal experiments , we investigated whether the downmodulation of miR-17–5p and miR-20a-5p in HeLa cells might result in an upregulation of p21 levels . Therefore , HeLa cells were transfected with a control miRNA inhibitor ( “Inhib . control” ) that carries no homology to any known mammalian gene or with specific miRNA inhibitors of miR-17–5p , miR-20a-5p , and miR-19b-3p . The latter miRNA inhibitor served as additional control , since its target miRNA does not possess a known binding site in the p21 transcript . The inhibitors of miR-17–5p and miR-20a-5p but neither the inhibitor control nor the miR-19b-3p inhibitor led to a significant upregulation of p21 protein levels ( Fig . 6D ) . Taken together , these results indicate that continuous E6/E7 oncogene expression in HPV-positive cancer cells is required to maintain miRNAs of the oncogenic miR-17~92 cluster at a level that keeps expression of the anti-proliferative p21 gene low . To investigate the influence of viral E6/E7 expression on the exosomal miRNA contents , exosomes secreted by HeLa cells were isolated from the cell culture medium by employing a protocol for exosome enrichment involving sequential ( ultra- ) centrifugation steps [69] , with minor modifications ( see Material and Methods ) . A characterization of the exosome preparations used for the deep sequencing studies is presented in Fig . 7 . The preparations stained positive for the exosomal markers HSC70 , CD63 , Annexin-1 , β-Actin and CD9 , showing the typical exosomal enrichment for the tetraspanins CD63 and CD9 [69] ( Fig . 7A ) . The absence of detectable bands for the endoplasmatic reticulum ( ER ) marker GRP78 and the early endosome marker EEA1 indicate only minor , or no , contamination with vesicles from other origins . Electron microscopy ( EM ) revealed the presence of small membrane vesicles with a diameter of 50–100 nm , possessing the typical cup-shaped appearance of exosomes in EM analyses [69] ( Fig . 7B ) . To investigate possible effects of the HPV oncogenes on the miRNA composition of exosomes , we treated HeLa cells with siRNAs blocking endogenous HPV18 E6/E7 expression or with control siRNA ( siContr-1 ) . Forty-eight hours after transfection , cells were allowed to secrete newly formed exosomes for 24 h into the cell culture medium pre-depleted of FBS-derived microvesicles . Inhibition of E6/E7 expression upon transfection of synthetic siRNAs was maintained over the time period required for exosome production and secretion ( Fig . 1 ) . Total RNA was extracted from RNase A-treated exosomes and quality and quantity of the isolated RNA samples were assessed using an Agilent Bioanalyzer ( Fig . 7C ) . In parallel , cellular RNA extracted from the respective exosome-producing cells was examined . The total RNA profile ( Fig . 7C , upper panel ) showed distinct differences between cellular and exosomal RNA , with exosomes lacking discernible 18S and 28S rRNA peaks , in agreement with previous publications [48 , 70] . Both cellular and exosomal RNA revealed a peak for transfer RNAs ( tRNAs ) and miRNAs ( size range as indicated ) in the small RNA profiles ( Fig . 7C , lower panel ) . Subsequently , the exosomal RNA samples were converted into cDNA libraries , subjected to small RNA deep sequencing and initial analysis was performed as described above for cellular miRNAs . The composition of exosomal and intracellular small RNA fractions differed in that the relative percentage of miRNAs among different classes of small RNAs was approximately 50% lower in exosomes ( S1 Fig ) . E6/E7 silencing only slightly affected the intracellular distribution of small RNA classes , but approximately doubled the relative percentage of miRNAs inside exosomes ( S1 Fig ) . Mean read counts of exosomal sequences mapping to known human miRNAs ranged from 1 to 445 , 143 in exosomes ( S1 Dataset , Fig . 8A for a read count distribution of exosomal miRNAs ) . RPM values of the 15 most frequently sequenced miRNAs in exosomes are displayed in Fig . 8B . Forty-seven exosomal miRNAs showed > 1 , 000 RPM in each sample and were subjected to further analysis . Thirty-six of these 47 exosomal miRNAs were also found among the 52 most abundant intracellular miRNAs with > 1 , 000 RPM ( S1 Fig ) . Relative quantification of si18E6/E7- versus siContr-1-treated samples revealed that—among the 47 most commonly detected exosomal miRNAs—21 were down- and four upregulated more than 1 . 5-fold upon intracellular E6/E7 silencing ( Fig . 8C ) . The relative expression of each of these 47 miRNAs upon E6/E7 silencing is displayed in Fig . 8D . The RPMmean values of the 25 E6/E7-modulated exosomal miRNAs are indicated in S4 Table . They encompass several family members with identical seed regions , including the let-7 family ( let-7a-5p , let-7d-5p , let-7f-5p , let-7g-5p ) , miR-378 family ( miR-378a-3p , miR-378c ) , miR-99 family ( miR-99a-5p , miR-100–5p ) , as well as members of the miR-17~92 cluster ( miR-20a-5p , miR-92a-3p ) . Next , the effects of E6/E7 expression on exosomal miRNAs—as identified by small RNA deep sequencing—were validated by qRT-PCR analyses . So far , there is no common RNA species for normalization of exosomal miRNA levels available . Therefore , two miRNAs , miR-452–5p and miR-183–5p , were chosen as stable endogenous exosomal miRNA controls based on the small RNA deep sequencing data ( in analogy to refs . [71 , 72] ) . Both miRNAs were frequently sequenced ( > 1 , 000 RPM in each sample ) and showed virtually no alterations of their exosomal concentrations upon E6/E7 silencing versus control treatment ( miR-452–5p: FCmean = 0 . 99 , miR-183–5p: FCmean = 1 . 04 ) . Modulation ( up or down ) upon inhibition of HPV18 E6/E7 expression was confirmed for roughly three quarters ( 72% ) of the identified exosomal miRNAs by qRT-PCR analyses ( Fig . 8E , dark grey columns ) . A statistically significant and > 1 . 5-fold decrease upon E6/E7 silencing was detected for exosomal let-7d-5p , miR-20a-5p , miR-378a-3p , miR-423–3p , miR-7–5p , miR-92a-3p , whereas miR-21–5p exhibited a statistically significant and > 1 . 5-fold increase upon E6/E7 silencing ( illustrated in bold in S4 Table ) . These findings indicate that continuous HPV E6/E7 oncogene expression determines a signature of seven miRNAs in exosomes secreted from HeLa cells in that it leads to significantly increased let-7d-5p , miR-20a-5p , miR-378a-3p , miR-423–3p , miR-7–5p , miR-92a-3p and decreased miR-21–5p levels . Comparative analyses of the above identified seven miRNAs in exosomes secreted by HPV16-positive SiHa cells revealed that the concentrations of all these are congruently modulated ( up or down ) upon inhibiting endogenous HPV16 E6/E7 expression ( Fig . 9 ) . Six of these seven miRNA alterations were also statistically significant in SiHa cells , with a > 1 . 5-fold change observed for four of them ( Fig . 9 ) . Thus , similar to the results obtained for the regulation of intracellular miRNAs , there is substantial overlap in the E6/E7-dependent regulation of miRNA species in exosomes secreted by HPV16- and HPV18-positive cancer cells .
The growth of HPV-positive cancer cells requires the continuous expression of the viral E6/E7 oncogenes [2 , 7 , 13 , 73–76] . To address the question whether this process is linked to alterations of the miRNA network , we here analyzed the influence of the E6/E7 expression on the intracellular and exosomal miRNA pools of HPV-positive cancer cells . We found that ten of the 52 most abundant intracellular miRNAs identified by deep sequencing analyses of HeLa cells were significantly affected upon silencing of endogenous viral oncogene expression . Notably , they are enriched for miRNAs that are linked to the regulation of cell proliferation , senescence and apoptosis , suggesting that the E6/E7-linked modulation of the miRNA network contributes to the growth of HPV-positive cancer cells . Consistently , we observed that the sustained endogenous E6/E7 expression is linked to an increase of miRNAs with growth promoting potential ( e . g . members of the miR-17~92 cluster blocking p21 expression ) . In addition , we determine the miRNA content of exosomes secreted from HPV-positive cancer cells and delineate specific miRNAs whose exosomal concentrations are dependent on viral oncogene expression . Several previous studies have identified miRNAs as potential targets for HPVs or have linked specific miRNAs to cervical carcinogenesis . By performing medline searches for the two keywords miRNA/microRNA and HPV/cervical cancer , 258 different publications were found ( date: November 26th , 2014 ) . Twenty-one of these reports encompass global miRNA profiling studies , performing analyses of the miRNA expression in tumorous versus normal cervical cancer tissue ( 13 publications ) , in different in vitro cell culture models ( 7 publications ) , or in both ( 1 publication ) . S5 Table provides an overview on these 21 studies and indicates the used platforms for miRNA analysis and the various experimental conditions . Only two of these studies performed comprehensive small RNA deep sequencing analyses [22 , 43] , without a pre-selection of candidate miRNAs ( e . g . for microarray design ) . We withdrew from these 21 publications the miRNAs that were reported to be differentially regulated in cervical cancer tissue or in in vitro models , and updated the original miRNA nomenclature of the publications to the current miRBase entries ( release 21 , June 2014 ) . As a result , 483 different mature miRNAs have been proposed by these 21 studies to be HPV-dependent and/or deregulated in cervical cancer ( S2 Dataset ) . Out of these 483 miRNAs , 201 were identified in more than one study , but showed substantial discordance with more than half of them ( 105 miRNAs ) being regulated in opposite directions in different reports ( S2 Dataset , S5 Table ) . Importantly , however , none of these experimental approaches have addressed the question whether the actual cellular miRNA composition of HPV-positive cancer cells depends on endogenous E6/E7 expression . This is a critical issue since E6/E7 expression levels are tightly controlled in HPV-positive cancer cells and it is not clear how this relates to the E6/E7 levels obtained , for example , by ectopic E6/E7 expression in keratinocytes . Furthermore , HPV-induced cell transformation requires additional alterations in the host cell , besides viral E6/E7 expression . Thus , it is crucial to investigate the E6/E7-dependence of the cellular miRNA network by analyzing the effects of endogenous E6/E7 expression levels , within the cellular background of HPV-transformed cervical cancer cells , in which the sustained E6/E7 expression leads to the relevant cellular phenotype ( maintenance of cell growth ) . For these analyses , we chose HPV18-positive HeLa cells as a model for several considerations: ( i ) as common for HPV-positive cervical cancer cells , HeLa cells express the viral oncogenes from chromosomally integrated HPV copies , using the authentic E6/E7 transcriptional promoter . ( ii ) HeLa cells mirror known critical mechanisms of HPV-linked carcinogenesis , such as inactivation of the p53 and pRb tumor suppressor proteins by the HPV E6 and E7 proteins , respectively . ( iii ) The growth of HeLa cells is strictly dependent on viral E6/E7 expression [8 , 13 , 73 , 75 , 76] as is the case for primary cervical cancer cells freshly isolated from human tumor samples [74] . ( iv ) E6/E7 silencing in HeLa cells results in the same phenotype as in primary cervical cancer cells , namely growth arrest and induction of cellular senescence [12–14 , 74 , 77] . ( v ) HeLa cells allow functional analyses within the intracellular milieu of an HPV-transformed cancer cell , which has acquired the necessary additional cellular alterations that are required for HPV-induced cervical carcinogenesis . Likely , these are not present in “normal” keratinocytes , which only in very rare instances are transformed to malignancy by the HPV E6/E7 oncogenes alone [78] . ( vi ) A meta-analysis of mRNA transcriptome studies validated that RNAi-mediated silencing of endogenous E6/E7 expression in HeLa cells [79] is one of the most suitable experimental approaches to predict molecular changes present in cervical cancer tissues [80] . We determined ten abundant intracellular miRNAs as E6/E7-dependent , based on our most stringent selection criteria ( RPM values > 1 , 000; modulated > 1 . 5-fold upon E6/E7 silencing in both deep sequencing and—statistically significant—in qRT-PCR analyses ) . Analyses in “p53-null” HeLa cells indicate that eight of the ten miRNAs are modulated upon E6/E7 silencing in a p53-independent manner . These include miR-143–3p , the levels of which have been reported to be increased by p53 via enhanced post-transcriptional miRNA maturation [81] . However , our observation that miR-143–3p levels are very similarly regulated in parental and p53-deficient HeLa cells indicates that this mechanism is not responsible for the miR-143–3p increase upon endogenous E6/E7 silencing . We included the ten E6/E7-dependent miRNAs in S2 Dataset , resulting in a total number of 485 miRNAs identified in global miRNA expression analyses of cervical cancer biopsies and different in vitro cell culture models . Studies in cervical cancer biopsies reported alterations of six of the ten miRNAs that we identified here as being modulated by E6/E7 . Notably , five of these six miRNAs exhibit congruent changes between our functional experiments in vitro and their expression patterns in vivo in at least one study , i . e . reduction upon E6/E7 silencing in HeLa and upregulation in cervical cancer biopsies ( miR-7–5p [43] , miR-17–5p [27–30 , 34 , 37] , miR-186–5p [35] ) or increase upon E6/E7 silencing in HeLa and downregulation in cervical cancer tissue ( miR-23b-3p [28 , 37] and miR-143–3p [23 , 29 , 31 , 33 , 37 , 38 , 82] ) ( S2 Dataset ) . Only for miR-378a-3p , which was downregulated upon E6/E7 silencing , our in vitro data contrasts the reported downregulation of this miRNA in cervical cancer tissue [28 , 34] . This high concordance with in vivo data provides further strong evidence for the suitability of the functional approach used here to identify E6/E7-dependent miRNA alterations . Remarkably , multiple of the most abundant miRNAs found to be significantly affected by E6/E7 silencing in HPV-positive cancer cells are known to be involved in the regulation of cell proliferation , senescence and apoptosis . Specifically , continuous E6/E7 expression is necessary to maintain high intracellular levels of miR-7–5p , miR-629–5p , miR-378a-3p , miR378f , miR-17–5p , and miR-186–5p ( S2 Table ) , which all have been linked to pro-tumorigenic activities . For example , miR-7–5p stimulated cell proliferation and tumorigenicity in lung cancer cells [83] and is linked to a more aggressive growth behavior of breast cancers [84] . miR-629–5p also promotes cell growth , has been found to be important for hepatocarcinogenesis via HNF4a repression [85] , and targets the NBS1 DNA tumor susceptibility gene [86] . Reduced miR-7–5p or miR-629–5p levels have also been both associated with cellular senescence [87] . Several members of the miR-378 family were among the most frequently sequenced miRNAs that decreased upon E6/E7 silencing ( S2 Table ) . miR-378a-3p can block the tumor-suppressive Fus1 ( TUSC2 ) and SUFU genes , leading to increased cell survival and tumor growth [88] . No functional data is yet available for miR-378f [89] , however , it contains the same seed sequence as miR-378a-3p and therefore both miRNAs could regulate overlapping genes . miR-17–5p is discussed in more detail below . Finally , miR-186–5p is an inhibitor of the FOXO1 tumor suppressor gene , which can exert anti-proliferative , pro-apoptotic and pro-senescent activities [90 , 91] . On the other hand , continuous E6/E7 expression is linked to a decrease of the intracellular concentrations of miR-23a-3p , miR-23b-3p , miR-27b-3p , and miR-143–3p . The E6/E7-dependent reduction of miR-23a-3p is surprising since this miRNA often is elevated in cancers , suggesting that it acts pro-tumorigenic [92] . However , miR-23a-3p possesses pro-senescent potential [93 , 94] and has also been linked to apoptosis induction [92] , indicating that miR-23a-3p can exert context-dependent pro- or anti-tumorigenic activities . miR-23b and miR-27b belong to the miR-23b-27b-24–1 cluster and both exhibit anti-tumorigenic activities [95 , 96] . Finally , among the 52 most commonly sequenced miRNAs , miR-143–3p represents the most strongly activated miRNA after E6/E7 silencing . It acts anti-proliferative [97] , including in cervical cancer cell lines [34] , and an increase of miR-143–3p levels has been linked to senescence [97] . It is also remarkable that three of the four abundant miRNAs that are significantly decreased by sustained E6/E7 expression are associated with the metabolic alterations typical for cancer cells . Specifically , lowered levels of miR-23a-3p and miR-23b-3p have been linked to enhanced glutamine catabolism [98] and a decrease of miR-143–3p favors glucose metabolism by aerobic glycolysis ( Warburg effect ) [99] . The identification of cellular miRNAs in the present work that are dependent on sustained endogenous E6/E7 expression forms a basis for future functional studies . Here , we took a closer look at members of the tumorigenic miR-17~92 cluster , since ( i ) miR-17–5p was among the top ten hits of abundant miRNAs of which the expression was maintained by the E6/E7 oncogenes , ( ii ) all other members of this cluster , as well as of the paralog cluster miR-106b~25 , were also downregulated by E6/E7 silencing when applying less stringent selection criteria ( S3 Table ) , ( iii ) several members of the miR-17~92 cluster are well-decumented to be overexpressed in cervical cancer tissues , including the tested miR-17–5p [27–30 , 34 , 37] and miR-20a-5p [23 , 30 , 31 , 34 , 35] ( also see S2 Dataset ) , and ( iv ) four of these miRNAs ( miR-17–5p , miR-20a-5p , miR-93–5p , and miR-106b-5p ) possess the same seed sequence and can bind to the 3’ UTR of the p21 mRNA [18] . Our finding that the concomitant inhibition of p21 and E6/E7 expression led to an alleviation of the senescent phenotype , compared to cells in which only E6/E7 was repressed , supports the notion that p21 contributes to the induction of cellular senescence upon E6/E7 inhibition in HPV-positive cancer cells [13] . In view of the strong anti-proliferative and pro-senescent potential of p21 , it seems critical for the growth of HPV-positive tumor cells to block p21 function . Our findings that miR-17–5p and miR-20a-5p inhibitors significantly induced endogenous p21 protein levels , indicates that oncogenic HPVs reduce p21 expression in cervical cancer cells by increasing the intracellular concentrations of members of this miRNA seed family . This provides evidence for a third layer of negative regulation of p21 by the HPV oncogenes , in addition to interfering with p53-mediated transcriptional p21 activation via E6-mediated p53 degradation [100] and the inhibitory E7/p21 protein/protein interaction [101 , 102] ( Fig . 10 ) . Comparative analyses of the ten HPV18 E6/E7-dependent cellular miRNAs ( HeLa ) in HPV16-positive cells ( SiHa ) revealed a substantial overlap in their regulation patterns upon inhibition of endogenous E6/E7 expression . This is not necessarily expectable since the two cell lines are derived from a cervical adenocarcinoma and a squamous cell carcinoma , respectively , and the miRNA composition of tumor cells can substantially vary even for the same cancer form , dependent on the histological background or differentiation status [103 , 104] . Since HPV16 and HPV18 E6/E7 share most of their functions , the overlap in miRNA regulation across tumor cells of different histopathological origin provides further evidence for its E6/E7-dependence . The present work also represents the first study investigating global changes of the miRNA composition of exosomes released from HPV-positive cancer cells , in dependence on endogenous viral oncogene expression . Consistent with the view that exosomal sorting of miRNAs is a directed process [105] , the most commonly sequenced intracellular and exosomal miRNAs exhibited only a partial overlap . We also observed that E6/E7 silencing increases the percentage of exosomal miRNAs relative to other small RNA fractions , raising the possibility that the viral oncogenes affect exosomal sorting of small RNAs . Among the 47 most frequently sequenced exosomal miRNAs , 25 were modulated > 1 . 5-fold by silencing E6/E7 expression . Seven of those also exhibited statistical significance in the validating qRT-PCR analyses . Our results show that continuous E6/E7 expression is linked to an upregulation of let-7d-5p , miR-20a-5p , miR-378a-3p , miR-423–3p , miR-7–5p , miR-92a-3p and a downregulation of miR-21–5p , in exosomes secreted from HeLa cells . Interestingly , several of these miRNAs exert cancer-associated activities inside cells . Let-7d-5p belongs to the let-7 miRNA family , which is considered to primarily act tumor-suppressive [106] . However , specific analyses of the let-7d family member also indicate anti-apoptotic activity by targeting the 3’ UTR of caspase 3 [107] and a strong increase of let-7d-5p levels has been observed during progression of breast cancers [108] . The other five of the six abundant exosomal miRNAs that are maintained by continuous E6/E7 expression have been primarily linked to pro-tumorigenic activities . The pro-oncogenic potential of miR-7–5p and miR-378a-3p is discussed above . miR-20a-5p and miR-92a-3p are both members of the miR-17~92 cluster . miR-20a-5p can block oncogene-induced senescence via p21 repression [109] , whereas miR-92a-3p possesses anti-apoptotic potential [110] . miR-423–3p has been shown to promote G1/S transition and cell growth . On the other hand , miR-21–5p , which is considered to be pro-tumorigenic [111] , was the only miRNA among the 47 most frequently sequenced miRNA species in exosomes that was significantly upregulated > 1 . 5-fold upon E6/E7 silencing , indicating that continuous E6/E7 expression is associated with reduced exosomal miR-21–5p levels . Thus , taken together , with the exception of miR-21–5p , sustained E6/E7 expression in HPV-positive cancer cells is linked to exosomal miRNA alterations that possess known pro-proliferative or anti-apoptotic potential . These findings complement results indicating that endogenous E6/E7 expression in HPV-positive cancer cells is also linked to exosomal protein alterations with growth promoting and anti-apoptotic potential , e . g . upregulation of Survivin [77] . Comparative analyses of the seven miRNAs in exosomes secreted by HPV16-positive SiHa cells revealed a substantial overlap in their modulation upon endogenous E6/E7 silencing . Thus , as observed for intracellular miRNAs , there is a similar regulation of E6/E7-dependent miRNAs in exosomes secreted by tumor cells that contain different HPV types and that are of different histological origin . Our observations concerning exosomal miRNA contents could be relevant for intercellular communication in that HPV-positive cells might convey a tumor-promoting message to surrounding cells via exosomes , as has been reported for two of the E6/E7-dependent exosomal miRNAs , miR-92a-3p [55] and miR-378a-3p [52] . Of note , however , studies on the intercellular communication via exosomes have to critically consider technical limitations that are still unresolved . Despite an increasing number of examples showing that an intercellular crosstalk via exosomal miRNAs is possible in cell culture , the physiological significance of these observations is often uncertain [47 , 112] . Specifically , most studies utilized concentrated exosome preparations and it is not clear how these experimental conditions relate to exosome concentrations in the physiological context [113] which are very low in biological fluids ( within 100 fM range ) . This might be below the threshold for exerting significant physiological effects in vivo [114 , 115] since it has been estimated that miRNAs require intracellular levels of greater than 1 , 000 copies per cell to trigger measurable activity on their mRNA targets [115] . These questions could be addressed once experimental systems to test the physiological relevance of exosomes become available , which is a topic of intense ongoing research in the exosome field [47 , 112] . The identification of an E6/E7-dependent miRNA signature in exosomes may also bear diagnostic potential . Circulating miRNAs are currently intensively investigated as new , minimally invasive biomarkers for early diagnosis , prognosis and prediction of response to specific therapies [116 , 117] . A significant source of miRNAs in extracellular fluids , like serum or saliva , are exosomes [118] . Major advantages of using exosomal miRNAs as biomarkers include their high stability and the possibility to increase the sensitivity of miRNA amplification from human biologic fluids by exosome isolation and enrichment [71 , 118] . It thus will be interesting to investigate whether the E6/E7-dependent miRNA changes identified here are mirrored in exosomes isolated from body fluids of patients suffering from HPV-linked diseases , such as in the serum , cervical lavages of cervical cancer patients or saliva of head and neck cancer patients . Taken together , this study shows that the endogenous E6/E7 expression in HPV-positive cancer cells is linked to increased concentrations of multiple pro-proliferative , anti-senescent and anti-apoptotic miRNAs , while the amounts of anti-proliferative , pro-senescent and pro-apoptotic miRNAs are reduced . This applies to abundant miRNA species both inside the cell and in exosomes . These findings imply that the viral E6/E7 oncogenes affect the growth of HPV-positive cancer cells by manipulating the intracellular and exosomal miRNA compositions . It will be interesting for future studies to further decipher the role of these miRNAs for the proliferation and survival of HPV-positive cancer cells . Moreover , since therapeutic agents acting on the miRNA level are now entering the clinic [117 , 119] and since therapeutically useful E6/E7 inhibitors are still not available , it will be important to evaluate whether a correction of the E6/E7-dependent miRNA alterations by miRNA mimics or inhibitors possesses therapeutic potential for the treatment of HPV-linked premalignant and malignant lesions .
HPV18-positive HeLa ( obtained from the tumor bank of the German Cancer Research Center , Heidelberg ) and HPV16-positive SiHa cervical carcinoma cells ( obtained from the American Tissue Culture Collection , ATCC ) were cultured in DMEM ( Gibco , Life Technologies , Carlsbad , CA , USA ) containing 5% fetal bovine serum ( Gibco , Life Technologies ) , 2 mM L-glutamine , 100 U/ml penicillin , 100 μg/ml streptomycin ( Sigma-Aldrich , Saint Louis , MO , USA ) . “p53-null” HeLa cells were described in detail in ref . [65] . Synthetic siRNAs ( Ambion , Life Technologies , Carlsbad , CA , USA ) were transfected with DharmaFECT I ( Thermo Fisher Scientific , Waltham , MA , USA ) , according to the manufacturer’s instructions , to reach a final siRNA concentration of 10 nM . For silencing viral HPV18 or HPV16 E6/E7 oncogene expression , three different siRNAs , which each target all three HPV E6/E7 transcript classes , were generated [8] . To minimize potential off-target effects [120 , 121] the three siRNAs were pooled at equimolar concentrations ( referred to in the text as “si18E6/E7” or “si16E6/E7” , respectively ) . The siRNA target sequences were as follows: HPV18 E6/E7–1 5’-CCACAACGUCACACAAUGU-3’; HPV18 E6/E7–2 5’-CAGAGAAACACAAGUAUAA-3’; HPV18 E6/E7–3 5’-UCCAGCAGCUGUUUCUGAA-3’ , HPV16 E6/E7–1 5’-CCGGACAGAGCCCAUUACA-3’; HPV16 E6/E7–2 5’- CACCUACAUUGCAUGAAUA-3’; HPV16 E6/E7–3 5’- CAACUGAUCUCUACUGUUA-3’; p21 ( CDKN1A ) 5’-CAAGGAGUCAGACAUUUUA-3’ . Control siRNA “siContr-1” , 5′-CAGUCGCGUUUGCGACUGG-3′ , contains at least four mismatches to all known human genes . miRNA Inhibitors ( Qiagen , Hilden , Germany ) and the miScript Inhibitor Negative Control ( Qiagen ) were transfected with DharmaFECT I ( Thermo Fisher Scientific ) , according to the manufacturer’s instructions , to reach a final concentration of 100 nM for miRNA inhibitors . Plasmids were transfected by calcium phosphate co-precipitation as described by Chen and Okayama [122] . The plasmid expressing the mir-17~92 cluster ( pcDNA3 . 1/V5-His-TOPO-mir17~92 , [123] ) was a gift from Joshua Mendell ( Addgene plasmid # 21109 ) and the pcDNA3 . 1 empty vector ( Life Technologies ) was used as negative control . For cell cycle analysis , cells were trypsinized 72 h after transfection , washed in ice-cold PBS and fixed in 80% cold ethanol overnight at -20°C . Subsequently cells were pelleted , resuspended in phosphate buffered saline ( PBS , 137 mM NaCl , 2 . 7 mM KCl , 4 . 3 mM Na2HPO4 , 1 . 4 mM KH2PO4 , pH 7 . 4 ) containing 1 mg/ml RNase A ( Roche Diagnostics ) and 25 μg/ml propidium iodide ( Sigma-Aldrich ) and incubated for 30 min at room temperature ( RT ) . Cell cycle analyses were performed by fluorescence-activated cell sorting ( FACS ) using a FACSCalibur Flow Cytometer ( BD Biosciences , Heidelberg , Germany ) with CellQuest Pro software provided by the manufacturer . Quantitation of the percentage of cells in the individual phases was performed using FlowJo software ( Tree Star , Ashland , OR , USA ) , applying the Dean-Jett-Fox model [124] . HeLa cells were plated on glass cover slips , followed by transfection with siRNAs , as described above . Staining for senescence-associated β-galactosidase ( SA-β-Gal ) activity was performed 168 h after transfection , as described by Dimri et al . [125] . For exosome production cells were plated on 15 cm dishes to reach 80% confluence 72 h post transfection . Forty-eight h post transfection the cells were washed with DMEM and cultured for 24 h in “vesicle-depleted medium” ( complete medium depleted of FBS-derived microvesicles by overnight centrifugation at 100 , 000 g ) . The conditioned medium was collected and cleared from intact cells and cellular debris by three rounds of centrifugation at 300 g , 3 , 000 g , and 10 , 000 g for 20 min . Subsequently , exosomes were pelleted from the resulting supernatant by ultracentrifugation at 100 , 000 g for 70 min using a SW28 rotor ( Beckman Coulter , Fullerton , CA , USA ) , resuspended in 36 ml PBS , and re-centrifuged at 100 , 000 g for 70 min . All centrifugation steps were performed at 4°C . The final pellet was resuspended in 100 μl PBS and an aliquot was analyzed by electron microscopy . For each preparation , the total protein concentration was quantified using the Qubit Protein Assay ( Life Technologies ) . The corresponding exosome-producing cells were harvested and pelleted by centrifugation at 800 g for 3 min , resuspended and washed in 800 μl PBS , and re-pelleted . Cell pellets were lysed in RIPA buffer ( 10 mM Tris ( pH 7 . 5 ) , 150 mM NaCl , 1 mM EDTA , 1% Nonidet P40 , 0 . 5% Na-Deoxycholat , 0 . 1% SDS , supplemented with 25 μl/ml Pefabloc ( Merck , Whitehouse Station , NJ , USA ) and 10 μl/ml of Protease Inhibitor Cocktail ( Sigma-Aldrich ) ) for 30 min on ice and proteins were collected by centrifugation at 12 , 000 g for 15 min . Protein concentrations were determined using the Bio-Rad Protein Assay ( Bio-Rad , Hercules , CA , USA ) , employing bovine serum albumin as standard . For Western blot analysis , protein extracts and exosome samples were boiled in SDS sample buffer ( for reducing conditions: 8% SDS , 250 mM Tris-HCL ( pH 6 . 8 ) , 20% β-mercaptoethanol , 40% glycerol , 0 . 008% bromphenol blue; for non-reducing conditions without β-mercaptoethanol ) for 5 min at 95°C and separated on NuPAGE Novex 4–12% Bis-Tris Mini Gels ( Life Technologies ) . Proteins were electrotransferred onto an Immobilon-P membrane ( Millipore , Bedford , MA , USA ) using the Trans-Blot Semi-Dry Transfer Cell ( Bio-Rad ) . Membranes were blocked with 5% skim milk powder ( Saliter , Obergünzburg , Germany ) in PBS-T ( PBS supplemented with 0 . 1% Tween-20 ) for 1 h at RT . Membranes were probed with primary antibodies over night at 4°C in PBS-T , followed by incubation with the respective HRP-conjugated secondary antibody in PBS-T for 1 h at RT . Proteins were visualized using the ECL Prime Western Blotting Detection Reagent ( GE Healthcare , Buckinghamshire , UK ) . Images were acquired using the Fusion SL Gel Detection System ( Vilber Lourmat , Marne-la-Vallée , France ) , band densities were determined by BioID image analysis software ( Vilber Lourmat ) . The following primary antibodies were used: mouse anti-α-Tubulin ( Merck ) , CP06 , dilution 1:5 , 000; mouse anti-β-Actin ( Sigma-Aldrich ) , A2228 , 1:10 , 000; mouse anti-Annexin 1 ( BD Transduction , Heidelberg , Germany ) , #610066 , 1:10 , 000; mouse anti-CD63 ( Santa Cruz Biotechnology , Santa Cruz , CA , USA ) , sc-5275 , 1:400 at non-reducing conditions; mouse anti-CD9 ( BD Pharmingen , San Diego , Ca , USA ) , #555370 , 1:200 at non-reducing conditions; mouse anti-GRP78 ( BD Transduction ) , #610979 , 1:1 , 000; chicken anti-HPV18 E7 ( E7C ) [126]; mouse anti-HPV18 E6 ( Arbor Vita Corporation Sunnyvale , CA , USA ) AVC #399; mouse anti-HPV16 E7 ( NM2 , kind gift of Dr . Martin Müller , German Cancer Research Center , Heidelberg , Germany ) ; mouse anti-HPV16 E6 ( Arbor Vita Corporation Sunnyvale , CA , USA ) AVC #843; rat anti-Hsc70 ( Stressgen , San Diego , CA , USA ) , ADI-SPA-815 , 1:1 , 000; mouse anti-p53 ( BD Pharmingen ) , #554293 , 1:500; mouse anti-EEA1 ( BD Transduction Laboratories ) , #E41120 , 1:2 , 000; mouse anti-pRb ( Cell Signaling ) , #9309 , 1:1 , 000; rabbit anti-phospho ( Ser807/811 ) -pRb ( Cell Signaling ) , #9308 , 1:1 , 000; rabbit anti-CyclinA1 ( Santa Cruz Biotechnology ) , 1:2 , 000 . The following HRP-conjugated secondary antibodies were applied: anti-mouse IgG ( Promega , Madison , WI , USA ) , W4021 , 1:5 , 000; anti-chicken IgY ( Promega ) , G1351 , 1:2 , 500; anti-rat IgG ( Dianova , Hamburg , Germany ) , #112035003 , 1:5 , 000; and anti-goat IgG ( Promega ) , V8051 , 1:3 , 000 . Purified exosomes ( 6 μl , corresponding to 1 to 4 μg protein , depending on the experiment ) were layered onto carbon-coated copper grids ( 300 mesh , Plano , Wetzlar , Germany ) and allowed to dry at RT . Grids were then washed with water for 5 min and stained with 2% uranyl acetate in water ( Polysciences , Warrington , PA , USA ) for 30 sec to 1 min . Imaging was performed at an acceleration voltage of 80 kV with the EM10 Electron Microscope ( Zeiss , Oberkochen , Germany ) . Total cellular RNA , including miRNA , was isolated with the miRNeasy Mini Kit ( Qiagen ) following the manufacturer’s protocol . All optional washing steps were included and RNA was eluted in a final volume of 30 μl RNase-free water . Total exosomal RNA , including miRNA , was isolated using the protocol described for cells with slight modifications: Exosome samples were pre-treated with 100 ng/μl RNAse A ( Roche ) for 30 min at 37°C , immediately before extracting RNA . Prior to the addition of chloroform and phase separation , 12 μg glycogen from Mytilus edulis ( Sigma ) were added to the sample . RNA concentrations were measured with the NanoDrop ND-1000 at 260 nm . RNA quality was assessed with the Agilent 2100 Bioanalyzer ( Agilent Technologies , Böblingen , Germany ) using the Agilent RNA 6000 Pico Kit ( total RNA ) and the Agilent Small RNA Kit ( small RNA ) . The 2100 Bioanalyzer Expert Software B . 02 . 08 . ( Agilent ) was applied to generate electropherograms . RNA samples were stored at -80°C until further analysis . For mRNA analysis , reverse transcription of 1 μg total RNA was carried out with the ProtoScript First Strand cDNA Synthesis Kit ( NEB ) according to the manufacturer’s instructions , using oligo-dT primers in an end volume of 20 μl . To assess for genomic DNA contamination of the sample , a no reverse transcriptase control ( RT- ) was prepared for each experiment by replacing the M-MuLV Enzyme Mix with RNase-free H2O . qRT-PCR reactions were performed with the SYBR Green PCR Master Mix ( Applied Biosystems ) and a final primer concentration of 500 nM on a 7300 Real-Time PCR System Detector ( Applied Biosystems ) . Two μl of a 1:5 dilution of the original cDNA were used for each reaction and samples were run in triplicate for each experiment . A no template control ( NTC ) to monitor contamination of the reagents was included for each primer pair by adding H2O instead of cDNA template . The forward ( fwd ) and reverse ( rev ) primer sequences ( Eurofins MWG , Ebersberg , Germany ) used for determining mRNA expression levels were as follows: HPV18 E6/E7 fwd 5’-ATGCATGGACCTAAGGCAAC-3’ , HPV18 E6/E7 rev 5’-AGGTCGTCTGCTGAGCTTTC-3’ , HPV16 E6/E7 fwd 5’-CAATGTTTCAGGACCCACAGG-3’ , HPV16 E6/E7 rev 5’-CTCACGTCGCAGTAACTGTTG-3’ , p21 ( CDKN1A ) fwd 5’-GACCATGTGGACCTGTCACT-3’ , p21 ( CDKN1A ) rev 5’-GCGGATTAGGGCTTCCTCTT-3’ , ACTB fwd 5’-AGACAGTATACCCCATGCTGCAT-3’ , ACTB rev 5’-TCCAATGTGTCTCCATACACAGA-3’ . Cycling conditions have been previously described [127] . The sizes of the PCR products were initially analyzed by agarose gel electrophoresis and subsequently checked by melting point analysis after each reaction using the 7300 System SDS Software ( Applied Biosystems ) . Cycle thresholds ( Ct ) were normalized to the Cts of ACTB using the comparative Ct ( 2-ΔΔCt ) method [128] . Fold enrichments were calculated as compared to the values from the mock control . miRNA expression was detected using the miScript PCR System ( Qiagen ) with miRNA specific primers according to the manufacturer’s instructions . Briefly , 1 μg cellular RNA was converted to cDNA using the miScript II Reverse Transcription Kit ( Qiagen ) in a reaction volume of 20 μl using 5x miScript HiFlex Buffer . Due to the low yield of exosomal RNA and consequently the lack of accurate RNA quantification , identical volumes of exosomal RNA ( 12 μl ) were used for cDNA synthesis . An RT- control was prepared for each experiment . qRT-PCR reactions were performed with the miScript SYBR Green PCR Kit ( Qiagen ) on a 7300 Real-Time PCR System Detector ( Applied Biosystems ) using Qiagen’s recommended cycling conditions . Two μl of a 1:100 dilution of the original cDNA were used for each reaction and samples were run in triplicate for each experiment . To monitor contamination of the reagents , an NTC was included for each primer pair . Data were analyzed using the comparative Ct ( 2-ΔΔCt ) method [128] with the small nuclear RNA RNU6–2 as endogenous control for cellular samples and respective mock- or control-treated samples ( as indicated ) as reference . Normalization of exosomal samples was conducted against an average of the expression of miR-452–5p and miR-183–5p . These two miRNAs were chosen as endogenous exosomal miRNAs for normalization since they were among the most frequently sequenced exosomal miRNAs in HeLa cells ( > 1 , 000 RPM in each sample ) and showed virtually no regulation in exosomes upon silencing of HPV18 E6/E7 versus control treatment based on the deep sequencing data ( miR-452–5p: FCmean = 0 . 99 , miR-183–5p: FCmean = 1 . 04 ) . miRNAs with Ct values > 35 were below detection limit and excluded from analysis . The following miScript Primer Assays ( Qiagen ) were applied: Hs_let-7a_2 ( hsa-let-7a-5p ) , Hs_let-7d_1 ( hsa-let-7d-5p ) , Hs_let-7f_1 ( hsa-let-7f-5p ) , Hs_let-7g_2 ( hsa-let-7g-5p ) , Hs_miR-100_2 ( hsa-miR-100–5p ) , Hs_miR-103a_1 ( hsa-miR-103a-3p ) , Hs_miR-106b_1 ( hsa-miR-106b-5p ) , Hs_miR-1246_2 ( hsa-miR-1246 ) , Hs_miR-125a_1 ( hsa-miR-125a-5p ) , Hs_miR-128_1 ( hsa-miR-128 ) , Hs_miR-1307_1 ( hsa-miR-1307–3p ) , Hs_miR-143_1 ( hsa-miR-143–3p ) , Hs_miR-17_2 ( hsa-miR-17–5p ) , Hs_miR-181b_1 ( hsa-miR-181b-5p ) , Hs_miR-182_2 ( hsa-miR-182–5p ) , Hs_miR-183_2 ( hsa-miR-183–5p ) , Hs_miR-186_1 ( hsa-miR-186–5p ) , Hs_miR-191_1 ( hsa-miR-191–5p ) , Hs_miR-196a_2 ( hsa-miR-196a-5p ) , Hs_miR-19b_2 ( hsa-miR-19b-3p ) , Hs_miR-20a_1 ( hsa-miR-20a-5p ) , Hs_miR-21*_1 ( hsa-miR-21–3p ) , Hs_miR-21_2 ( hsa-miR-21–5p ) , Hs_miR-221_1 ( hsa-miR-221–3p ) , Hs_miR-222_2 ( hsa-miR-222–3p ) , Hs_miR-23a_2 ( hsa-miR-23a-3p ) , Hs_miR-23b_2 ( hsa-miR-23b-3p ) , Hs_miR-25_1 ( hsa-miR-25–3p ) , Hs_miR-25_1 ( hsa-miR-25–3p ) , Hs_miR-26a_2 ( hsa-miR-26a-5p ) , Hs_miR-27a_1 ( hsa-miR-27a-3p ) , Hs_miR-27a*_1 ( hsa-miR-27a-5p ) , Hs_miR-27b_2 ( hsa-miR-27b-3p ) , Hs_miR-30c_2 ( hsa-miR-30c-5p ) , Hs_miR-31_1 ( hsa-miR-31–5p ) , Hs_miR-320a_1 ( hsa-miR-320a ) , Hs_miR-320_2 ( hsa-miR-320b ) , Hs_miR-34a_1 ( hsa-miR-34a-5p ) , Hs_miR-422b_1 ( hsa-miR-378a-3p ) , Hs_miR-378c_1 ( hsa-miR-378c ) , Hs_miR-378d_1 ( hsa-miR-378d ) , Hs_miR-378f_1 ( hsa-miR-378f ) , Hs_miR-423_1 ( hsa-miR-423–3p ) , Hs_miR-452_4 ( hsa-miR-452–5p ) , Hs_miR-629_2 ( hsa-miR-629–5p ) , Hs_miR-7_2 ( hsa-mir-7–5p ) , Hs_miR-92_1 ( hsa-miR-92a-3p ) , Hs_miR-93_1 ( hsa-miR-93–5p ) , Hs_miR-98_1 ( hsa-miR-98 ) , Hs_miR-99a_2 ( hsa-miR-99a-5p ) , Hs_RNU6–2_1 ( RNU6–2 ) . All analyzed miRNAs are of human ( Homo sapiens ) origin and therefore the prefix “hsa” was omitted throughout the text . For each exosome sample , total RNA ( containing the small RNA fraction ) was extracted from one entire exosome preparation of 100 μl . Due to the low RNA yield , exosome samples were further concentrated to a volume of 6 μl using the RNeasy MinElute Cleanup Kit ( Qiagen ) . The entire volume of resulting 6 μl concentrated exosomal total RNA ( 100 to 600 ng ) was used as input for the library preparations . For cells , 1 μg total RNA in a volume of 6 μl was applied . Small RNA libraries were prepared using the NEBNext Multiplex Small RNA Library Prep Set for Illumina ( NEB , Frankfurt/M . , Germany ) with custom multiplex adaptors and primers ( NEBNext Multiplex Oligos for Illumina , Index Primers Set 1 ) . Essentially , all materials not included in the set were purchased as recommended and the manufacturer’s guidelines were followed with a few modifications . Briefly , the Multiplex 3’ Adaptor was ligated to the RNA at 25°C for 1 h . After hybridization of the Multiplex RT Primer , the Multiplex 5’ Adaptor was ligated to the RNA . Afterwards , reverse transcription was performed using the SuperScript III Reverse Transcriptase ( Life Technologies ) . The cDNA product was amplified by PCR using an optimized cycling protocol: initial denaturation for 3 min at 94°C , thirteen cycles of denaturation for 80 sec at 94°C , annealing for 30 sec at 62°C , extension for 15 sec at 70°C and final extension for 5 min at 70°C . Unique NEBNext Index Primers were applied for each of the six exosome samples ( Index 1–6 ) and the four cellular samples ( Index 1–4 ) . Amplicons corresponding to adapter-ligated constructs from 21–30 nt RNA fragments were purified on a 6% TBE polyacrylamide gel ( Life Technologies ) and eluted at RT for 3 h . The gel slurry was passed through a 5 μm filter tube ( IST Engineering , Milipitas , CA , USA ) and precipitated overnight at -80°C . The size , DNA concentration and quality of each final small RNA library was determined twice using the High Sensitivity DNA Kit ( Agilent ) with the BioAnalyzer 2100 . The concentration of each sample was adjusted to 10 nM and equal volumes of barcode-labeled samples were pooled for multiplexed sequencing in one lane . Sequencing ( 50 bp , single read ) was performed on an Illumina HiSeq 2000 instrument ( San Diego , CA ) . Raw sequencing reads were pre-processed and mapped using the function mapper . pl of the miRDeep2 package ( [129] , Max Delbrück Center , Berlin , Germany ) as described by Weischenfeldt et al . [130] . Briefly , low quality reads were filtered out , the adaptor sequence was clipped and reads shorter than 18 nt were discarded . Accepted reads were mapped to known human miRNAs based on miRBase v . 18 . 0 ( www . mirbase . org/; [131–134] ) using the function quantifier . pl in miRDeep2 . Since one mismatch was allowed during the mapping procedure , the raw read file of each further analyzed miRNA was manually checked to assure that the reads truly annotated to the respective miRNA . The obtained raw read counts of each sample were normalized by dividing with the total number of reads mapping to known human microRNAs for each sample . Values are expressed as reads per million ( RPM ) . Fold changes ( FCs ) were obtained by dividing the RPM of the si18E6/E7-treatment by the respective value of the siContr-1-treatment . Genome mapping was performed on the pre-processed reads with miRDeep2 allowing two mismatches and up to five mapped positions in the genome . Read counts were obtained using python script rpkmforgenes . py ( http://sandberg . cmb . ki . se/media/data/rnaseq/rpkmforgenes . py ) applied to aligned data along with two major annotation sources: Gencode v . 15 ( http://www . gencodegenes . org/releases/15 . html ) for snoRNA; and RepeatMasker track ( http://www . repeatmasker . org/ ) for scRNA , tRNA and snRNA . Statistical significance of the data was evaluated by the paired Student’s t-test using the Sigma Plot software ( Systat Software Inc . , San Jose , CA ) . P-values of p ≤ 0 . 05 ( * ) , p ≤ 0 . 01 ( ** ) , and p ≤ 0 . 001 ( *** ) were considered statistically significant . | Oncogenic human papillomaviruses ( HPVs ) are major human carcinogens of broad biomedical importance . The growth of HPV-positive cervical cancer cells is critically dependent on sustained E6/E7 oncogene expression from endogenous viral DNA sequences . We here addressed the question of whether this process is linked to specific , E6/E7-dependent alterations of the cellular micro ( mi ) RNA network . By comprehensive deep sequencing analyses we show that endogenous E6/E7 expression significantly affects the concentrations of abundant intracellular miRNAs in HPV-positive cervical cancer cells , which are linked to the control of cell proliferation , senescence and apoptosis . These include members of the miR-17~92 cluster , which are expressed at increased levels by sustained E6/E7 expression and repress the anti-proliferative p21 gene in HPV-positive cancer cells . Moreover , we identified an E6/E7-dependent seven-miRNA-signature in exosomes secreted from HPV-positive cancer cells . These small vesicles are involved in intercellular communication and may serve as novel diagnostic markers . Taken together , our results show that continuous E6/E7 expression in HPV-positive cancer cells is linked to significant alterations in the amounts of intracellular and exosomal miRNAs with growth-promoting , anti-senescent and anti-apoptotic potential . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Dependence of Intracellular and Exosomal microRNAs on Viral E6/E7 Oncogene Expression in HPV-positive Tumor Cells |
Drosophila Pumilio ( Pum ) protein is a translational regulator involved in embryonic patterning and germline development . Recent findings demonstrate that Pum also plays an important role in the nervous system , both at the neuromuscular junction ( NMJ ) and in long-term memory formation . In neurons , Pum appears to play a role in homeostatic control of excitability via down regulation of para , a voltage gated sodium channel , and may more generally modulate local protein synthesis in neurons via translational repression of eIF-4E . Aside from these , the biologically relevant targets of Pum in the nervous system remain largely unknown . We hypothesized that Pum might play a role in regulating the local translation underlying synapse-specific modifications during memory formation . To identify relevant translational targets , we used an informatics approach to predict Pum targets among mRNAs whose products have synaptic localization . We then used both in vitro binding and two in vivo assays to functionally confirm the fidelity of this informatics screening method . We find that Pum strongly and specifically binds to RNA sequences in the 3′UTR of four of the predicted target genes , demonstrating the validity of our method . We then demonstrate that one of these predicted target sequences , in the 3′UTR of discs large ( dlg1 ) , the Drosophila PSD95 ortholog , can functionally substitute for a canonical NRE ( Nanos response element ) in vivo in a heterologous functional assay . Finally , we show that the endogenous dlg1 mRNA can be regulated by Pumilio in a neuronal context , the adult mushroom bodies ( MB ) , which is an anatomical site of memory storage .
Drosophila melanogaster Pumilio ( Pum ) protein is one of the founding members of the PUF RNA-binding protein family . Its function in the posterior body patterning of Drosophila embryos is relatively well studied . Wharton and Struhl [1] first identified two copies of sequence elements located in the 3′ untranslated region ( 3′UTR ) of maternal hunchback ( hb ) mRNA , named Nanos Response Elements ( NREs ) , which are essential for normal abdominal segmentation . It was later shown that Pum binds these elements , recruits Nanos ( Nos ) and Brain Tumor ( Brat ) , and represses the translation of maternal hb mRNA [2] . Pum was also reported to temporally regulate the translation of Drosophila bicoid ( bcd ) mRNA , which plays a key role in anterior development [3] . In addition , Pum , acting together with Nos , is required for germline development in Drosophila embryos , and Cyclin B ( CycB ) mRNA appears to be a target of translational repression by this complex [4] , [5] . As a characteristic of the PUF family proteins , the minimal RNA-binding domain of Pum comprises eight imperfect repeats , is evolutionarily conserved across species from yeast to human [6] and , therefore , is termed the PUF domain or Pumilio Homology Domain ( Pum-HD ) . This RNA-binding domain appears to be sufficient for the function of Pum in vivo during Drosophila abdominal segmentation [7] . More recently , Pum has been found to play a role in the nervous system at the neuromuscular junction [8]–[11] , in voltage-gated Na+ current homeostasis in the CNS [9] and in long-term memory [12] . Dubnau et al . [12] employed the complementary “genomics” approaches of ( i ) a large-scale behavioral screen for mutants defective in one-day memory , and ( ii ) DNA microarray screening to identify genes in normal flies that are transcriptionally regulated during long-term memory formation . pum was found with both approaches: it is transcriptionally upregulated during memory formation after spaced training ( which results in long-term memory ) relative to massed training ( which results only in shorter forms of memory ) , and two independent transposon insertions into pum yielded mutants with defective one-day memory after spaced training . In addition to pum , six other components of a pathway putatively involved in local translational control were identified: staufen , orb ( CPEB ) , moesin and eIF-2G were transcriptionally regulated during memory formation , whereas transposon-mediated lesions were found in or near oskar ( norka mutant ) and eIF-5C ( krasavietz mutant ) . Local mRNA translation within dendrites of neurons has been proposed to be a mechanism for activity-dependent synaptic plasticity ( reviewed in [13] ) . We hypothesized that Pum might play a role in local translation involved in synapse-specific modifications during memory formation [12] . Consistent with this notion , Ye et al . [10] showed that Pum and Nos act together and play a critical role in the morphogenesis of high-order dendritic branches in Drosophila peripheral neurons , and that Nos colocalizes with RNA granules in dendrites . The role of Pum-dependent regulation in neurons also may be conserved [14] . Despite these genetic observations of Pum/Nos function in neurons , only a few neuronal targets of Pum have been demonstrated in vivo [8] , [9] . A large number of Pum-associated mRNAs have been recently identified from oocytes and early embryos [15] . These include a number of neuronally expressed genes whose in vivo relationship with Pum remains to be shown . As a complementary approach to screen for potentially relevant neuronal ( and in particular synaptic ) targets of Pum , we have used a combination of informatics and experimental approaches . Our first step to identify new Pum targets was to characterize and model the Pum binding sites . We then used our models to predict the presence of NREs in the 3′UTRs of mRNAs coding for synaptic proteins . We validated several of these by in vitro binding assays . We then used an established in vivo functional assay [1] to demonstrate Pum-dependent repression via the predicted NRE in the 3′UTR of dlg1 . Finally we demonstrated that transgenic over-expression of Pum is sufficient to reduce endogenous levels of Dlg protein in Kenyon cell neurons of the mushroom body .
We constructed three alternative models for Pum-binding sites , based on different assumptions . The first model is a simple consensus pattern , and the other two are based on positional weight matrices ( PWM ) [20] , [21] . The three alternative models of the NRE are shown in Figure 2 . NRE_PAT is a simple consensus of known NREs in hb and bcd , and translational control element ( TCE ) in CycB [22] . The conserved boxes in NREs suggest a pattern in which Box A precedes Box B . Both of the boxes may be important as previous studies suggested that Pum makes contact with both of them [2] , [6] , [7] . The distance between Box A and Box B in bcd of some fly species is one base longer than melanogaster , suggesting that the distance between the two boxes may be flexible . CycB TCE also contains short sequence segments like Box A and Box B and the distance between them is 23 bp . Therefore , we arbitrarily set the distance between 3 to 45 bases , to reduce the chance of missing some possible functional sites . NRE_M8 and NRE_M10 are frequency matrices generated by Gibbs Sampler ( see Materials and Methods ) . NRE_M8 is based on the assumption that both Box A and Box B may bind Pum . We used the recursive mode of Gibbs Sampler to require each sequence to contain two to three binding sites . In the output , the program actually picked two sites in each sequence . When we required a longer motif length , the information content at the additional position was very low . Therefore , we stopped at this motif with seven valid positions and one gap . NRE_M10 is based on the assumption that only Box B is important for Pum binding . This was derived from the data of the human Pum-RNA crystal structure [17] . We used the site sampler mode of the Gibbs program , which assumes that each sequence contains exactly one binding site . We picked the motif length 10 because this motif happened to cover Box B and four bases downstream , which contact Pum in the crystal structure . It is also worth noting that two of these four downstream bases are conserved across fly species in hb and bcd NREs ( Figure 1B ) . The predicted Pum targets among the 151 synaptic genes with the above three NRE models are listed in Tables S1 , S2 , S3 , respectively . With NRE_PAT , only five transcripts/genes are predicted . Among them , the pattern match is conserved between D . melanogaster and D . pseudoobscura in only one gene , dlg1 ( transcript isoforms A and D , which contain identical 3′UTRs ) . Conservation is unknown for two genes , AP-1 gamma and mam , because corresponding D . pseudoobscura 3′UTR sequences were not available at the time we initiated this study . Non-conserved predictions on CaMKII and EP2237 could be false positives . However , it is also possible that the 3′UTR sequences of those two genes are incomplete or inaccurate for D . pseudoobscura ( at the time we initiate this study ) , resulting in the failure to find conserved sites . With NRE_M8 , 31 transcripts ( 28 genes ) are predicted to be candidate Pum targets . Here , we require that a 3′UTR sequence must contain at least two high-score sites to be considered as a candidate Pum target . Among them , 10 transcripts ( 8 genes ) have at least two predicted sites that are conserved between the two fly species . With NRE_M10 , 28 transcripts ( 25 genes ) are predicted to be candidate Pum targets , among which 11 transcripts ( 9 genes ) have at least one conserved site . Notably , dlg1 gene is predicted to be a candidate Pum target all three NRE models . In addition , the target dlg1 has also been previously suggested as a potential Pum target based on its presence in a collection of 1434 Drosophila genes containing the motif UGUAHAUA [15] . Candidate memory genes from our previous studies [12] were sorted by their effect size ( i . e . , differential expression in microarray experiments ) . 12 transcripts ( 11 genes ) with predicted Pum binding sites were chosen for further testing based on their ranking in the candidate memory gene list and their relevance to memory and/or synaptic functions as annotated in FlyBase . Among those , we successfully obtained the 3′UTR sequence segments in 9 transcripts by PCR , to make templates for in vitro transcription . These target genes , their Pum-binding predictions , and the locations of tested 3′UTR segments are listed in Table 1 . Among these , the dlg1 gene has predicted Pum binding sites in the 3′UTR of two non-overlapping transcript isoforms ( also refer to Figure S4 ) . We next sought to determine the binding specificity of the predicted NRE-like elements . To this end , we carried out electrophoretic mobility shift assay ( EMSA ) using purified GST-Pum , which bears the RNA-binding domain of Drosophila Pum ( amino acids 1091–1533 ) fused with an N-terminal GST tag and has been shown to maintain the full binding activity of the wild-type Pum protein [6] , [7] . The second NRE element ( NRE2 ) of hb served as a positive control for Pum binding , whereas a random control RNA sequence , CRS that does not resemble an NRE-like element served as a negative control . Under the experimental conditions used , GST-Pum bound to hb NRE2 with high affinity , but did not bind to the control RNA sequence CRS , as shown in Figure 3A . In a parallel control experiment in which GST-Pum was substituted by GST alone , no protein–RNA complex between GST and hb NRE was formed , ruling out the possibility that the complex between GST-Pum and hb NRE was generated by non-specific binding of GST to RNA . We also note that , under our experimental conditions , only one complex was formed between GST-Pum and hb NRE as we increased the concentration of GST-Pum , consistent with the presence of a single Pum binding site in a single hb NRE ( Figure 3B ) . Next , we determined the binding specificity of the predicted NRE-like elements by EMSA . As shown in Figure 4A and 4B , Pum binds , albeit with different affinities , to all these predicted elements , except for dlg1 isoform C , which was not bound by Pum at all , even at a high molar ratio of protein to RNA . However , dlg1 transcript isoform C shares a different 3′UTR sequence from dlg1 transcript isoforms A and D . For the RNAs from hb NRE , dlg1 isoforms A and D , and AP-1 gamma , only one complex was formed upon binding of Pum . For the remaining RNAs , two or more complexes were formed , suggesting the existence of more than one Pum-binding site . To evaluate the relative binding affinities of these NRE-like elements , we quantified the EMSA results on a phosphorimager ( Table 1 ) . At the 5∶1 molar ratio of protein to RNA , 67 . 9% of hb NRE was bound by Pum . Under the same experimental condition , greater than 50% of the transcripts from dlg1 ( isoforms A and D ) , shn , Csp , and mam were bound by Pum , suggesting that NRE-like elements in these transcripts have strong Pum-binding activities comparable to hb NRE . On the other hand , at the same 5∶1 molar ratio of protein to RNA , transcripts from Ace , AP-1gamma , EP2237 , and Gad1 were largely unbound by Pum and showed weaker but substantial Pum-binding activities . We also tested Pum-binding activity of a 142-nt RNA fragment consisting of CycB TCE and flanking sequences ( nts 400–541 of 3′UTR of CycB mRNA ) and found that CycB TCE was able to bind to Pum with a much lower affinity compared to hb NRE ( Figure 4A , lanes 10–12 , and data not shown ) . As a validation of our PWM models , we calculated the correlation coefficient between the prediction scores and the binding affinities . The correlation for NRE_M10 is statistically significant ( cor = 0 . 67 , p = 0 . 017 ) whereas the correlation for NRE_M8 is weaker and not statistically significant ( see Figure S1 for details ) . This suggests that NRE_M10 is more accurate than NRE_M8 , supporting the assumption behind NRE_M10 , i . e . , only Box B is important for Pum binding . While the validity of our model is also supported by our in vitro binding experiments , we decided to use an in vivo assay to validate our target prediction method for a few of the putative targets . Because we were interested in targets with potential relevance to behavioral plasticity , we decided first to quantify transcript levels for each candidate in response to behavioral training that induces long-term memory . Expression profiling after experience-dependent memory formation indicated that the regulatory pathway for local translation ( including Pum ) is transcriptionally induced by spaced training [12] . Thus we reasoned that mRNA levels of some of Pum targets might also be regulated . Using quantitative ( real time ) PCR ( QPCR ) , we measured expression levels after spaced versus massed training for each of the putative Pum targets that showed robust binding in vitro . Two of them , Ace and dlg1 , were significantly induced 6 hours after spaced training ( fold change = 1 . 58 , N = 8 , p = 0 . 0036 for Ace; fold change = 1 . 56 , N = 8 , p = 0 . 0068 for dlg1 ) . While we do not understand why transcriptional responses for Pum's targets are in the same direction as that of Pum , this may reflect global transcriptional increases versus local translational repression ( see Discussion ) . These two candidate target genes were chosen for in vivo assays . To validate our target prediction method in vivo , we chose to use a Pum response assay described previously [1] . This assay relies upon the requirement that maternally supplied hb mRNA be repressed by Pum/Nos in posterior regions of the early embryo . We started with a canonical genomic hb rescuing transgene in which the endogenous NRE motifs were deleted . In the absence of functional NRE elements , this construct causes a dominant sterility in transgenic females due to ectopic hb translation in the posterior half of the embryos produced . Such embryos are unable to form abdominal segments . Insertion of a functional NRE motif into this canonical construct restores Pum-mediated repression in the posterior , allowing production of viable progeny . Using this strategy , we tested the functional capacity of the predicted NRE motifs from Ace and dlg1 . We chose these two putative targets because they showed relatively strong in vitro binding and also because both transcripts are induced by spaced training . We generated a series of hb-transgene constructs ( Figure 5 and Table S4 ) in which the two endogenous hb NREs had either been deleted entirely ( hbΔ ) , replaced with a single hb NRE , NRE2 ( hb2 ) , had both hb NRE elements re-inserted ( hb1 , 2 ) , replaced with putative NRE elements from Ace or dlg1 genes ( Ace or dlg1 ) , or replaced with an anti-sense version of the predicted dlg1 NRE ( dlg1-anti ) . We found that the predicted NRE from dlg1 is sufficient to partially restore abdominal patterning when compared with hb1 , 2 ( Figure 5A and 5B ) , which provided full rescue as in Wharton and Struhl [1] . It is worth noting that the rescue observed with the single dlg1 NRE is superior to that observed with a single copy of the hb NRE ( Figure 5A and 5B ) . Consistent with a previous observation by Wharton and Struhl [1] , a single hb NRE ( hb2 ) yields partial rescue . In contrast , control transgenic lines in which no functional NRE was provided , or in which the dlg1 NRE was inserted in opposite orientation ( dlg1-anti ) generate progeny nearly devoid of abdominal segments ( Figures 5A and 6B , and Table S4 ) . It is also worth mentioning that we failed to observe a rescue of normal abdominal segmentation when using another hb-transgene construct ( dlg1-full ) , in which the two endogenous hb NREs are replaced by a longer version of the transcript , a 1 . 2-kb sequence including the predicted NRE element from the 2 . 8-kb sequence of dlg1 3′UTR ( Table S4 ) . The lack of rescue with this construct may be caused by the artificial context of the transcript resulting from insertion of such a large heterologous fragment into the hb 3′UTR . We also failed to observe any rescue when using a hb-transgene construct in which hb NREs were replaced with putative NRE elements from Ace , indicating Ace might not function as a Pum target in an in vivo context despite positive results in computational search and biochemical validation . The above data support the conclusion that the dlg1 mRNA contains a Pum binding site that can confer translational repression to a heterologous reporter system in the embryo . We next sought to test whether the endogenous dlg1 mRNA can be regulated by Pumilio in a relevant neuronal context . Because of our interest in olfactory memory , we chose to test for Pum-mediated regulation of Dlg in the adult mushroom body ( MB ) , which is an anatomical site of memory storage [23]–[25] . We first used a monoclonal antibody against Dlg to examine the distribution of Dlg protein in brains of wild-type animals . Consistent with Ruiz-Canada et al . [26] , we found that Dlg is widely distributed in the adult brain , with elevated levels in antenna lobes ( AL ) and mushroom bodies ( Figure 6A ) . We then tested whether transgenic over-expression of Pum in MB was sufficient to reduce the endogenous Dlg expression . To do this , we used a MB Gal4 enhancer trap line OK107 [27] to drive the expression of both UAS-mCD8::GFP and UAS-Pumilio transgenes in the same brain . The GFP expression permitted independent visualization of the MB neuronal architecture and also served as an internal control for the distribution of Dlg . Our imaging studies support two conclusions . First , we found that transgenic expression of Pum in MB Kenyon cells results in a dramatic reduction of Dlg expression levels . Importantly Dlg expression in AL appears unaffected ( Figure 6A ) . In addition , the GFP expression in MB neurons appears at normal levels . This observation strongly supports the hypothesis that endogenous Dlg expression can be repressed by Pum in the CNS . Second , we also noticed that transgenic over-expression of Pum causes a severe defect in the elaboration of the axonal projections of MB neurons . This is evident in the expression of UAS-mCD8::GFP , which permits visualization of the entire MB neuronal architecture . In wild type animals , MB Kenyon cell axons dive ventrally and anteriorly along the peduncle . They then bifurcate into distinct vertical ( α and α′ ) and horizontal ( β , β′ and γ ) lobes , which contain the axon terminals . In contrast , the MBs of Pum over-expressing animals do not form normal lobe structures . Instead , the axons appear to prematurely terminate just medial to the peduncle . The above observation suggests the interesting possibility that Pum normally plays a key developmental role in elaboration of MB structure . While we cannot rule out neo-morphic effects of Pum over-expression , these findings nevertheless are consistent with the previous observations of Pum's role in dendrite morphology [10] . At the same time , however , we were concerned that the decreased accumulation of Dlg protein that we observed with Pum over-expression could be an indirect consequence of the MB structural defects . We used several strategies to rule this out . First , we made careful observation of Dlg expression levels in the peduncle in both wild type control and Pum over-expressing brains ( Figure 6A ) . Unlike the lobes , which are largely absent from these animals , the peduncle is intact . GFP expression in the peduncle was used as a reference . Second , we used a monoclonal antibody against FasII , which like Dlg , is expressed at elevated levels in MB Kenyon cell neurons ( although mostly α/β ) . This permitted a second independent means to image the MB of the same animals and also provided expression of a second endogenous protein as a control . Both of these experiments support the conclusion that Dlg expression per se is reduced in Pum over-expressing animals because both GFP and FasII protein levels are un-altered in the residual lobes and in the peduncle ( Figure 6B and Figure 7 ) . Finally , we used several additional MB expressing Gal4 drivers to confirm the key observation that ectopic Pum can down regulate Dlg ( see Figure 6 legend; data not shown ) . The magnitude of the effects on Dlg expression varied depending on expression levels , timing and number/type of MB neurons labeled . Nevertheless , we observed decreased Dlg immuno-labeling both with MB Gal4 line C739 and 238Y ( Figure 6 legend and data not shown ) .
The bioinformatic prediction of mRNA targets for sequence-specific RNA binding proteins continues to be a significant challenge . In most cases , biologically relevant motifs are hard to define , in part due to the unknown impact of secondary structure . This is confounded by the fact that in vivo assays to validate predictions are often not trivial . One approach to identify targets is to use genome-wide detection of mRNAs that directly associate with an RNA-binding protein . This approach was used with success [15] to identify putative Pum-associated mRNAs from ovaries and early embryos . In this study , we have taken a different approach to identify neuronal targets that might underlie Pum's role in memory . We took advantage of: ( 1 ) the availability of well characterized structural and functional information about Pum-HD:RNA interactions; ( 2 ) several conserved NRE elements that had been described for the hb and bcd genes; ( 3 ) the availability of a robust in vivo functional assay [1] , and ( 4 ) in vivo imaging of one target gene's expression to validate our predictions . We have identified a group of putative neuronal targets of Pum , including dlg1 and Ace , both of which are also induced during memory consolidation . In the case of dlg1 , the identified NRE appears capable of functioning both in a heterologous in vivo context of the early embryo and an endogenous one in the adult brain ( Figures 5 and 6 ) . Our results also suggest that the binding specificity of Pum is conserved between Drosophila and mammals , as previously noted in Wang et al . [17] , which is consistent with the observations that human Pum2 binds to the Drosophila NRE sequence [28] , [29] . First , NRE_M10 , which is based on assumptions derived from the human Pum-RNA crystal structure , performed best among the three motif models constructed with known Pum targets in flies . Second , a motif derived from mouse PUM2 SELEX data , MmSelex_M8 ( “Conservation of Pum binding specificity between fly and mouse” in Text S1 and Figure S2 ) , fit well with the Drosophila Pum binding data from EMSA . Furthermore , this conservation of Pum binding specificity may be extended to non-mammalian vertebrates , as Xenopus Pum has been shown to bind Drosophila hb NRE [18] , [30] . In fact , the RNA-binding domain of Drosophila Pum is very similar to that in human , mouse and Xenopus ( amino acid identity ≥78% ) . The fact that prediction scores of NRE_M10 and MmSelex_M8 are well correlated with in vitro binding data demonstrates the validity of these two models for Pum binding site prediction . The predicted hits by these two models in the synaptic gene set are significantly higher than random ( Figure S3 ) , further demonstrating their validity and also suggesting that a number of synaptic genes are likely regulated by Pum . In the case of dlg1 , our in vivo evidence indicates that the predicted NRE can function , not only in context of the hb 3′UTR , but also in CNS while Pum is over-expressed . Comparing our synaptic gene set with the pulled-down targets from Gerber et al . [15] , 27 ( 18% ) genes are in the adult specific target list . Only one gene overlaps with the embryo specific targets , presumably because the embryo specific target list is much smaller . Our predicted Pum targets using NRE_M10 and mmSelex_M8 are significantly enriched with experimentally pulled-down targets ( 36% and 30% , respectively , see Figure S5 for more details ) . Although our NRE models , NRE_M10 and mmSelex_M8 were constructed from a very limited number of training sequences , the motif patterns match closely with the consensus Pum binding site published in Gerber et al . [31] , especially in the 8-nt core motif . These all validate the effectiveness of our method . Of course , further improvement can be made with more high confidence training sequences . Studies in diverse organisms strongly indicate that sequences around BoxB play a major role in binding to Puf proteins [15] , [17] , [18] , [31] although BoxA may affect the binding affinity to some extent [32] . Interestingly , the binding specificities appear to vary among Puf family members even though their RNA-binding domains are highly conserved . For example , Puf3 , Puf4 and Puf5 in yeast appear to recognize similar motifs but in different lengths [31] . A recent finding by Opperman et al . [33] shed a light on this . It is indicated that small structural difference in the RNA-binding domain may require extra spacer nucleotides in the binding site . This BoxB related motif , hallmarked with UGUA tetranucleotide , may represent the most prevalent binding sites for Pum or even Puf family proteins . However , other types of binding sites may also exist as we will discuss below . Notably , Pum binds to a 142-nt RNA harboring CycB TCE with a lower affinity than hb NRE under our experimental conditions . CycB TCE was initially proposed due to its resemblance to bcd and hb NRE , and was required for translational repression control [22] . This cis-acting element was able to bind GST-Pum [5] , [34] , but not the purified Pum RBD or native embryonic extracts [5] , [34] . Indeed , CycB TCE has a lower score according to our matrix . A new element downstream of TCE has recently been proposed and been shown to bind to Pum in gel mobility shift experiments and , when substituted for the native hb NRE in a chimeric hb mRNA , was able to mediate CycB-like regulation on hb mRNA [5] , [34] . Intriguingly , our matrix also predicts a Pum-binding site with high score ( ATTGTGCAAA , nts 561–570 of 3′UTR of CycB mRNA ) in the RNA fragment used in these experiments . Our predicted site is close to the NRE element proposed by Kadyrova and colleagues , but not the same . Further work needs to be done to address this discrepancy . It is also worth mentioning that there are several significant differences between regulation of CycB mRNA and hb/bcd mRNAs [5] , [34] . In contrast with bcd and hb , for example , regulation of CycB is Brat-independent . Kadyrova et al . [5] have demonstrated that in the case of CycB , Pum binding seems important only to recruit Nanos , because artificially tethering Nanos to the 3′UTR bypasses the requirement for Pum binding . This is in contrast to Pum's regulation of hb . Thus it seems that there are significant differences between the Pum-binding sites in CycB mRNA and those in hb and bcd mRNAs , as proposed previously [8] . Related to that , in the minimal 51 nt eIF-4E 3′UTR sequence bound by Pum [8] , only one binding site is predicted by NRE_M8 with a score just above the cutoff value 7 . 5 , suggesting the Pum binding to eIF-4E 3′UTR may be also different from hb and bcd . Discovery of additional Pum targets from a variety of cell types and biological contexts may uncover the relationship between NRE sequence and regulatory mechanism . To our knowledge , this is the first study to characterize and predict Pum-binding sites with a PWM approach , which is typically more sensitive and more precise than consensus methods [21] . Our in vitro binding assay of Pum on a subset of the predicted targets provides a measure of validation of our motif models . Like Pum , two of these targets , Ace and dlg1 , also appear to be transcriptionally induced after spaced training relative to massed training , suggesting that these are relevant targets for memory formation . We do not know why both a translational repressor and its putative targets are transcriptionally induced . It may be that transcripts are increased on a cell-wide level , while translation is spatially regulated within neurons . In the case of dlg1 , our in vivo evidence supports the conclusion that the predicted NRE can mediate Pum-dependent repression both when it is in the context of the hb 3′UTR and in the endogenous dlg1 transcript in the CNS . Thus , our findings directly predict that dlg1 is a synaptic target of Pum . Dlg is the sole Drosophila member of a family of membrane-associated guanylate kinases ( MAGUKs ) that in mammals have been shown to play a key role in assembling the post-synaptic density in glutamatergic synapses . In Drosophila , Dlg expression is both pre- and post-synaptic at Type I boutons at the NMJ , and mutants exhibit post-synaptic structural defects as well as increased transmitter release [35] , [36] . Dlg is thought to play a key role in clustering GluRIIB receptors at the NMJ [37] as well as Shaker K+ channels throughout the CNS [26] . Like Dlg , Pum also appears to have both pre- and post-synaptic effects at the NMJ and is co-localized with Dlg at Type I boutons [8] . In addition to morphological effects on synapse structure , Pum appears to regulate excitability via an effect on expression of para Na+ channels [9] , [11] , [38] . The regulation of para may be direct , or may depend upon Pum's putative role in regulating translation of eIF-4E [8] . Pum expression itself is activity-induced and is induced by behavioral training that results in long-term memory [9] , [12] . Thus , one reasonable hypothesis is that activity-dependent increases in Pum expression play a homeostatic role by reducing excitability via repression of para [38] . para is in our list of synaptic genes , yet our models did not predict any Pum binding sites in its 3′UTR . That is not surprising since Mee et al . [9] reported NRE-like sequence located in its 5′UTR . Therefore , a different mechanism may be involved in the regulation of para by Pum . Our findings suggest that an additional role of Pum is direct regulation of dlg1 expression , thereby antagonizing the effects of Dlg on neuronal structure and/or function . We do not yet know whether other classic factors ( Nanos and Brat ) that cooperate with Pum in early embryos are also required in the translational control of Dlg in neurons . Further investigation also will be required to separate the roles of Pum in neuronal development and memory formation . Ultimate confirmation that Pum-dependent repression of dlg1 and the other predicted NRE-containing genes underlies Pum's role in neuronal structure , function and memory will also require additional examination .
Synaptic genes were collected based on GeneOntology ( GO ) terms in the Berkeley Drosophila Genome Project ( BDGP , http://www . fruitfly . org/ ) Release 3 . 1 annotation and keyword search in the FlyBase Vocabulary Report ( http://flybase . org/ ) of gene expression . GO terms involved in neurotransmitter metabolism were not considered to relate directly to synaptic functions , and were thus excluded . 68 genes were obtained from the GO annotation and 132 genes were obtained from FlyBase search using the keyword “synapse . ” Among those , a total of 151 genes were mapped to Release 3 . 1 Drosophila genome ( with CG ID ) and were used for further analysis ( Table S5 ) . Sequences of mRNA or genomic DNA that contain complete 3′UTRs of hb and bcd from different fly species were retrieved from GenBank . The GenBank accessions are listed in Figure 1B . The 3′UTR sequences of all annotated genes for D . melanogaster were retrieved from BDGP Release 3 . 1 annotation . Putative D . pseudoobscura 3′UTR sequences were obtained based on whole-genome alignment between D . melanogaster and D . pseudoobscura produced by the BDGP at Lawrence Berkeley National Laboratory ( http://pipeline . lbl . gov/ ) . Distinct 3′UTR sequences of the mapped 151 synaptic genes are included in Tables S1 , S2 , S3 , S4 , S5 . The Gibbs Sampler program ( [39]; also refer to http://bayesweb . wadsworth . org/gibbs/gibbs . html ) obtained from C . E . Lawrence's group was used to perform local multiple sequence alignment to identify the motif model . The base-frequency matrix output from the program was converted into the log-odds PWM with a background nucleotide frequency derived from all 3′UTRs in the genome of D . melanogaster , i . e . , where wb , j is the matrix weight for base b at position j , fb , j is the frequency of base b at position j and pb is the background frequency of base b . b = A , C , G or T , j = 1 … n for a PWM of length n . Input sequences to Gibbs Sampler included known NREs in hb and bcd of D . melanogaster and their corresponding sequence segments in other fly species ( Figure 1B , in DNA letters without gaps ) . 3′UTR sequences for CycB ( melanogaster and pseudoobscura ) and eIF-4E ( melanogaster only ) were also included . Pattern search was implemented with a Perl script as a regular expression match . Weight matrix scan on sequences was performed with an R script . For a PWM of length n , the score of a target sequence segment t = b1b2 … bn , is:where j is the position in the PWM , bj is the jth base of the target sequence . We searched in the 3′UTR sequences of all 151 synaptic genes , including their distinct splicing variants in D . melanogaster . The matrix score cutoff was selected so that most of the known NREs scored above the threshold . Corresponding putative 3′UTR sequences of D . pseudoobscura were also searched when available . We define a predicted site in D . melanogaster as conserved if this site is aligned or overlaps with a predicted site in D . pseudoobscura in the LAGAN alignment provided by BDGP . The plasmid R6646 that encodes amino acids 1091–1533 of Drosoplila Pum as a fusion with GST [7] was a gift from Dr . Robin Wharton . The protein was expressed in E . coli and purified by affinity chromatography on glutathione-Sepharose ( Amersham Biosciences ) by standard procedures . Transcription templates for the predicted NRE-like elements were obtained by PCR from D . melanogaster genomic DNA . A T7 promoter was added at the 5′ terminus of the template by PCR . PCR products were purified and used as templates for in vitro transcription , which was done as described [40] . RNA transcripts were purified by electrophoresis on an 8% or 4 . 5% polyacrylamide/7M urea gel . EMSA was done as described [6] . The hunchback NRE2 sequence used was AUUAUUUUGUUGUCGAAAAUUGUACAUAAGCC . The random control RNA sequence ( CRS ) is GGUAGUGCAUACAACUUCCUU . Binding reactions were carried out by mixing 10 fmol radiolabeled RNA with variable amounts of purified GST-Pum in a 10 μl binding buffer containing 0 . 1 mg/ml BSA , 10 mM Hepes/KOH pH 7 . 4 , 50 mM KCl , 3 mM MgCl2 , 1 mM EDTA , 0 . 1 mg/ml yeast tRNA , 2 mM dithiothreitol , 0 . 01% ( w/v ) Tween-20 , 0 . 2 U rRNAsin ( Promega ) , and 10% ( v/v ) glycerol . The protein-RNA complexes were allowed to form for 20 min at room temperature , followed by electrophoresis on a 5% non-denaturing acrylamide gel in 1× TBE buffer . The gel was dried , followed by autoradiography at −70°C or quantification on a phosphorimager ( Fuji ) . RNA isolations were performed with Trizol ( Invitrogen ) as described before [12] , with the following modifications . After the Trizol step , samples were treated with DNase I ( Promega , 5 U ) for 30 min ( 37°C ) and then were extracted with phenol/chloroform/iso-amyl alcohol ( Invitrogen ) , precipitated with ethanol , and resuspended in DEPC-treated water . RNA quality was tested using an Agilent Bioanalyzer 2100 and RNA 6000 Nano Chips . Reverse transcription reactions were performed with 5 . 0 µg RNA per reaction with an oligo dT primer and Taqman reverse transcription reagents ( Applied Biosystems ) in 100 µl total volume . PCR quantification was performed by using 4 µl of the above RT product per reaction on a real-time PCR machine ( 7900 HT , Applied Biosystems ) using Taqman probe and Taqman reagents ( Applied Biosystems ) according to the manufacturer's protocols . Gene-specific primers and Taqman probes had the following sequences: Ace: primers: 5′-GCACTACCCAAGACAAATTTTATCGAAA-3′ and 5′-GCCCCGTACTACGCTTACAA-3′; probe: 5′-CACATTTTCGATCGATTCTT-3′ dlg1: primers: 5′-ATCCGCATAATAATGTAAACTACGACAGAA-3′ and 5′-ACTCATTATATAGGTTTAAATCAACGCGAfCAA-3′; probe: 5′-CAAATTCAATTTCTCCTTTTTTCC-3′ TBP: primers: 5′-GCATCATCCAAAAGCTCGGTTT-3′ and 5′-GAGCCGACCATGTTTTGAATCTTAA-3′; probe: 5′-CCCTGCAAAGTTCC-3′ Prior to QPCR quantification of Pum targets , all primers and probes underwent the linearity test using 1 , 2 and 4 µg RNA for RT reaction . Expression levels were normalized to Drosophila TBP transcript levels . TBP was confirmed as an unchanged control by comparing in excess of 100 RNA extractions each after spaced and massed training ( data not shown ) . All reactions were done in parallel by using at least eight independent RNA isolations for each group , with each RNA isolate being assayed once . Normalized threshold values ( Ct ) were subjected to parametric t-tests , with significance levels set at alpha = 0 . 05 . The in vivo function of the predicted NRE-like elements was tested as described by Wharton and Struhl [1] . Briefly , the selected NRE-like elements and control DNA were each cloned and inserted into the SpeI site of plasmid p1809 , which bears a hunchback genomic rescuing construct with a deletion of NRE elements . An Asp718I-BamHI fragment containing each modified hunchback gene was cut out from the resulting plasmid and inserted into the P-element transformation vector CaSpeR4 digested with the same restriction enzymes . The resulting constructs were injected separately into w1118 ( isoCJ1 ) [12] recipient embryos and transformant lines were isolated by standard procedures via the BestGene , Inc . . In all cases , only male progeny were bred to avoid selecting non-expressing inserts . For each modified hunchback gene , four independent transformant lines were analyzed for the effects on segmentation pattern in embryos . NRE function in each line was tested by collecting embryos from heterozygous females . Cuticle preparations were analyzed according to Wharton and Struhl [1] . A stock ( 5137; OK107 ) which is homozygous for both MB-specific Gal4 driver OK107 ( on chromosome IV ) and UAS-mCD8::GFP ( on chromosome II ) was crossed with wild type w1118 ( isoCJ1 ) or UAS-Pumilio ( on chromosome II ) homozygotes flies . Adult brains were dissected in 1× PBS , fixed in 1× PBS containing 4% formaldehyde for 30 minutes , and blocked in penetration/blocking buffer consisting of 1× PBS , 2% Triton and 10% normal goat serum ( Jackson ImmunoResearch Laboratories , Cat . 005-000-121 ) for 2 hours at 4°C . Then dissected brains were placed in primary antibody ( 1:20 dilution in Dilution Buffer containing 0 . 25% Triton and 1% normal goat serum in 1× PBS ) for overnight at 4°C . After washing by Washing Buffer ( 1% Triton , 3% NaCl in 1× PBS ) for 4×10 minutes in room temperature , dissected brains were placed in secondary antibody ( 1:200 dilution in Dilution Buffer ) for overnight at 4°C . The following antibodies were used: monoclonal anti-discs large-s antibody 4F3 ( Developmental Studies Hybridoma Bank at the University of Iowa ) as primary antibody for Dlg staining , monoclonal anti-Fasciclin II-s antibody 1D4 ( Developmental Studies Hybridoma Bank at the University of Iowa ) as primary antibody for FasII staining , Cy3 conjugated AffniPure Goat Anti-Mouse IgG ( H+L ) ( Jackson ImmunoResearch Laboratories , Cat . 115-165-003 ) as secondary antibody . Finally , the brains were washed by washing buffer for 4×10 minutes at room temperature , treated with FocusClear ( CelExplorer Labs , Cat . FC-101 ) for 10 minutes and mounted onto slides with MountClear ( CelExplorer Labs , Cat . MC-301 ) . Confocal stacks of brains were acquired using a ZEISS LSM 510 confocal microscope . Following confocal settings were used: 40× water immersion lens , 1 µm spacing in the z-axis and 1024×1024 resolution in x- and y-axes . The Cy3 signal is captured by HeNe1 543nm laser and GFP signal is captured by Argon/2 488nm laser . All brains were scanned from the anterior to the posterior to ensure good resolution of MB . The raw data were processed by LSM Image Browser Rel . 4 . 2 ( ZEISS ) and further arranged into figures by Adobe Photoshop CS2 . | The Drosophila Pumilio ( Pum ) protein was originally identified as a translational control factor for embryo patterning . Subsequent studies have identified Pum's role in multiple biological processes , including the maintenance of germline stem cell , the proliferation and migration of primordial germ cells , olfactory leaning and memory , and synaptic plasticity . Pum is highly conserved across phyla , i . e . , from worm to human; however , the mRNA targets of Pum within each tissue and organism are largely unknown . On the other hand , the prediction of RNA binding sites remains a hard question in the computational field . We were interested in finding Pum targets in the nervous system using fruit flies as a model organism . To accomplish this , we used the few Pum binding sequences that had previously been shown in vivo as “training sequences” to construct bioinformatic models of the Pum binding site . We then predicted a few Pum mRNA targets among the genes known to function in neuronal synapses . We then used a combination of “golden standards” to verify these predictions: a biochemical assay called gel shifts , and in vivo functional assays both in embryo and neurons . With these approaches , we successfully confirmed one of the targets as Dlg , which is the Drosophila ortholog of human PSD95 . Therefore , we present a complete story from computational study to real biological functions . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"neuroscience/behavioral",
"neuroscience",
"developmental",
"biology/developmental",
"molecular",
"mechanisms",
"computational",
"biology"
] | 2008 | Identification of Synaptic Targets of Drosophila Pumilio |
Given that micronutrient deficiency , neglected intestinal parasitic infections ( IPIs ) and poor socioeconomic status are closely linked , we conducted a cross-sectional study to assess the relationship between IPIs and nutritional status of children living in remote and rural areas in West Malaysia . A total of 550 children participated , comprising 520 ( 94 . 5% ) school children aged 7 to 12 years old , 30 ( 5 . 5% ) young children aged 1 to 6 years old , 254 ( 46 . 2% ) boys and 296 ( 53 . 8% ) girls . Of the 550 children , 26 . 2% were anaemic , 54 . 9% iron deficient and 16 . 9% had iron deficiency anaemia ( IDA ) . The overall prevalence of helminths was 76 . 5% comprising Trichuris trichiura ( 71 . 5% ) , Ascaris lumbricoides ( 41 . 6% ) and hookworm infection ( 13 . 5% ) . It was observed that iron deficiency was significantly higher in girls ( p = 0 . 032 ) compared to boys . Univariate analysis demonstrated that low level of mother's education ( OR = 2 . 52; 95% CI = 1 . 38–4 . 60; p = 0 . 002 ) , non working parents ( OR = 2 . 18; 95% CI = 2 . 06–2 . 31; p = 0 . 013 ) , low household income ( OR = 2 . 02; 95% CI = 1 . 14–3 . 59; p = 0 . 015 ) , T . trichiura ( OR = 2 . 15; 95% CI = 1 . 21–3 . 81; p = 0 . 008 ) and A . lumbricoides infections ( OR = 1 . 63; 95% CI = 1 . 04–2 . 55; p = 0 . 032 ) were significantly associated with the high prevalence of IDA . Multivariate analysis confirmed that low level of mother's education ( OR = 1 . 48; 95 CI% = 1 . 33–2 . 58; p<0 . 001 ) was a significant predictor for IDA in these children . It is crucial that a comprehensive primary health care programme for these communities that includes periodic de-worming , nutrition supplement , improved household economy , education , sanitation status and personal hygiene are taken into consideration to improve the nutritional status of these children .
Anaemia is a specific condition where red blood cells are not providing adequate oxygen to the body tissues . It is usually caused by iron deficiency , which is the commonest micronutrient deficiency in both developing and developed countries [1] , [2] . Generally , it takes at least several weeks after iron store has depleted before anaemia develops . When iron deficient occurs , haemoglobin concentrations are reduced to below optimal levels and therefore , iron deficiency anemia ( IDA ) is considered to be present . However , because anaemia is the most common indicator used to screen for iron deficiency , the terms anaemia , iron deficiency , and IDA are sometimes used interchangeably and synonymously [2] . Group most affected include pregnant women , pre-school and school-age children , low birth weight infants and women of child-bearing age [1] , [3] . The World Health Organization ( WHO ) estimates that more than two billion people are affected by iron deficiency and anaemeia , which corresponds to 24 . 8% of the world's population [1] . Most are in the Western Pacific and South-East Asia . Despite its increasing prevalence in South-East Asia , anaemia is the most neglected nutritional deficiency disorder in the region today [4] . Iron deficiency anaemia ( IDA ) has severe nutritional and health consequences , including inadequate growth and mental development in children [5] , high maternal mortality and incidence of low birth weight infants and low productivity in adults [5] , [6] . Poor school performance among school children and adolescent has also been associated with IDA [7] , [8] . Micronutrient deficiency causes are multifactorial ranging from micronutrient deficiency such as iron , folate and vitamin B12 , insufficient dietary intake , malabsorption and infectious diseases in particular parasitic infections [9] . The latter is well documented and soil-transmitted helminth ( STH ) infections are prevalent in areas where anaemia and IDA is widespread [10] . Accumulating evidence from a number of studies has shown that micronutrient deficiency and STH infections are intertwined and co-exist among low-income population [11] , [12] . Other determinants such as demographic factors such as age , gender and larger family size [13] , [14] , and low educational attainment of parents [15]–[17] has shown to have significant association with both anaemia and IDA , particularly among the rural and poor communities in developing countries . In Malaysia , the impact of STH infections on nutrition , growth and development have been studied [11] , [12] , [16] , [18] , [19] . Malnutrition is often associated with IDA because of the low intake of heme iron from animal food sources , derived from low quality diet because of poverty . Very often malnourished individuals are also anaemic and they are often associated with high parasitic infections , particularly STH infections and malaria . Several studies have demonstrated that STH infections are strong indicators of malnutrition such as IDA and low serum retinol ( i . e . , indicative of vitamin A deficiency ) [19]–[21] . Given that the nutritional deficiency , neglected intestinal parasitic infections and poor socioeconomic status are closely linked , we conducted a comprehensive study to provide current information on a continuing problem on the prevalence of anaemia , iron deficiency , IDA , intestinal parasitic infections and also to investigate their possible associated factors among 550 children living in remote and rural areas in West Malaysia .
A cross-sectional study was carried out between November 2007 to July 2009 among 550 children living in 8 villages from 5 different states in remote and rural areas of West Malaysia . The villages were selected based on ( i ) village entry approval by the Ministry of Rural and Regional Development Malaysia , ( ii ) STH infections , anaemia and IDA are known to be high and ( iii ) it is accessible by road transportation for rapid transfer of samples to the laboratory . Each village had a small population , and the number of children in each village was estimated to be between 20 to 100 . Majority of the parents ( 71 . 8%; 409/570 ) did not have any formal education . More than half ( 85 . 6% ) of the parents of the children did odd jobs such as selling forest products without any stable income . Some were daily wage earners working in rubber or palm oil plantations , unskilled laborers in factories or construction sites . Therefore , more than half ( 76 . 3% ) of the households which the children belonged to earned less than RM 500 per month ( <US$ 166 . 7 ) , the poverty income threshold in Malaysia [22] which is inadequate to maintain a good living standard . Although majority of the children's houses have provision of basic infrastructure such as treated water supply ( 56 . 5% ) , at least 43 . 5% are still using untreated water originating from a nearby river for their domestic needs . All children that agreed voluntarily to participate were included in this study . The inclusion criteria were children below 12 years old , residence in rural and remote areas and provided consent to participate . Exclusion criteria included having medical condition for which follow-up was required or refusal to participate . Although 700 questionnaires and faecal containers were distributed , only 550 stool and blood samples were collected the following day resulting in a response rate of 78 . 6% . Hence , 150 ( 21 . 4% ) children who did not turn up or failed to provide their faecal or blood samples were excluded from the study . An interview-administrated questionnaire was used to elicit and gather information from participants on the demographic ( i . e . , age , gender and education attainment ) , socioeconomic ( i . e . , father or mother occupation , household income ) and medical treatment ( i . e . , whether the participant has taken anthelminthic drugs and iron supplement ) of the participants which will assist the assessment of potential factors associated with serum iron status . It was adapted from a standard questionnaire that was previously used in recent studies on IPIs and iron serum indicator in Malaysia [11] . The questionnaire was first designed in English and then translated and pretested in Malay language , which is the national language for Malaysia and well understood by the participants . For very young children , the questionnaire was completed by interviewing their parents and guardians or the relevant adult ( normally head of the family ) who signed the informed consent . Participants who participated in this study were honored with a small token of appreciation . Approximately 5 ml of venous blood sample was drawn from each qualified participant who fulfilled the specific criteria by trained medical assistants and nurses . Each blood sample collected was distributed into 2 different tubes: ( i ) Becton Dickinson Vacutainer K2 EDTA tube ( anticoagulant ethylene diamine tetraacetic chloride ) and ( ii ) plain tube ( without anticoagulant ) . The blood samples were kept in standard storage box with ice pack and transported back to the Department of Parasitology , Faculty of Medicine , University of Malaya for further analysis . Blood samples were spun at 1500 rpm for 10 minutes and the sera and plasma were kept at −20°C until use . All the samples were analyzed within 3 to 10 hours after blood collection . Iron status was determined by measuring the haemoglobin , serum ferritin ( SF ) and serum iron ( SI ) levels [3] . Individuals are categorized as iron deficient when the SF level falls below the cut-off value ( see below ) . For IDA , individuals should be both anaemic ( low Hb level ) and iron deficient ( low SF level with or without low SI level ) . Hb was measured using an automated hematology cell counter analyzer ( Sysmex XE-2100 , Sysmex America , Inc . ) . The procedure was carried according to manufacturer's guidelines . Anaemia was confirmed when the Hb level is <110 g/L for children aged 6 to 59 months , <115 g/L for children 5 to 11 years , <120 g/L for children 12 years [2] . The level of SF was determined using the ADVIA Centaur System Assay ( Bayer ADVIA Centaur; Siemens Healthcare Diagnostics , NY , USA ) . This is a two-site sandwich immunoassay using direct chemiluminometric technology , which uses constant amounts of two anti-ferritin antibodies . The procedure was carried out according to the ADVIA Centaur Assay Manual ( 111653 Rev . G , 2003–2005 ) as provided by the manufacturer's guidelines . Iron deficiency ( ID ) was determined when SF levels are <15 µg/L for individuals aged >4 years . In addition , a lower cut-off value ( <10 µg/L ) was also used for participants 1 year old [2] . SI was determined calorimetrically using the FerroZine method on the COBAS INTEGRA 400/800 ( Iron Gen . 2 ) analyzer ( Roche Diagnostic GmbH , Indianapolis , IN , USA ) . The procedures were carried out according to the manufacturer's guidelines . Individuals with concentrations below the cut-off value ( <11 µmol/L ) were considered to have ID [2] . Individuals with normal Hb levels and low SF level with or without low SI level were classified as iron deficiency . All these procedures pertaining to Hb , SF and SI were carried out at the Clinical Diagnostic Laboratory , University Malaya Medical Centre ( Malaysia ) . For the examination of parasites in faeces , a wide mouth and screw capped faecal container with an attached scoop were labeled , coded and distributed to each participant together with plastic bag after the questionnaires were completed . The participant was instructed to scoop a thumb size faecal sample using a provided scoop into the container , making sure that the sample was not contaminated with urine for collection on the following day . The collected faecal samples were processed using formalin ether concentration technique [23] followed by iodine staining and microscopy examination for the presence of STH infections . In addition , Kato-Katz technique was employed to determine the intensity of STH infections , as estimated by egg counts per gram of faeces for the presence of Ascaris lumbricoides , Trichuris trichiura and hookworm ova [24] . The worm burden was classified as light , moderate and heavy based on the threshold proposed by WHO Expert Committee [25] . Dysenteric or inadequate samples , which were unsuitable for egg counts were used only for the confirmation of the presence of STH ova by formalin ether concentration technique . Statistical analysis was carried out using the SPSS software ( Statistical Package for the Social Sciences ) programme for windows version 13 ( SPSS , Chicago , IL , USA ) . For descriptive data , percentage rate was used to describe the characteristics of the studied population , including the prevalence of anaemia , IDA and STH infections . The distribution of Hb , SF and SI were presented as median and inter quartile range ( IQR ) after being examined for normality using the Kolmogrov-Smirnov Z test . The intensity of STH infections ( worm burden ) was quantitatively estimated as ova per gram of faeces and was categorized into three main categories: light , moderate and heavy infections . The distribution of egg counts for all the three STH species were not normally distributed , hence presented as median . Crude associations of the binary outcome variable ( for proportion ) were assessed by Pearson's Chi-square ( X2 ) . For each categorical variable , odds ratios ( ORs ) and 95% confidence interval ( 95% CI ) were calculated using univariate analysis . As for the continuous variables , i . e . , Hb , SI , SF value and egg count of the three STH species were not normally distributed , therefore the correlation between each of these variables were computed using Spearman's correlation coefficients ( rs ) test . The association between anaemia , iron deficiency and IDA and their determinants were examined by univariate and multivariate logistic regression analysis . Significant variables in univariate analysis ( p<0 . 05 ) were included in a logistic multivariate analysis ( stepwise regression ) to determine which factors could be dropped from the multivariable model . The level of statistical significance was set as p<0 . 05 and for each statistically significant factor , an odds ratio ( OR ) and 95% confidence interval ( 95% CI ) were used for all test to explore the strength of the association between anaemia , ID and IDA and the variable of interest . The study protocol was approved and granted by the Ethics Committee of the University Malaya Medical Centre ( MEC Ref . No . 638 . 36 ) . Prior to participation , surveyors introduced themselves and an oral briefing to describe the objective and methodology of the study was given to the participants . They were also informed of the potential risk of employed procedures and the assurance that their identity and personal particulars will be kept confidential and anonymously . Participation was voluntary and the children could withdraw from the study at any time without giving any reason . Consent of those who agreed to participate were taken either in written form ( signed ) or verbally followed by their thumb prints and from parents or guardians ( on behalf of the very young children ) .
A total of 550 children ( 254 boys and 296 girls ) were recruited in this study . With regards to age groups , there were a total of 30 ( 5 . 5% ) young children aged 1 to 6 years and 520 ( 94 . 5% ) school children aged 7 to 12 years with a median age of 10 years . The present study showed that 26 . 2% ( 144/550 ) of the participants had anaemia , 54 . 9% ( 302/550 ) had ID and 16 . 9% ( 93/550 ) had IDA ( Table 1 ) . The median concentration of haemoglobin , serum ferritin and serum iron was 126 . 0 g/l ( IQR = 119 . 0–133 . 0 ) , 26 . 1 µg/l ( IQR = 13 . 0–51 . 6 ) and 11 . 5 µmol/l ( IQR = 8 . 4–15 . 3 ) , respectively . The prevalence of iron status was further analyzed according to gender and age groups ( Table 1 ) . Generally , the occurrence of anaemia , ID and IDA were not significantly associated with age and gender . Although the prevalence of anaemia in young children aged 1 to 6 years ( 36 . 7% ) was higher compared to school children aged 7 to 12 years ( 25 . 6% ) , but the differences was not statistically significant . Similarly , there was no significant difference between ID and IDA with age groups although the prevalence of ID and IDA were high among young children compared to school children . With regards to gender , it was observed that only ID was significantly higher in girls ( X2 = 4 . 50; p = 0 . 032 ) compared to boys . The overall prevalence of STH infections was 76 . 5% ( 421/550 ) . Among all the three species of STH infections , Trichuris trichiura ( 71 . 5%; 393/550 ) was the most predominant , followed by Ascaris lumbricoides ( 41 . 6%; 229/550 ) while only 13 . 5% ( 74/550 ) had hookworm infections ( data not shown ) . Off these , double infections ( 36 . 5%; 201/550 ) was most common followed by single infection ( 33 . 3%; 183/550 ) and 6 . 7% ( 37/550 ) were infected with all three worm infections . The combination of T . trichiura and A . lumbricoides ( 31 . 8%; 175; 550 ) was the most common , followed by T . trichiura and hookworm ( 3 . 1%; 17/550 ) and hookworm and A . lumbricoides ( 1 . 6%; 9/550 ) . As for single infection , T . trichiuria infection ( 29 . 8%; 164/550 ) was the most prevalent , followed by hookworm infection ( 2 . 0%; 11/550 ) and A . lumbricoides ( 1 . 5%; 8/550 ) ( data not shown ) . With regards to the intensity of infections , not all microscopically positive samples were examined by Kato Katz due to the limited amount of sample available . This resulted in only 391 out of 393 microscopically positive for T . trichiura , 224 out of 229 for A . lumbricoides and 65 out of 74 for hookworm were examined by Kato Katz , respectively ( Table 2 ) . The median egg counts among infected children were 1 , 465 ( range: 22–115 , 085 epg ) for T . trichiura , 6 , 638 ( range: 22–365 , 190 epg ) for A . lumbricoides and 44 ( range: 22–4 , 129 epg ) for hookworm infection . The proportion of the infected children was further explored according to intensity of infection for all the three STH species ( Table 2 ) . The mean egg count for hookworm showed a significant difference with age ( F = 0 . 034; p<0 . 001 ) as determined by one way ANOVA of log 10 transformed egg count . However , the mean egg count for T . trichiura and A . lumbricoides did not show any significant variation with age . Similarly , there was no significant difference between mean egg counts of all the three STH species with gender ( data not shown ) . The prevalence of T . trichiura and A . lumbricoides infections were found to be significantly associated with anaemia and IDA . However , no prevalence of any STH infections was significantly associated with ID . There was a significant correlation between increasing T . trichiura egg counts and decreasing Hb value , however , this correlation was weak ( rs = −0 . 122; p = 0 . 016 ) . As for A . lumbricoides and hookworm egg counts , no significant correlation was found with Hb value . Likewise , the SI value was also not significantly correlated with any of the three STH species egg counts . With regards to SF values , A . lumbricoides egg count was significantly correlated with SF values ( rs = −0 . 150; p = 0 . 019 ) . The distribution of iron status indicator was also analyzed according to intensity of STH infections ( Table 3 ) . The Hb , SF and SI levels declined from light infection to heavy infection for T . trichiura , A . lumbricoides and hookworm infections . Although the prevalence of anaemia , ID and IDA increased with increasing worm burden , it was not statistically correlated with any of the worm burden thresholds . The association of IDA in relation to IPIs and sociodemographic characteristics were examined by univariate analysis ( Table 4 ) . The results showed that low level of mother's education , i . e . , less than 6 years of formal education ( OR = 2 . 52; 95% CI = 1 . 38–4 . 60; p = 0 . 002 ) , non working parents ( OR = 2 . 18; 95% CI = 2 . 06–2 . 31; p = 0 . 013 ) , low house income ( OR = 2 . 02; 95% CI = 1 . 14–3 . 59; p = 0 . 015 ) , T . trichiura infection ( OR = 2 . 15; 95% CI = 1 . 21–3 . 81; p = 0 . 008 ) and A . lumbricoides infection ( OR = 1 . 63; 95% CI = 1 . 04–2 . 55; p = 0 . 032 ) were significantly associated with the odds of IDA . A logistic regression model was used to assess the effects of the significant explanatory variables in order to distinguish predictors of IDA . The final multivariate analysis indicated that only low level of mother's education , i . e . , less than 6 years of formal education ( OR = 1 . 48; 95 CI% = 1 . 33–2 . 58; p<0 . 001 ) was a significant predictor for IDA in these children .
Anaemia is regarded worldwide as a medical condition deserving of sustained public health intervention and still a major public health problem in many developing countries , especially in rural communities . It is estimated that most children and preganant women in developing and 40 . 0% in developed countries are iron deficient [2] . Findings of the present study demonstrated that the overall prevalence of anaemia was 26 . 2% while 54 . 9% had ID and 16 . 9% had IDA among rural and remote children of West Malaysia . This is in concordance with a study among rural adolescents in Sabah ( East Malaysia ) , which found that the prevalence of anaemia and IDA was 20 . 0% and 17 . 0% , respectively [13] . However higher rates were reported in other local studies . The most recent study conducted among rural school children in Malaysia reported a prevalence of 48 . 5% for anaemia and 34 . 0% for IDA [11] . Similarly , another local study which has been conducted among rural children documented 41 . 5% and 36 . 0% of anaemia and IDA , respectively [16] . When compared to data from other countries , the present results demonstrated that the prevalence of anaemia and IDA among rural children in Malaysia was relatively higher . In south-eastern Brazil , the prevalence of anaemia , ID and IDA was 11 . 8% , 12 . 7% and 4 . 3% , respectively among populations living in highly endemic area of hookworm infection [26] and relatively lower prevalence of anaemia ( 16 . 5% ) was also reported in South Africa [27] . However , anaemia was extremely high ( 92 . 0% ) in Kenya , which could be attributed to the high prevalence of malaria in the study area [28] . Nevertheless , findings of this present study are parallel with the most recent study carried out among Nigerian children where 38 . 6% children were found to be anaemic [29] . Similarly , study in northeast Thailand also reported 31 . 0% of the children to be anaemic [30] . Among the age groups , the prevalence of anaemia , ID and IDA were higher among young children compared to school children . However , this finding could be attributed to the benefit of school children having access to iron supplementation ( sponsored by the government ) in rural schools . The present study found low prevalence of IDA among children who received iron supplement within the last 12 months although it was not statistically significant . A local study investigated the effects of iron-folate supplements administered at school and it was found that iron-folate supplementation has a direct benefit in improving iron nutrition on these schoolchildren [31] . It has also been demonstrated that this is a practical , safe , effective and inexpensive method for improving the wellbeing of school children [31] . The low numbers of young children , i . e . , less than 6 years old who participated in the present study compared to school children has unable us to investigate the casual association between cases of anaemia , ID and IDA with age groups . Nonetheless , previous studies conducted in Malaysia [11] , [16] , Thailand [17] and Brazil [26] have documented that cases of anaemia decreased with age . The poor daily iron intake together with poverty and infections could be the main factors contributing to high prevalence of anaemia and IDA among the children involved in this study . Although efforts to obtain meaningful dietary assessment was unsuccessful in this study , other studies have shown that daily iron intake among rural children was low and inadequate , achieving only 29 . 0% to 49 . 0% of the Recommended Daily Intake ( RDI ) [11] . In the present study , 76 . 5% of the children were infected with at least one of the STH species . T . trichiura ( 71 . 5% ) infections proved to be the most common compared to A . lumbricoides ( 41 . 6% ) and hookworm ( 13 . 5% ) . This is in agreement with other previous local studies where T . trichiura infections had the highest prevalence ( range: 26% to 98 . 2% ) , followed by A . lumbricoides infections ( range: 19% to 67 . 8% ) and lastly hookworm infections ( range: 3% to 37% ) [16] , [32]–[35] . Therefore , the present findings not only showed that the prevalence of STH remains high but the trend of distribution of STH also remains unchanged in these rural children [34] . The higher rate of STH infection especially T . trichiura infection could be due to the ineffective dosage and choice of anthelminthic used or drug resistance and has been discussed in our previous study [35] . The aetiology of anaemia and IDA and the reasons for its ubiquitous persistence are multi-factorial and complex [1] , [2] . Interactions of many factors that co-exist such as poor dietary intake , increased demands ( e . g . , growth ) , parasitic infections , socioeconomic causes and genetic factors ( e . g . , thalassaemia ) may be causes of anaemia and IDA . Therefore , the present study also highlighted and assessed the relationship between the associated factors underlying iron status . There was significant association between anaemia and IDA in those who were infected with T . trichiura compared to uninfected individuals as reported in the present study . This is in line with other studies where T . trichiura infection is a significant predictor for anaemia and IDA among Panamanian [7] and Kenyan children [36] . The present study also demonstrated that those infected with severe T . trichiura were almost two times more likely to suffer from IDA , which is similar to previous studies where high intensity of T . trichiura infection as a significant risk factor for anaemia and IDA [11] , [16] . Studies conducted in south-eastern Brazil [26] and East Africa [37] also showed significant association between intensity of T . trichiura and hookworm infections with anaemia and IDA . In T . trichiura infections , it is well accepted that the infection may involve significant blood loss given the location of the worm in the large intestine [7] . Blood depletion is even worse in cases where trichuriasis is in concomitant with hookworm infections . Adult hookworms tend to inhabit the upper small intestine , whereas mature T . trichiura inhabit the upper caecum and colon . Bleeding due to hookworm infection occurs in the upper small intestine and some of the constituents from the blood are reabsorbed further down in the gastrointestinal tract . Therefore , it is possible that the re-absorption of iron may be impaired , either by ingestion of the iron by T . trichiura or by the mal-absorptive surface of the gut [7] . Moreover , severe T . trichiura infection also causes colitis leading to dysentery and chronic faecal blood loss . In our study , we also found significant relationship between A . lumbricoides infections and IDA among these rural children . Similarly , a most recent study conducted among rural Nigerian children found significant association between A . lumbricoides infection and anaemia [29] . Likewise , study among Zanzibari schoolchildren also demonstrated that an A . lumbricoides infection was associated with lower Hb values [38] . Iron is absorbed through the intestinal wall in the duodenum and jejunum and it is believed that iron absorption could be impaired by the presence of A . lumbricoides in this part of the intestine [39] . Although we found no significant association between hookworm infection nor intensity of the infection with iron status , the prevalence of anaemia and IDA were higher among those infected with hookworm infections . This finding is parallel with a study conducted among Vietnamese [40] and Ugandan [41] children where no association was established between hookworm infection and anaemia but disagrees with a most recent study among children living in rural Nigeria [29] . This is also in contrast with studies conducted in East Africa which found that iron stores depleted even with light eggs counts [37] . Additionally , previous evidences have demonstrated that hookworm infection as an important aetiological cause of anaemia and IDA among infected individuals [26] , [36]–[38] . This could be due to a low prevalence of hookworm among the children , whom mainly had low infection intensity . It is also possible that the hookworm infection among the children in the present study were too light to have significant impact on their iron status . It is also likely that iron stores were not sufficiently depleted for hookworm to be associated with anaemia . The present study also highlighted the impact of low socioeconomic status on their iron status among these rural children . In addition , parental educational attainment ( especially mothers ) also plays an importance role on the health of the children as demonstrated in the present study whereby children of parent with low educational background are more likely to develop IDA than children of parent with higher educational background . Similar observation has been reported in study among rural children in Malaysia [11] . Likewise , study conducted in Brazil also reported the low level of Hb and SF among children of illiterate parent [42] . Significant association between non working parents and IDA was also noted in the present study , which corroborated with previous study , showing significant correlation between IDA and non working parent in India [15] . However , there is a disparity between the present findings with a previous study , which found a significant association between IDA and working parent [11] , [16] . Low household income ( <RM 500 per month/<US$ 166 . 7 ) was also significantly associated with the high prevalent of IDA in the present study . Previous study also attributed poverty , unavailability of nutritious food and proper health care as significant contributing factors [11] . Such an association between low household income and malnutrition was also reported among rural children in Malaysia [43] , [44] . A study in Thailand observed that there is a significant increase in risk of acquiring IDA when household income decreases [17] . The present study has several limitations . Firstly , the findings were based only on single point data collection , i . e . , cross-sectional study , and may therefore fail to identify direct casual association between IDA and it determinants . The casual associations between IDA and risk factors of importance can be confirmed by pre and post intervention observational studies that compare the effects of deworming treatment on iron status . There have been numerous evidences that showed regular antihelminthic treatment does improve the iron status of the infected individuals . Study conducted to evaluate the effects of school based deworming program on iron status among children in Zanzibar [45] and Tanzania [46] demonstrated significant improvement of the Hb and serum ferritin concentrations after treatment with anthelminthic drug . Secondly , the results on IDA which depended solely on SF as the indicator for iron status in these populations burdened with high prevalence of infections may lead to underestimation of iron deficiency . Serum ferritin , a reputedly more stable marker of iron status has been used widely as a reliable index in nutritional survey and clinical assessment for the replacement of SI and total iron binding capacity ( TIBC ) [47] , however , many studies have demonstrated that SF tends to be elevated during the presence of acute or chronic inflammation [48] . It is well known that infections can lead to inflammation and SF level may often reach up to 20 µg/L in the present of inflammation even in the presence of marked iron deficiency [49] . Unfortunately , we have not been able to consider the effect of inflammation on the assessment of SF given that not all infected individual with intestinal parasites had inflammation and vice versa . Assumption of the presence of inflammation in all subjects or those infected individual could lead to underestimation of the number of cases with low SF . Therefore , it is highly recommended to use different indicators such as C-reactive protein ( CRP ) or α-1 chymotrypsin ( ACT ) to distinguish between inflamed and non-inflamed individuals in indicating whether a normal or high level of ferritin can truly represent adequate iron stores in future study [49] . With regards to this , we have tried our best to minimize the effect of inflammation on SI level such as by excluding any children with evidence of severe and chronic inflammation from our study and also by using a low cut-off point for SF ( <10 µg/L ) so that there can be little doubt that iron status was deficient . Nevertheless , despite all these limitations , this study is one of the few quantitative , comprehensively analyzed studies on the epidemiology of parasitic infection , iron status and its determinants among Malaysian children . In conclusion , our results provided a comprehensive current population-based iron status among children living in highly endemic area of IPIs coupled with poor socioeconomic background . As the alleviation of poverty among rural communities is critical as illustrated by the health consequences , some of the major issues which propagate poverty such as being left out of the country's mainstream development need to be address urgently and holistically . It is crucial that a comprehensive primary health care programme for these communities which includes periodic de-worming , nutrition supplement , improved household economy , education , sanitation status and personal hygiene are taken into consideration to improve the nutritional status of these children . | Micronutrient deficiency and intestinal parasitic infections ( IPIs ) share a similar geographical distribution . A conservative estimate indicated that almost 2 billion individuals suffer from anaemia due to iron deficiency ( ID ) , corresponding to 24 . 8% of the world's population . Crucially , most of these individuals are children and women of reproductive age in developing countries . Intestinal parasitic infections , especially soil-transmitted helminthes ( STH ) , are prevalent in areas where micronutrient deficiency is widespread and the relationship between them has been studied . Most studies have noted an association between iron deficiency and IPIs . Against this background we studied the association between micronutrient deficiency , IPIs and socioeconomic factors among rural children in West Malaysia . Overall , 26 . 2% , 54 . 9% and 16 . 9% of the participants had anaemia , ID and iron deficiency anaemia ( IDA ) , respectively . The overall prevalence of STH infections was 76 . 5% with Trichuris trichiura ( 71 . 5% ) , Ascaris lumbricoides ( 41 . 6% ) and hookworm ( 13 . 5% ) . Univariate analysis found that low level of mother's education , i . e . , less than 6 years of formal education , non working parents , low house income , T . trichiura infection and A . lumbricoides infection were significantly associated with the odds of IDA . The final multivariate analysis indicated that low level of mother's education was a significant predictor for IDA in these children . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
"nutrition",
"neglected",
"tropical",
"diseases",
"parasitic",
"diseases"
] | 2012 | Association between Anaemia, Iron Deficiency Anaemia, Neglected Parasitic Infections and Socioeconomic Factors in Rural Children of West Malaysia |
Pathogenicity of the human pathogen Helicobacter pylori relies upon its capacity to adapt to a hostile environment and to escape from the host response . Therefore , cell shape , motility , and pH homeostasis of these bacteria are specifically adapted to the gastric mucus . We have found that the helical shape of H . pylori depends on coiled coil rich proteins ( Ccrp ) , which form extended filamentous structures in vitro and in vivo , and are differentially required for the maintenance of cell morphology . We have developed an in vivo localization system for this pathogen . Consistent with a cytoskeleton-like structure , Ccrp proteins localized in a regular punctuate and static pattern within H . pylori cells . Ccrp genes show a high degree of sequence variation , which could be the reason for the morphological diversity between H . pylori strains . In contrast to other bacteria , the actin-like MreB protein is dispensable for viability in H . pylori , and does not affect cell shape , but cell length and chromosome segregation . In addition , mreB mutant cells displayed significantly reduced urease activity , and thus compromise a major pathogenicity factor of H . pylori . Our findings reveal that Ccrp proteins , but not MreB , affect cell morphology , while both cytoskeletal components affect the development of pathogenicity factors and/or cell cycle progression .
Helicobacter pylori is a Gram negative , highly motile , microaerophilic , spiral-shaped organism , which colonizes the stomachs of at least half of the world's population [1] . Infection of humans results in persistent gastritis , which can develop into peptic ulcer disease and adenocarcinoma [2] , [3] . Motility is a key factor in the adaptation of infection , allowing for the penetration of the mucus and enabling the bacteria to colonize and to persist in the gastric lumen [4] . Both spiral shape and flagella contribute to the motility of this human pathogen . Whereas flagella of H . pylori have been studied intensively , our knowledge of the maintenance and establishment of spiral structure in H . pylori and in fact for any bacterium is marginal . In addition , nothing is known about any cytoskeletal protein in this pathogen . Maintenance of cell morphology is highly important or essential for functioning and survival of most eukaryotic and prokaryotic cells . For many eukaryotic cells , it is also vital to be able to change the shape of the cell , and/or to be able to move via flexible extension/retraction of the cell membrane . Cytoskeletal elements actin and intermediate filaments are key elements of the eukaryotic cytoskeleton that controls cell morphology and cell rigidity . Due to its rapid polymerisation/depolymerization properties , actin is the driving force for motility involving membrane rearrangements , and is also involved in trafficking of vesicles and in cell division [5] . IF proteins , on the other hand , are characterized by extended coiled coil regions . The proteins are believed to be highly elongated and assemble into sheet structures based on extensive interactions between coiled coils [6] . IF like proteins provide mechanical strength to e . g . skin or blood vessel cells , and are involved in positioning of cellular organelles [7] . For most rod shaped bacteria analysed so far , the loss of genes affecting cell shape is lethal . Escherichia coli or Bacillus subtilis cells are unable to grow as round cells , into which they turn when gene products of rodA , mreB , or mreC are depleted . While RodA and MreC are membrane proteins , whose function is still unclear , MreB is an actin like protein that forms filaments in vitro , dependent on ATP [8] . In vivo , MreB forms filamentous helical structures underneath the cell membrane [9] , [10] . In B . subtilis and in Caulobacter crescentus , these filaments are highly dynamic , and appear to move along the membrane with dynamics similar to those of eukaryotic actin [11] , [12] . Movement of filaments is most likely based on ratchet-like extension of filaments at one end , and depolymerization ( and thus shrinkage ) at the other end . E . coli MreB and an MreB ortholog , Mbl , in B . subtilis , have been shown to interact with MreC [13] , [14] , which in turn appears to interact with enzymes that synthesize the extension of the murein sacculus [15] . Because the incorporation of new cell wall material occurs in a helical pattern [16] , it has been proposed that the helical organization of MreB filaments in the cytosol may direct the helical localization of cell wall synthetic proteins within the periplasm/outside the cell . A disputed question is the effect MreB exerts on the segregation of duplicated chromosomes . Interfering with MreB levels or polymerization activity has been shown to strongly impair chromosome segregation in several organisms [10] , [17] , but arguments against a direct involvement of MreB in segregation have also been put forward [18] . The question of how bacterial cells can obtain a curved shape has only been investigated in the vibrio-shaped bacterium C . crescentus . CreS encodes for a coiled coil protein , crescentin , which has high similarity to IF proteins . Crescentin forms filamentous structures in vitro without the addition of any nucleotides . Deletion of creS leads to the generation of straight cells , and thus to loss of cell curvature , while the culture doubling time or any other obvious physiological aspect of the cell is not affected [19] . Crescentin localizes as a defined ribbon structure along the short side of the cells , suggesting that it forms a filamentous structure in vivo [19] . Recent evidence suggests that crescentin exerts its effect on cell curvature through mechanical control of cell growth [20] . In this work , we set out to analyse cytoskeletal elements in the human pathogen Helicobacter pylori . We have systematically inactivated genes encoding coiled coil-rich proteins , and for mreB . Surprisingly , deletion of mreB is not lethal , but affects a variety of cellular parameters , such as chromosome segregation , but not cell shape . Deletions of Ccrp ( coiled coil rich proteins ) genes have different effects on cell shape in different strains , from loss of helical shape to complete loss of a regular morphology . We have also established a system for the visualization of proteins in H . pylori , and show that Ccrp proteins have a specific pattern of localization , consistent with their function in cell shape maintenance .
To gain insight into the question of how H . pylori gains its helical cell shape , we searched for elements similar to known cytoskeletal or cell morphological elements . Chromosomes of all H . pylori strains analysed contain a gene with high similarity to mreB , followed by a mreC gene . Like in E . coli and B . subtilis , the MreC gene product is predicted to contain a single membrane span , and coiled coil regions . No mreD gene could be found in the genomes , but a rodA like gene , and several pbp genes ( not shown ) . Interestingly , all strains contain two genes that have already been suggested to encode for IF-like proteins ( HP0059 and HP1143 in strain 26695 ) [19] , which are predicted to contain several extended heptad repeat regions , but also a so-called stutter , where coiled coil 4 is clearly discontinued for few amino acids [21] . However , HP0059 is almost entirely composed of heptad repeat regions , and lacks the characteristic N- and C-terminal domains of IF proteins , which are predicted to be globular . According to their predicted secondary structure we suggest to term this class of proteins as “coiled coil rich proteins” ( Ccrp ) . We designate the H . pylori HP0059 or HP1143 gene products as Ccrp59 or Ccrp1143 , respectively . Because of the genetic ( and morphological ) variability of Helicobacter pylori , we generated constructs in several different strains , to obtain information on the general validity of gene deletions or localization patterns of fusion proteins . We focussed our work on the reference strain 26695 ( moderately motile ) , on KE88-3887 , a hyper-motile variant of strain 26695 , and on the clinical isolates G27 and 1061 , all of which are relatively well amenable for genetic analysis . It should be noted that H . pylori strains have somewhat different morphologies . Strain 26695 is highly helical ( Fig . 1A ) ( similar to KE88-3887 , Fig . 2D ) , with an average of length of 3 . 0 +/− 0 . 5 µm ( n = 72 ) and can be up to 4 . 0 µm in length , while cells of strain 1061 are much shorter with an average of length of 2 . 3 +/− 0 . 5 µm ( n = 100 ) and their helical shape is less pronounced ( compare Fig . 2A ) . Other strains of H . pylori also have varying degrees of cell curvature . In order to study possible functions of genes predicted to encode for cell shape determinants , we inactivated genes HP0059 and HP1143 in H . pylori strains 26695 , KE88-3887 , G27 and 1061 . To ensure expression of the downstream genes , all genes were disrupted by insertion of a cat gene driven by its own promoter but lacking a terminator . Growth analysis of all mutants revealed that inactivation of none of these genes showed any effect on the growth rate of H . pylori . Interestingly , the inactivation of gene HP0059 resulted in the formation of 100% straight rods in strains 26695 , KE88-3887 and G27 ( Fig . 1B , Fig . 2E , and data not shown for G27 ) , or 85% straight cells in strain 1061 ( Fig . 2B ) , revealing a complete loss of the spiral shape in the absence of the HP0059 gene product . To rule out a possible downstream effect on gene HP0060 , HP0060 was disrupted by introducing a pcat cassette . No change in growth or cell curvature could be detected compared with wild type cells ( data not shown ) showing that the loss of helical cell shape is due to the inactivation of gene HP0059 . The same observation was made with strains 1061 , KE88-3887 and G27 ( data not shown ) . Inactivation of HP1143 had a mild effect on cell shape . Whereas 10 to 15% of 26695 wild type cells were straight ( Fig . 1A ) , about 60% of HP1143 mutant cells were straight ( Fig . 1C , or 52% for strain KE88-3887 , Fig . 2F ) . These experiments show that the loss of genes HP0059 or of HP1143 affects cell curvature to different extents . The deletion of HP1143 had an even more dramatic effect on cell shape in 1061 cells , about 70% of the cells were round , oval or irregularly shaped , while the remaining cells were straight or bulgy rod shaped ( Fig . 2C ) . Single non-aggregated cells were basically undetectable . Thus , deletions of genes HP0059 and HP1143 have different effects on cell shape in different strain backgrounds . Absence of HP0059 generates loss of cell curvature in all strains tested , while lack of HP1143 results in a complete loss of cell shape in strain 1061 . H . pylori undergoes a transition from helical cells to coccoid cells upon prolonged starvation . We analysed whether ccrp mutant cells influence this morphological transition , whose mechanism is still poorly understood . Like wild type cells , all HP0059 or HP1143 mutant cells were coccoid 7 days after inocculation ( i . e . 5 days into stationary phase ) , showing that the inactivation of Ccrp encoding genes does not influence the helical to coccoid transition . To investigate if HP0059 and HP1143 are genetically linked , we generated a strain from the parent 26695 , in which both genes are deleted . Interestingly , cells of the double mutant strain displayed a variety of cell shapes: while 65% of the cells were straight , 30% had an irregular curved shape , and 5% had a highly bent shape , such that the cell ends came together ( Fig . 1D ) , which is never observed for wild type cells . For strain KE88-3887 , the double deletion resulted in even more highly bent cells ( suppl . Fig . S1 ) . These findings show that the loss of both Ccrp encoding genes leads to a complete loss of regular cell shape in strains 26695 and KE88-3887 , and exacerbates the phenotype of the single gene deletions . The double deletion of HP0059 and HP1143 in strain 1061 was similar to that of the HP1143 single gene deletion , in that most ( >80% ) double mutant cells were round , oval or irregularly shaped , while the remaining cells were straight or bulgy rod shaped ( data not shown ) . We wished to obtain insight into the biochemical properties of Ccrp proteins . Towards this end , we purified an N-terminally strep-tagged version of Ccrp59 to more than 95% purity ( Fig . 3A ) . Ccrp59 could be purified in very low quantities as a soluble protein upon mild and short time ( 2 h ) induction of the protein in E . coli cells , but appeared in inclusion bodies after prolonged induction . On SDS-PAGE , Ccrp59 migrated as monomer but also as a band that corresponded to a dimer ( Fig . 3A ) , which is apparent in the Western blot in Fig . 3B . When subjected to centrifugation , a major proportion of Ccrp59 appeared in the pellet fraction ( Fig . 3C ) , suggesting that it forms large assemblies . Over time ( i . e . days to weeks ) , the amount of Ccrp59 in the pellet fraction increased ( data not shown ) . When purified fractions were subjected to electron microscopy , it became clear that Ccrp59 forms extended filamentous structures in vitro , in the absence of any added cofactor ( Fig . 4A ) , similar to IF-type proteins [21] , and dissimilar to most other filament forming proteins . However , the fact that Ccrp59 can be purified as soluble protein clearly distinguishes it from IF proteins , which need to be refolded to be obtained in solution ( compare Table 1 for dissimilarities and similarities ) . Filaments were generally straight , and present in bundles or sheets ( Fig . 4A , grey triangles ) . The smallest observable filaments were 10 nm wide and about 50 nm long ( Fig . 4A , black triangles ) ; these may represent single Ccrp filaments . A closer investigation of the bundles showed that they consist of individual filaments ( also 10 nm wide ) that were positioned in parallel , and appeared to have staggered ends ( hatched triangle ) . Bundles could frequently be observed to split into several single - or double filaments ( Fig . 4A , white triangle ) , supporting the idea that Ccrp59 forms bundles or sheets of individual straight filaments . Most Ccrp59 bundles had a length of 120 to 160 nm , but bundles of more than 200 nm were also observed ( Fig . 4A , red triangle ) . The diameter of individual filaments was in the range of 10 nm , similar to IF filaments from eukaryotic cells , while the larger filament bundles had a diameter of 30 to 60 nm . Interestingly , the length of Ccrp59 bundles as well as their width increased with time and with protein concentration . 5 to 7 days after purification , large bundles up to 950 nm length consisting of individual parallel filaments could be seen ( Fig . 4A , lower panels ) , and were still observable after several weeks , showing that these structures are highly stable . Next , we wished to know if Ccrp59 can form filaments in vivo in a heterologous system . Accordingly , we transfected D . melanogaster S2 Schneider cells ( derived from macrophages ) with a Ccrp59-YFP fusion . Straight filamentous structures of 1 . 7 µm±0 . 3 ( n = 9 ) length , which were frequently branched , could be seen soon after induction of transcription of the fusion ( Fig . 5A ) , albeit in few cells . These observations show that the Ccrp59-GFP fusion can form filaments in vivo . Interestingly , upon coinduction of wild type Ccrp59 , straight and branched filamentous structures were observed in more cells ( Fig . 5B ) , which measured 2 . 45 µm±0 . 43 ( n = 42 ) µm on average . At later time points after induction , large aggregates filled the transfected cells , which appeared to consist of large bundles of filaments ( Fig . 5C ) . Importantly , Ccrp59-GFP filaments were of uniform fluorescence over their full length , and were much longer than those seen in the EM . These data show that Ccrp59 forms extended filamentous structures in vitro as well as in vivo in a heterologous system . The observations also suggest that the intracellular concentration of Ccrp59 must be kept at a certain level to avoid crowding of the cytosol by uncontrolled polymerisation of Ccrp59 . In order to obtain information on Ccrp1143 , the protein was purified as Strep-tagged versions analogous to Ccrp59 , and was fully soluble ( Table 1 ) . When subjected to electron microscopy , Ccrp1143 was observed as single straight filaments of 50 to 60 nm length ( Fig . 4B , left panel ) . Interestingly , a change of the purification condition from pH 8 to pH 7 resulted in the formation of structures , which were about 600 nm long and more than 20 nm wide , as well as of round or U-shaped structures of about 50 nm in diameter ( Fig . 4B , right panels , green triangles ) . U-shaped structures were never observed for Ccrp59 , suggesting that they are intrinsic to Ccrp1143 . Therefore , similar to IF proteins [21] , pH conditions considerably affect the ability of Ccrp1143 to form extended filaments ( see Table 1 ) . Like Ccrp59 , Ccrp1143 filaments were still observed several weeks after purification , and thus highly stable structures . These experiments show that both Ccrp proteins form filaments in vitro , which share several properties with IF proteins , but are dissimilar to IF type proteins because both can be purified as soluble proteins without the need for refolding . We wished to obtain insight into the pattern of localization of cytoskeletal elements in live H . pylori cells . We adapted a system for the generation of GFP fusions for Bacillus subtilis cells to H . pylori , which allowed integration of the fusions at the original locus within the chromosome . This strategy was successful with strain 1061 , and in some cases also with 26695 , which does not easily take up and integrate plasmid DNA ( in contrast to linear DNA ) . Ccrp59 was visualized through the generation of a C-terminal GFP fusion that was integrated at the original locus , such that it was expressed under the native promoter , and was the sole source of Ccrp59 within the cells . Cells of strain 26695 expressing Ccrp59-GFP were helical like wild type cells and not straight ( Fig . 6A ) , showing that the fusion was functional , even in the absence of wild type Ccrp59 . Discrete Ccrp59-GFP foci could be detected within exponentially growing cells ( Fig . 6A–E ) . Small cells contained 2 to 3 foci , while the number of foci increased with cell size . Foci were not of uniform fluorescence , but showed different intensities . Foci with high fluorescence intensity ( indicated by grey triangles in Fig . 6A , C and D ) were positioned at relatively regular intervals within the cells , with an average of 0 . 89 µm±0 . 2 ( n = 62 ) between the foci , and were frequently interspersed with foci of low intensity . Imaging of different Z-planes within cells and ensuing 3D deconvolution suggested that some of the foci were connected with each other ( Fig . 6C ) . Due to the low cell diameter of H . pylori ( 0 . 78 µm ) , and because of the weak fluorescence of Ccrp59-GFP ( which allows capturing of only 4–5 Z-planes ) it was not possible to clearly determine if the foci are arranged in a helical pattern ( which some images suggest ) , or in which other pattern . However , the data are compatible with a helical localization of Ccrp59 filaments along the long axis of the cells ( Fig . 6F ) . Ccrp59-GFP also localized in a very similar arrangement in strain 1061 ( Fig . 6D ) , suggesting that the observed localization reflects the true positioning of Ccrp59 in several if not all H . pylori strains . Importantly , time lapse microscopy showed that Ccrp59-GFP signals were not moving through the cells , but were stationary positioned over a period of 4 minutes ( Fig . 6E ) . We did not observe any movement of Ccrp59-GFP foci in any of the 120 cells analysed . Thus , Ccrp59-GFP foci are not freely diffusing elements , supporting the idea that they may constitute cytoskeletal elements that are statically localized along the length of the cells . We have not been able to generate a functional Ccrp1143-GFP fusion . We created a strain derived from 1061 in which a complete Ccrp1143-GFP fusion was integrated into the original locus by single crossover , such that the fusion as well as the wild type gene HP1143 were present within the H . pylori chromosome . Between 40 to 60% of these cells showed abnormal cell shape ( Fig . 6G ) , and contained one to two distinct Ccrp1143-GFP foci at random places within the cell ( data not shown ) , suggesting that the Ccrp1143-GFP fusion is dominant negative . These data reinforce the idea that a loss of function of Ccrp1143 leads to aberrant cell morphology . As mentioned above , H . pylori strains can have different degrees of helical cell curvature and different cell lengths . Occasionally , laboratory strains lose cell curvature altogether and become rod shaped . To investigate if differences in genes encoding for Ccrp proteins may be the basis for this phenomenon , we amplified the gene region of HP0058 up to the beginning of gene HP0060 from different strains and sequenced the PCR products . Interestingly the whole region differs in length from about 1500 bp in strain 26695 , 1600 bp in strain J99 , about 1000 bp in strain 1061 up to only 550 bp in strain SS1 ( mouse adapted ) . This is in agreement with a previous study that showed that HP0059 is among the most divergent genes in H . pylori [22] . Analysing HP0059 ( encoding Ccrp59 ) itself , the size of 855 bp , 984 bp , 750 bp or 500 bp in strains 26695 , J99 , HPAG1 and 1061 , respectively , was determined . Gene jhp0050 ( is similar to HP0059 ) in strain J99 is 663 bp long . Because strain KE88-3887 is a hyper-motile variant of strain 26695 both strains contain the same HP0059 sequence . To our surprise , it was possible to generate a deletion of the mreB gene , through a replacement of the gene with a chloramphenicol acetyltransferase cassette . Therefore we inactivated the mreB gene in three different strains indicating that this result was not strain dependent . The generated mutant cells were able to grow , albeit at strongly reduced growth rate compared with wild type cells . To rule out an effect on the downstream mreC gene , we isolated total RNA from mreB mutants from different H . pylori strains and performed dot-blot hybridization with probes specific for the mreC gene , showing that mreC is expressed in ΔmreB cells like in wild type cells ( Fig . 7A ) , ruling out a polar effect of the disruption of mreB . MreB mutant cells were obtained at a similar frequency compared with many deletions of non essential genes generated in our laboratory [23] , strongly arguing against the generation of secondary suppressor mutations . The growth rate of mreB mutant cells was severely decreased compared with wild type cells for strain 26695 ( Fig . 7B ) and for KE88-3887 and 1061 ( data not shown ) . The growth curves of all wild type strains showed a lag phase of about 8 hours and an exponential increase in cell density until at least 25 h , whereas all mreB mutants ( i . e . in the 3 different strains ) displayed a highly decreased growth rate . Interestingly , there was no change in cell morphology of mreB mutant cells other than cell elongation in comparison with wild type cells ( Fig . 8 , compare A with D for 26695 , B with E for 1061 and C with G for KE88-3887 ) . MreB deleted cells were still helical and had the same average cell diameter of 0 . 78 µm ( n>100 cells ) than that of wild type cells . Cell elongation can be easily seen in Fig . 8F . Interestingly , mreB mutant cells showed a strong defect in the segregation of chromosomes . In contrast to wild type cells of all strain , which contained one , two , or ( rarely ) three well defined nucleoids ( Fig . 8A , B and C ) , mreB mutant cells contained brightly staining bilobed nucleoids and large DNA free cell regions ( Fig . 8D , E and G ) . Similar to C . crescentus smc mutant cells that have a strong segregation defect [24] , no anucleate mreB mutant H . pylori cells were observed . Fluorescence intensity of the bilobed nucleoids in mutant cells was similar to that of separated nucleoids in large wild type cells , while the length of the bilobed nucleoids was twice of that of single segregated nucleoids in wild type cells , showing that the nucleoids in mutant cells contain two largely duplicated chromosomes demonstrating a separation delay . MreB mutant cells from strain 1061 frequently contained a single extended non-segregated nucleoid in spite of the large cell size ( Fig . 8E ) , showing that loss of MreB strongly affects chromosome segregation in H . pylori cells . MreB mutant cells from strain 1061 could reach more than 3 times the normal cell size ( Fig . 8F ) . Blocking of chromosome segregation leads to a delay in cell division in bacteria such as E . coli or B . subtilis [25] , suggesting that most likely , the elongation of cells lacking MreB is due to the defect in chromosome partitioning . To obtain further insight into the function of MreB , we treated H . pylori cells with A22 , which was reported to mediate disassembly of MreB filaments in vivo [26] . Addition of a low amount of A22 ( 10 µg/ml ) to exponentially growing H . pylori cells led to the formation of abnormally shaped nucleoids ( Fig . 8H ) , and the addition of 50 µg/ml A22 resulted in a similar phenotype than the mreB deletion: only 2 doubling times after addition of A22 , nucleoids no longer separated into two ( Fig . 8I ) , and growth proceeded at an extremely slow rate ( Fig . 7B , open triangles ) . Resuspension of cells after A22 treatment into fresh growth medium fully restored growth of cells , showing that interfering with MreB function transiently and rapidly leads to disturbance of the cell cycle , but does not kill the cells under experimental conditions . The fact that A22 treatment resulted in a phenotype that closely resembles that of an mreB deletion reinforces the idea that the phenotype is not masked by a secondary mutation but is due to the inactivation of MreB activity . The lack of MreB did not interfere with the formation of polar flagella ( Fig . 8F , right panel ) . Our data suggest that MreB plays a direct or indirect role in the progression of the cell cycle , but not in cell shape determination . We also examined the possible link between Ccrps and MreB , because the effect of the lack of MreB on cell shape could potentially be masked by the presence of Ccrps . Therefore , we treated HP0059 mutant cells with A22 , and visualized the effect of inhibition of MreB on cell shape . While wild type cells of strain 26695 ( Fig . 8J ) or of strain 1061 ( Fig . 8K ) remained helical during addition of A22 , mutant cells of strain 26695 ( Fig . 8L ) or of strain 1061 ( Fig . 8M ) remained straight and rod shaped like the non-treated cells , and displayed the same degree of growth retardation as the wild type cells . These data support the findings that cell shape is not affected by the loss of MreB activity , but is determined by Ccrp proteins . The persistence of Helicobacter pylori in the hostile environment of the human stomach is ensured by the activity of urease . Urease catalyses the hydrolysis of urea into carbon dioxide and ammonia , which are buffering compounds essential to raises the pH in the microenvironment surrounding the cell [27] and to maintain the pH homeostasis in the bacterial cytoplasm [28] . Therefore , enzyme activity is essential for both early colonization events and for virulence [29] , [30] . To test whether this major pathogenicity factor is affected by cytoskeletal elements , we determined urease activity in mreB mutant cells , and found a statistically significant ( p<0 . 01 ) 2 . 5 fold decrease in activity in strain KE88-3887 ( Fig . 9A ) , and a ∼6 fold decrease in strain 26695 ( data not shown ) . Interestingly , addition of 1 µM NiCl2 restored urease activity up to wt level ( data not shown ) . Western blot analysis showed that the urease level in the mreB mutant strain is similar to or even higher than that in the parental wild type strain ( Fig . 9B ) . It is unclear how MreB exerts its effect on urease activity , but clearly , loss of this cytoskeletal element compromises H . pylori pathogenicity .
This report provides novel insight into the bacterial cytoskeleton and the function of cytoskeletal elements , and shows that the human pathogen H . pylori has a novel type of system for the establishment and maintenance of defined cell morphology . We show that two coiled coil rich proteins ( Ccrp ) are essential for the maintenance of proper cell shape in H . pylori , whereas the actin-like protein MreB is not involved in the generation of helical and/or rod cell morphology , like in many other bacteria . Deletion of gene HP0059 encoding for protein Ccrp59 resulted in the complete loss of helical cell curvature in strains 26695 , KE88-3887 , G27 and 1061 . Loss of a second Ccrp protein , Ccrp1143 , resulted in a mild reduction of cell curvature in strain 26695 . However , in strain 1061 , lack of Ccrp1143 resulted in a complete failure to maintain cell morphology , mutant cells were round or oval , or irregularly shaped . Thus , Ccrp proteins contribute differentially to cell morphology in different H . pylori strains , and are required for the maintenance of cell morphology in H . pylori . Intriguingly , in contrast to mreB and ftsZ , Ccrp encoding genes are highly variable both in terms of their length and in sequence between various H . pylori strains analysed in this study . It is thus plausible to propose that the great variety of cell shapes of H . pylori strains – from small bent cells to large and highly helical cells – stems from the nature of the Ccrp proteins . For example , Ccrp59 is much longer in strain 26695 than in 1061 , which produces smaller and less helical cells than 26695 . Thus , loss of Ccrp1143 in strain 26695 may be compensated for by Ccrp59 , while Ccrp59 of strain 1061 may not be able to do so . Unfortunately , we do not have sophisticated genetic tools at present to test these intriguing ideas , and clearly , the situation is more complicated , because of the differential contribution of Ccrp proteins in different strains . We show that both Ccrp proteins form extended filaments in vitro . Ccrp59 forms bundles of filaments in vitro , in the absence of any added cofactor , and is able to form extended filaments in macrophage cells , and thus in the absence of any cofactor from H . pylori . Ccrp59 bundles clearly consist of parallel stacks of filaments , which appear to be arranged in a staggered fashion , as is proposed to be the case for IF filaments from eukaryotic cells [6] . However , both Ccrp proteins identified in this study are initially soluble proteins when expressed in E . coli cells , and Ccrp59 lacks characteristic N and C terminal domains of IF proteins , showing that Ccrps are distinct from IF proteins . Possibly , Ccrp proteins are evolutionarily older versions of IF proteins , or even unrelated to IFs , and possibly a novel class of cytoskeletal elements in bacteria . Towards a further analysis of Ccrps , we localized Ccrp59 in H . pylori cells . We found that a functional Ccrp59-GFP fusion forms distinct foci , whose position did not change over a time of several minutes , along the length of the cells . Thus , Ccrp59 is not a freely diffusing cytosolic protein , but remains at fixed positions , and may thus serve as a cytoskeletal structure that affects cell morphology . Due to the narrow width of H . pylori cells and the relatively weak fluorescence of Ccrp59-GFP , it was not possibly to unequivocally determine if the foci are arranged in a helical pattern . Because of the fact that Ccrp59 forms extended filaments , which can be longer than H . pylori cells , in vitro , and when expressed in S2 macrophages , we favour the idea that the foci consist of filaments that are connected and run along the long axis of the cells ( Fig . 6F ) . Rigid Ccrp59 filaments could exert force onto the cell membrane and this way lead to a helical twist in the cell wall during synthesis . Alternatively , a helical growth pattern could also be achieved through a possible interaction of Ccrps and proteins that synthesize the cell wall , which would be positioned in a helical arrangement . MreB positions cell wall synthetic enzymes in B . subtilis [31] , but H . pylori MreB clearly does not affect cell shape , so this function could be performed by Ccrps . Coiled coil rich/IF-like protein crescentin in C . crescentus forms a filamentous structure along the short axis of the cell , and likewise actin-like MamK and MamJ in magnetotactic bacteria , which align magnetosomes in a straight line along the short axis of the helical cells [32] , [33] . On the other hand , the cytoskeletal element CfpA , found exclusively in spirochaetes , is part of filaments running along the long axis of the highly helical cells [34] , which even persist and retain their helical path when the cells are gently lysed . Interestingly , CfpA is also predicted to contain a high degree of coiled coils . It will be important to determine the nature of the foci formed by Ccrp59-GFP within the cells , and to identify factors that interact with Ccrps in H . pylori , to find out how the proteins mediate the generation of helical curvature of the cells . In C . crescentus , the IF-like protein crescentin is essential for the generation of cell curvature [19] , while MreB is indispensable for the maintenance of rod shape , in striking contrast to H . pylori , where cell shape depends on two Ccrps , but not on MreB . Moreover , Ccrp59 is clearly different from crescentin , because crescentin forms individual long filaments [19] , and not parallel bundles of filaments like Ccrp59 . In S . coelicolour , the filament-forming coiled coil rich protein FilP affects cell rigidity , but not cell shape [35] , while MreB is involved in differentiation ( sporulation ) , but does not play a role during vegetative growth [36] . Our findings show that H . pylori employs a novel concept for the generation of complex cell shape and suggest that Ccrp proteins may set up complex cell shape in many other bacteria that contain MreB ( which may serve different functions ) , and also in bacteria lacking mreB , such as Corynebacterium , which is rod shaped . We also addressed the question of the function of MreB in H . pylori . MreB mutant H . pylori cells are viable , but grow much more slowly than wild type cells . Strikingly , mutant cells contained non-segregated but strongly fluorescent ( and thus duplicated ) chromosomes , and were highly elongated . Because a defect in chromosome segregation leads to a delay in cell division , cell elongation in mreB mutant cells most likely stems from the delay in cell cycle progression . Thus , in H . pylori , MreB affects chromosome segregation , but not cell shape , while in other bacteria , the observed defect in chromosome segregation may be due to an indirect effect caused by the loss of cell shape . Strikingly , mreB mutants contain considerably lower levels of urease activity , whereas the amount of urease is unchanged . At present , we have no clear indication as to how MreB might affect the activity of an enzyme . Possibly , MreB affects the activity of membrane proteins such as transporters , and the absence of MreB may thereby change intracellular levels of metals and ions . Indeed , a deletion of mreB in B . subtilis can be rescued by the addition of high concentrations of magnesium and sucrose [18] , and urease activity in H . pylori mreB mutant cells can be rescued by an increase in the concentration of nickel , which is a limiting factor for the enzyme [37] . In any event , our findings severely alter the spectrum of cellular functions affects by MreB . Because high urease activity is a prerequisite for colonization and persistence of Helicobacter pylori in the hostile environment of the human stomach , we establish for the first time a connection , directly or indirectly , between the bacterial cytoskeleton and a pathogenicity factor . To verify the different contributions of Ccrps and MreB in H . pylori , we added the MreB inhibitor A22 to HP0059 mutant cells . The addition of A22 resulted in slow growth in the mutant cells , which however retained their rod cell shape . Therefore , cytoskeletal elements in H . pylori strongly affect cell shape ( Ccrps ) and growth/pathogenicity ( MreB ) , which emphasizes the potential to generate antibacterial chemicals by screening for compounds that affect the assembly of MreB and Ccrp proteins . The study of H . pylori at the level of cell biology and the investigation of its cytoskeleton has revealed a novel type of system for cell shape maintenance , and point to additional interesting features of its cell cycle that deserve further investigation .
Bacterial strains are listed in suppl . Table S1 . H . pylori strains were routinely cultivated on Dent blood agar in a microaerobic atmosphere as described earlier [37] . Growth experiments were performed in Brucella broth with 5% fetal calf serum ( BBF ) . Bacteria were precultured to an optical density at 600 nm ( OD600 ) of approximately 1 . 0 in BBF and subsequently diluted 1∶150 in test media . Growth rate was assessed by optical density ( OD600 ) . All growth experiments were performed in triplicate and were repeated at least three times . E . coli strains were grown aerobically at 37°C in Luria-Bertani medium . When appropriate , growth media were supplemented with 50 µg/l ampicillin ( Ap ) or 20 µg/l chloramphenicol ( Cm ) . Restriction and modifying enzymes ( New England Biolabs , USA ) were used according to the manufacturer's instructions . Cloning was performed in E . coli according to standard protocols . Plasmids were isolated with a QIAprep Spin Miniprep Kit from Qiagen ( Qiagen 27104 ) . The chloramphenicol-acetyl-transferase gene catGC with ( Pcat ) promoter were amplified by PCR from plasmid pTnMax5 ( suppl . Table S1 ) using primer CATS1 in combination with the primer CATAS1 ( suppl . Table S2 ) . The Pcat gene were fused to upstream and downstream DNA regions of mutagenized genes by using a modified version of the megaprimer PCR protocol [38] , [39] as described earlier [23] , [40] , [41] . Marker exchange mutagenesis of H . pylori was performed by electroporation or natural transformation according to standard procedures [42] . H . pylori mutants carrying the Pcat gene inserted into the chromosome were selected by growth on Dent blood agar containing chloramphenicol ( Cm ) at concentrations of 20 mg/l . Correct insertion of cat and Pcat was verified by PCR analysis with appropriate primers listed in suppl . Table S2 . All fluorescent tag vectors ( see Protocol S1 ) were integrated into the H . pylori chromosome via single crossover integration , which was verified by PCR . D . melanogaster S2 Schneider cells were grown in Schneider's Drosophila medium ( Lonza Group Ltd . ) supplemented with 5–10% fetal calf serum ( FCS ) at 25°C without addition of CO2 . Cells were passaged every 2 to 3 days to maintain optimal growth . S2 cells were transfected using the cationic lipid Cellfectin ( Invitrogen ) . The S2 cells were spread in a 6-well plate at 1×106 per well in 3 ml medium with 5% FCS . Supercoiled plasmids ( 0 . 3 µg of each plasmid ) were complexed with lipid ( 10 µl Cellfectin reagent ) in 200 µl serum-free medium . The complex was incubated at room temperature for 15 min , filled up with serum-free medium to 1 ml and was added to cells from which the growth medium had been removed ( cells were washed once with serum-free medium ) . After 18 hrs , the supernatant was removed and replaced by 3 ml of medium containing 5% FCS . After further incubation for 24 hrs , the production of the proteins was induced by adding CuSO4 to a final concentration of 1 mM . Recombinant versions of the H . pylori HP0059 and HP1143 proteins were produced in E . coli using the StreptagTM protein expression system from IBA ( Göttingen , Germany ) according to the manufacturer's instructions ( http://www . iba-go . de ) . The coding sequences from H . pylori strain 26695 were amplified using the primer pairs listed in Table S2 and cloned via the BsaI restriction sites added as 5′-extensions ( underlined ) into plasmid pASKIBA-7TM ( IBA-Göttingen ) . The plasmids were transferred to E . coli BL21 and expression was induced with 0 . 2 mg/l tetracycline . The bacteria were harvested by centrifugation and the recombinant proteins were purified to homogeneity on a Strep-TactinTM column according to the manufacturers' instructions . In case of HP1143 the coding sequence from H . pylori strain 26695 was amplified using the primer pairs listed in Table S2 with the Streptag sequence integrated and cloned via the NcoI and PstI restriction sites into plasmid pETDuet-1 ( Novagene ) . Protein expression was performed according to the manufacturer's instructions . For protein purification at pH 7 , buffer W ( 100 mM Tris/HCl pH 8 , 150 mM NaCl , 1 mM EDTA ) as well as the buffer E ( 100 mM Tris/HCl pH 8 , 150 mM NaCl , 1 mM EDTA , 2 . 5 mM Desbiotin ) were adjusted to pH 7 . Spin down assays were performed as follows: 20 µl of purified protein fractions in buffer W ( usually 24 h after elution , with storage at 4°C ) were centrifuged at 13000 rpm in a bench centrifuge , after removal of the supernatant , the pellet was resuspended in 20 µl buffer W . SDS sample buffer were added and equal volumes of supernatant and pellet were subjected to SDS PAGE analysis . Urease activity was determined in fresh lysates by measuring ammonia production from hydrolysis of urea , as described previously [37] , [43] . The concentration of ammonia in the samples was inferred from a standard NH4Cl concentration curve . Enzyme activity was expressed as µmol urea substrate hydrolysed min−1 ( mg protein ) −1 . Elution fractions of the Streptag purification and from gel filtration were applied to 200 mash copper grids and were negatively stained with 2% phosphotungstic acid pH 2 . 7 or with 1% uranyl acetate . Filaments were visualized under a Philipps/FEI CM10 ( 80000V ) electron microscope equipped with a Bioscan Camera . Images were processed with Digital Micrograph ( Gatan ) software . Fluorescence microscopy was performed on a Zeiss Axioimager microscope using a 100×Objective with A = 1 . 45 . Cells were mounted on agarose gel pads on object slides . Images were acquired with a digital CoolSnap HQ CCD camera; signal intensities and cell length were measured using the Metamorph 6 . 3 program ( Universal Imaging Corp . , USA ) . 3D deconvolution was done using Autdeblur software . DNA was stained with 4′ , 6-diamidino- 2-phenylindole ( DAPI; final concentration 0 . 2 ng/ml ) and membranes were stained with FM4–64 ( final concentration 1 nM ) . Filters used were: DAPI – ex360–370 , dc400 , em420–460 , GFP – ex460–495 , dc505 , em510–550 , FM4–64 ex480–550 , dc570 , em590 . For acquisition of Z-stacks , 20 planes with a spacing of 0 . 2 µm were taken from bottom to top , or reverse . Signal intensities were measured in Metamorph program . | The human pathogen Helicobacter pylori lives in the hostile environment of the human stomach . H . pylori possesses a spiral shape and high motility that enable the bacterium to swim through the stomach lumen and to come into close contact with epithelial cells . High urease activity in the bacterium counterbalances the low pH within the stomach , in order to persist within the viscous mucus layer . In this work , we analysed the molecular basis of the spiral structure of H . pylori . We demonstrate that the helical cell shape depends on so called coiled coil rich proteins ( Ccrp ) , which form extended filamentous structures in vitro and in vivo , and are differentially required for the maintenance of proper cell morphology . In most bacteria analysed so far , the actin-like protein MreB affects cell morphology . Contrarily , H . pylori MreB is not involved in the maintenance of cell shape , but affects the progression of the cell cycle . Mutant cells were highly elongated , characteristic for a delay in cell division , and contained non-segregated chromosomes . The persistence of H . pylori in the hostile environment of the human stomach depends on the activity of urease . Interestingly , mreB mutant cells displayed significantly reduced urease activity , revealing a novel connection between the cytoskeletal element and an enzyme , and thus with pathogenicity . These experiments show that H . pylori has a novel type of system setting up helical cell shape , which has not yet been described for any bacterium . Our work will allow studying H . pylori cell cycle and pathogenicity at a new visual level . | [
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] | 2009 | A Novel System of Cytoskeletal Elements in the Human Pathogen Helicobacter pylori |
Noroviruses are the principal cause of epidemic gastroenteritis worldwide with GII . 4 strains accounting for 80% of infections . The major capsid protein of GII . 4 strains is evolving rapidly , resulting in new epidemic strains with altered antigenic potentials . To test if antigenic drift may contribute to GII . 4 persistence , human memory B cells were immortalized and the resulting human monoclonal antibodies ( mAbs ) characterized for reactivity to a panel of time-ordered GII . 4 virus-like particles ( VLPs ) . Reflecting the complex exposure history of the volunteer , human anti-GII . 4 mAbs grouped into three VLP reactivity patterns; ancestral ( 1987–1997 ) , contemporary ( 2004–2009 ) , and broad ( 1987–2009 ) . NVB 114 reacted exclusively to the earliest GII . 4 VLPs by EIA and blockade . NVB 97 specifically bound and blocked only contemporary GII . 4 VLPs , while NBV 111 and 43 . 9 exclusively reacted with and blocked variants of the GII . 4 . 2006 Minerva strain . Three mAbs had broad GII . 4 reactivity . Two , NVB 37 . 10 and 61 . 3 , also detected other genogroup II VLPs by EIA but did not block any VLP interactions with carbohydrate ligands . NVB 71 . 4 cross-neutralized the panel of time-ordered GII . 4 VLPs , as measured by VLP-carbohydrate blockade assays . Using mutant VLPs designed to alter predicted antigenic epitopes , two evolving , GII . 4-specific , blockade epitopes were mapped . Amino acids 294–298 and 368–372 were required for binding NVB 114 , 111 and 43 . 9 mAbs . Amino acids 393–395 were essential for binding NVB 97 , supporting earlier correlations between antibody blockade escape and carbohydrate binding variation . These data inform VLP vaccine design , provide a strategy for expanding the cross-blockade potential of chimeric VLP vaccines , and identify an antibody with broadly neutralizing therapeutic potential for the treatment of human disease . Moreover , these data support the hypothesis that GII . 4 norovirus evolution is heavily influenced by antigenic variation of neutralizing epitopes and consequently , antibody-driven receptor switching; thus , protective herd immunity is a driving force in norovirus molecular evolution .
Noroviruses ( NoVs ) are the leading cause of severe viral gastroenteritis and are responsible for 50% of all acute gastroenteritis outbreaks in the United States and Europe [1] . Although the severity of disease is usually moderate , lasting 1–3 days , infection can be especially virulent in young children , the elderly , and the immunocompromised , with the latter group experiencing chronic diarrhea and virus shedding for over a year [2]–[8] . Importantly , it is estimated that 200 , 000 people die each year from norovirus infections , primarily children in the developing world [9] . An effective vaccine would be particularly advantageous for the very young and aged populations , military personnel , children and healthcare providers , food handlers , cruise ship passengers , and populations of the developing world [10] . Immunotherapeutics are especially needed for treating immunosuppressed populations experiencing long-term infections with chronic diarrhea . The lack of understanding of the extensive antigenic relationships among the large number of norovirus strains and the complex relationship between host protective immunity and virus antigenic heterogeneity are the primary obstacles to norovirus vaccine development . Noroviruses are ∼38 nm icosahedral viruses with a ∼7 . 5 kb single-stranded , positive-sense RNA genome that contains three large open reading frames ( ORFs ) . ORF1 encodes the non-structural proteins , while ORFs 2 and 3 encode the major and minor capsid proteins respectively . Expression of the major capsid protein ( ORF2 ) in Venezuelan equine encephalitis ( VEE ) virus or baculovirus results in the formation of virus-like particles ( VLPs ) composed of 90 copies of the major capsid protein dimer [11] . Noroviruses are grouped by the amino acid sequence of the major capsid protein: viruses with less than 14 . 3% difference are classified as the same strain , 14 . 3–43 . 8% difference as the same genotype , and 45–61 . 4% difference as the same genogroup [12] . Currently , noroviruses are grouped into five genogroups ( GI–GV ) . Genogroups GI and GII are responsible for most human infections and are further subdivided into 8 and 21 different genotypes , respectively [1] , [12] . Structurally , the capsid monomer is divided into three domains . The shell domain ( S ) forms the core of the particle and the protruding domain ( P ) extends away from the core . The P domain is further subdivided into the P1 subdomain ( residues 226–278 and 406–520 ) and the P2 subdomain ( residues 279–405 ) [11] . The P2 subdomain is the most exposed region of the viral particle and is well positioned to interact with potential neutralizing antibodies and histoblood group antigen ( HBGA ) ligands [13]–[17] . Previous studies have shown that the P2 subdomain of the major capsid protein of GII . 4 strains is evolving rapidly , resulting in new epidemic strains with altered carbohydrate ligand binding properties and antigenicity [13] , [18]–[23] . For the past two decades , the majority of norovirus outbreaks have been caused by strains within the genogroup II , genotype 4 ( GII . 4 strains ) subcluster . Between 1995 and 2006 , four major norovirus pandemics associated with GII . 4 strains were characterized using molecular epidemiologic methods . During the mid-1990's [24] strain US95/96 was responsible for ∼55% of the norovirus outbreaks in the USA and 85% of the outbreaks in the Netherlands [25] . In 2002 , the US95/96 strain was replaced by the Farmington Hills strain [26] , which was associated with ∼80% of norovirus outbreaks [27] in the USA . In 2004 , the Hunter GII . 4 variant was detected in Australia , Europe , and Asia [28]–[30] . Hunter strains were largely replaced in 2006 by two new co-circulating GII . 4 variants in the USA and Europe , Laurens ( 2006a ) and Minerva ( 2006b ) [5] , [29] , [31] . Although similar to Minerva , Apeldoorn317 ( GII . 4 . 2008 , GenBank accession no . AB445395 ) represents a new evolutionary cluster in the phylogeny of the GII . 4 viruses . Most recently , a new GII . 4 . 2006 variant , GII . 4 . 2009 New Orleans , has been the predominate outbreak strain , although GII . 4 . 2006 Minerva continues to circulate at low levels [1] , [32] . A variety of studies using time ordered human outbreak sera and mouse monoclonal antibodies support the hypothesis that the GII . 4 noroviruses are undergoing antigenic variation and that this variation contributes to the emergence of new outbreak strains over time [13] , [22] , [33] , [34] . However , the lack of a cell culture or small animal model for human norovirus cultivation restricts study of neutralization antibodies and epitopes . To circumvent this problem , highly informative in vitro assays have been developed that measure the ability of an antibody to “block” binding of a VLP to a carbohydrate ligand [13] , [35] , [36] . This assay is highly sensitive , as it differentiates between norovirus strains too similar to be distinguished by enzyme immunoassay ( EIA ) . The clinical relevance of the blockade assay , as a surrogate neutralization assay , has been confirmed in both infected chimpanzees [37] and Norwalk virus-infected humans [10] , [38] . For NoV strains that hemagglutinate RBCs , high blockade antibody titers that prevent hemagglutination also correlate with protection from disease in humans [39] . Using human norovirus outbreak sera , VLP-immunized mouse sera , and mouse mAbs [13] , [33] , [34] , the early GII . 4 strains ( 1987 and 1997 ) were antigenically indistinguishable from each other by EIA and surrogate neutralization assays . VLPs of strains circulating post 2002 had significantly less reactivity with sera directed against earlier strains and no reactivity to mouse mAbs directed to GII . 4 . 1987 . Conversely , select mouse mAbs generated against GII . 4 . 2006 reacted with VLPs that circulated only from 2002 or later . No blockade epitopes were found to be in common between GII . 4 . 1987 and GII . 4 . 2006 . Prior to this work , we and others had predicted GII . 4 antibody epitopes using bioinformatic techniques . As expected , discreet amino acids are repeatedly identified as potential evolving epitopes . In particular , residues 296–298 and 393–395 are consistently identified as putative epitopes that change between epidemic GII . 4 strains . Additional surface residues at 333 , 340 , 356 , 368 , 372 , 407 and 412–413 were also predicted as potential antibody epitopes [13] , [18] , [19] , [22] , [28] , [40]–[42] . These amino acids tend to cluster on loops and ridges of the P2 subdomain where antibody interaction would be most accessible . Beyond bioinformatics predictions , only a few studies have shown empirical evidence mapping GII . 4 antigenic change . Allen et al . [42] compared the reactivity of five monoclonal antibodies against a pre and post-2002 epidemic GII . 4 strain , and identified conformational epitopes composed of residues 294–296 and 393–395 . The carbohydrate blockade potential of these antibodies was not reported , so the role of these sites in escape from herd immunity was unclear . However , the finding that residues 393–395 were antigenically important supported our previously published work identifying amino acid 395 as an antigenic determinant in the GII . 4 . 2002 Farmington Hills strain [13] . Using mouse mAbs and molecular biology approaches to exchange predicted epitopes between GII . 4 strain backbones , we have clearly identified amino acids 294 , 296–298 , 368 and 372 to comprise an evolving blockade epitope , as exchange of these amino acids from GII . 4 . 1987 into GII . 4 . 2006 conferred binding of mAbs that recognize GII . 4 . 1987 but not GII . 2006 [43] . Extending this approach , we have also confirmed amino acids 407 , 412 and 413 to constitute a GII . 4 . 2002 Farmington Hills-specific blockade epitope [17] . These empirical studies support the validity of using computational analysis to guide norovirus epitope studies . Comparing reactivity of polyclonal sera collected from immunized mice and infected humans suggested antigenic variation within the GII . 4 noroviruses [13] , [33] . The development of mouse mAbs to different time-ordered GII . 4 VLPs has greatly facilitated progress towards understanding the complex antigenic relations among these strains by clearly demonstrating antigenic variation over time and epidemic strain [34] , [42] , [43] . However , to maximally define the mechanistic relationships that exist between antigenic variation , immunity , and HBGA binding patterns noted in the GII . 4 noroviruses in the context of natural infection history , the cross reactivity patterns , blockade responses , and epitope targets of human anti-GII . 4 monoclonal antibodies are needed . Robust approaches exist for the isolation of human monoclonal antibodies that are elicited following virus infection . Using human PBMCs as a source of memory B cells , we created a panel of human mAbs directed against GII . 4 strains and compared the reactivity of these mAbs to a panel of time-ordered GII . 4 VLPs using EIAs and surrogate neutralization assays . We identified one novel , broadly cross reactive antibody that differentially blocks GII . 4 . 1987 through 2009 VLP interactions with carbohydrate ligands , a potential immunotherapeutic for the treatment of acute or chronic GII . 4 disease . We also defined unique antibody interactions with two different surface exposed epitopes that evolve over time . Importantly , antigenic variation in one of these epitopes correlated with changing carbohydrate ligand binding patterns over time , supporting the proposed relationship between epitope escape from human herd immunity and changing HBGA usage for virus docking [13] . In addition to defining the first human monoclonal antibodies with therapeutic potential for treating acute and chronic NoV GII . 4 infections , these data support the hypothesis that GII . 4 norovirus evolution results in antigenic drift of neutralizing epitopes and consequently , antibody-driven HBGA receptor switching; thus , protective herd immunity is a driving force in norovirus evolution .
The development of mouse mAbs against different time-ordered GII . 4 VLPs has greatly facilitated understanding of the complex antigenic relations between these strains by clearly demonstrating antigenic variation over time and by epidemic strain [34] . However , understanding of the human anti-GII . 4 norovirus antibody response is essential not only for understanding the complex relationships between host immunity and virus antigenic change , but also for rational vaccine design based on defined neutralizing epitopes . Therefore , we developed a panel of human anti-GII . 4 norovirus monoclonal antibodies to begin to characterize GII . 4 antibody reactivity in the native virus host under natural infection conditions , noting that the norovirus pre-exposure histories in human volunteers are unknown and can only be inferred by human sera cross-reactive antibody binding and blockade patterns using time-ordered VLPs representing different outbreak and pandemic strains ( Table 1 ) [13] , [33] . Plasma and PBMC samples from 63 healthy individuals were collected in early 2009 and plasma binding titers ( ED50 ) were measured by EIA against a panel of 6 different norovirus VLPs representing GI and GII strains ( Figure 1 ) . The majority of tested samples reacted by EIA with variable ED50 titers to the panel of VLPs tested ( Figure S1 ) . One sample ( Donor NVB ) was shown to react strongly with GII VLPs and was therefore chosen for further characterization and isolation of norovirus-specific mAbs . The NVB plasma sample was tested again by EIA against a larger panel of norovirus VLPs and shown to react with the entire panel of GII . 4 VLPs representing epidemic strains from 1987 to 2009 ( Table 2 and Figure S2 ) . Plasma did not react with GI . 1 VLPs . Plasma reactivity to VLPs representing genogroup II strains outside the GII . 4 genocluster was variable by strain . NVB plasma efficiently blocked pig gastric mucin ( PGM ) binding of each of the GII . 4 VLPs ( Figure 2 ) . However , significantly less plasma was needed to block GII . 4 . 2006 binding to PGM ( EC50 0 . 0353% plasma ) than was needed to block the other GII . 4 VLPs binding to PGM ( EC50 range 0 . 0673–0 . 1791% plasma ) , supporting an association between the donor plasma titers and the prevalence of global circulating NoV strains . Having demonstrated antibody responses to the complete GII . 4 panel , memory B cells from this PBMC donor were EBV-immortalized and seven anti-GII . 4 mAbs were isolated and characterized . Of note , all seven mAbs were isotype IgG1 , agreeing with previous observations of a predominantly Th1 mediated immune response to norovirus in challenged volunteers ( data not shown and [36] , [44] ) . None of the antibodies recognized GI VLPs ( data not shown and Table 2 and Figure S2 ) . EIA reactivity was limited to GII . 4 strains for mAbs NVB 114 , 97 , 111 , 43 . 9 and 71 . 4 . Monoclonal Abs 37 . 10 and 61 . 3 extended reactivity to include additional VLPs from GII . 1 , GII . 2 and GII . 12 genoclusters ( Table 2 and Figure S2 ) . The reactivity of mAbs between GII . 4 VLPs varied , but could be grouped into time-related clusters for four of the seven human mAbs . The remaining three mAbs demonstrated broad GII . 4 reactivity . Human mAb NVB 114 reacted by EIA and blockade assay exclusively with GII . 4 . 1987 and GII . 4 . 1997 ( Table 2 , Figure 3 , and Figure S2 ) . Significantly more antibody was needed to block GII . 4 . 1997-PGM binding ( EC50 0 . 4152 µg/ml ) than GII . 4 . 1987-PGM binding ( EC50 0 . 3414 µg/ml ) ( Figure 3B ) ( p<0 . 05 ) , supporting the hypothesis that subtle antigenic differences exist between these strains . In contrast to the early strain GII . 4 reactivity of NVB 114 , EIA of human mAb NVB 97 exclusively recognized VLPs of contemporary circulating ( 2004–2009 ) GII . 4 strains ( Table 2 and Figure S2 ) ; VLPs representing GII . 4 strains circulating prior to 2004 were not recognized by NVB 97 . Accordingly , the NVB 97 blocked VLP-PGM interaction of GII . 4 . 2005 , 2006 and 2009 VLPs ( Figure 4 ) . A comparable blockade assay for GII . 4 . 2004 is not available , as our strain doesn't bind carbohydrate ligand under our conditions of treatment [13] , [17] , [34] . However , under standard conditions , the EC50 for GII . 4 . 2006 ( 0 . 1195 µg/ml ) was significantly less than the EC50 of GII . 4 . 2005 ( 0 . 1559 µg/ml ) and GII . 4 . 2009 ( 0 . 1810 µg/ml ) ( Figure 4B ) ( p<0 . 05 ) . These data are consistent with the hypothesis that the contemporary 2009 Minerva variant may be diverging antigenically from its 2006 Minerva variant ancestral strain . The difference in blockade sensitivity of GII . 4 . 2006 and GII . 4 . 2009 to NVB 97 provides the first evidence of subtle antigenic divergence between two Minerva variants , each of which caused widespread outbreaks globally [1] . This observation is further supported by Human mAbs NVB 111 and NVB 43 . 9 reactivity profiles . By single-dilution EIA , NVB 111 specifically reacted to 2006 but minimally with the 2009 variant of Minerva and other tested VLPs ( Table 2 and Figure S2 ) . Accordingly , NVB 111 required 13-fold more antibody to block GII . 4 . 2009-PGM interaction ( EC50 9 . 953 µg/ml ) than it required to block GII . 4 . 2006-PGM interaction ( EC50 0 . 7376 µg/ml ) ( Figure 5A and B ) ( p<0 . 05 ) . In comparison , NVB 43 . 9 specifically recognized both the 2006 and 2009 Minerva variants by EIA ( Table 2 and Figure S2 ) . The interaction of both variants with PGM ligand was efficiently blocked by NVB 43 . 9 ( Figure 5C and D ) . At relatively low antibody concentrations , NVB 43 . 9 did significantly differentiate GII . 4 . 2006 from GII . 4 . 2009 ( EC50 0 . 1031 and 0 . 1739 µg/ml , respectively ) . Combined , these three human mAbs ( NVB 97 , 111 , and 43 . 9 ) indicate that GII . 4 . 2006 and GII . 4 . 2009 are diverging from each other at the antigenic level , but that significant 2006 blockade epitopes are still preserved , suggesting that additional evolution is needed prior to the emergence of an antigenically distinct , new pandemic strain . NVB 114 , 97 , 111 , and 43 . 9 recognize blockade epitopes that are evolving over time ( Figures 3–5 ) . Three additional antibodies recognize epitopes that are highly conserved over time . Human mAbs NVB 37 . 10 and 61 . 3 exhibited broad GII reactivity , detecting VLPs from GII . 1 , GII . 2 , GII . 3 and GII . 12 genoclusters and the entire panel of time-ordered GII . 4 ( 1987–2009 ) VLPs ( Table 2 and Figure S2 ) . Despite broad EIA reactivity , NVB 37 . 10 and 61 . 3 did not efficiently block VLP-PGM interactions for any GII . 4 VLP tested ( Figures 6A and B ) . In contrast , human mAb NVB 71 . 4 recognized the entire time-ordered GII . 4 VLP panel but was unreactive with any other GII VLPs ( Table 2 and Figure S2 ) . Remarkably , NVB 71 . 4 blocked VLP-PGM interaction of each of the GII . 4 VLPs ( Figure 6C ) . The blockade potential varied between the VLPs . GII . 4 . 2002 and GII . 4 . 2006 had similar EC50 values ( 1 . 095 and 0 . 9233 µg/ml , respectively ) , while significantly less antibody was needed for blockade of GII . 4 . 1987 ( EC50 0 . 4506 µg/ml ) and GII . 4 . 2009 ( EC50 0 . 2716 µg/ml ) and significantly more antibody was needed to block GII . 4 . 1997 ( EC50 13 . 73 µg/ml ) and GII . 4 . 2005 ( EC50 3 . 544 µg/ml ) ( Figure 6D ) . These three human mAbs indicate the existence of conserved GII . 4 epitopes over the past twenty-five years and across three pandemic strains that could serve as targets for broad-based vaccine design . Importantly , NVB 71 . 4 represents the first potential , broad spectrum immune-therapeutic for any NoV . In addition to VLP-PGM interaction blockade assay , human mAbs were also tested for blockade of VLP-synthetic biotinylated HBGA ( Bi-HBGA ) interaction and ability to block VLP hemagglutination of O+ RBCs . Regardless of substrate ( PGM or Bi-HBGA ) , the dose-response profiles for all blockade antibodies and VLPs were similar ( compare Figures 3–6 to Figure 7 ) . Reflecting valency differences in the number of potential binding sites of HBGA in the two substrates , the EC50 values differed between assays ( compare Tables S1 and S2 ) . NVB 114 blocked only GII . 4 . 1987 ( EC50 0 . 1054 µg/ml ) and GII . 4 . 1997 ( EC50 0 . 3275 µg/ml ) , with 1997 blockade requiring significantly more mAb ( p<0 . 05 ) . NVB 97 blocked only GII . 4 . 2005 ( EC50 0 . 1835 µg/ml ) , 2006 ( EC50 0 . 0668 µg/ml ) , and 2009 ( EC50 0 . 1732 µg/ml ) with blockade of GII . 4 . 2005 and 2009 requiring significantly more mAb than the blockade of GII . 4 . 2006 ( p<0 . 05 ) . NVB 111 and 43 . 9 blocked only GII . 4 . 2006 ( EC50 0 . 3324 and 0 . 05406 µg/ml , respectively ) and 2009 ( EC50 2 . 727 and 0 . 1140 µg/ml , respectively ) with significantly more mAb needed to block 2009 for both antibodies ( p<0 . 05 ) . Importantly , the broad blockade phenotype of NVB 71 . 4 was reproduced in the Bi-HBGA blockade assay . The EC50 value varied by VLP and ranged from 0 . 0906 µg/ml for GII . 4 . 1987 to 1 . 219 µg/ml for GII . 4 . 2005 . Agreeing with the PGM assay , only GII . 4 . 2002 ( EC50 0 . 1679 µg/ml ) and GII . 4 . 2006 ( EC50 0 . 2039 µg/ml ) were blocked similarly ( p>0 . 05 ) . NVB 37 . 10 and 61 . 3 , the two mAbs that did not block PGM interaction of any tested VLP , both blocked GII . 4 . 2009 interaction with synthetic Bi-HBGAs by at least 50% ( Figure 7E and F ) , although EC50 titers were relatively high ( EC50 0 . 9753 and 1 . 581 µg/ml for NVB 37 . 10 and 61 . 3 , respectively ) , compared to the amount of antibody needed to block GII . 4 . 2009 by the strain-specific mAbs ( EC50 0 . 1140 and 0 . 1732 µg/ml for NVB 43 . 9 and 97 ) . Repeated testing with PGM as substrate did not replicate the findings with synthetic carbohydrate substrates ( Figure 6A and B ) . An additional measurement of antibody blockade ability uses RBCs as the VLP binding substrate . Previous work has demonstrated that Norwalk virus VLPs hemagglutinate ( HA ) O+ RBCs , that this interaction can be disrupted by antibodies found in polyclonal serum ( hemagglutination inhibition; HAI ) , and that the HAI titer of serum correlates with antibody blockade of VLP-Bi-HBGA interaction [38] , [39] , [45] . To determine if these findings could be extended to study GII . 4 VLP blockade , we first tested each GII . 4 VLP for hemagglutination ability . In contrast to Norwalk VLPs , which demonstrated robust HA activity , VLPs of GII . 4 . 1987 , 1997 , and 2009 did not reproducibly HA O+ RBCs ( data not shown ) . GII . 4 . 2002 , 2005 and 2006 did HA O+ RBCs , and VLP HA was inhibited by NVB plasma ( HAI 0 . 01% plasma for GII . 4 . 2002 and 2005 and 0 . 001% plasma for GII . 4 . 2006 ) ( Table S3 ) . Neither NVB plasma nor any of the mAbs inhibited Norwalk virus VLP HA . In agreement with the other two blockade assays , GII . 4 . 2006 VLP HA of O+ RBCs was blocked by NVB 97 ( HAI 0 . 07 µg/ml ) , 111 ( HAI 0 . 5 µg/ml ) , and 43 . 9 ( HAI 0 . 04 µg/ml ) while HA of O+ RBCs by GII . 4 . 2002 was unaffected by these mAbs at 0 . 5 µg/ml . NVB 97 also inhibited GII . 4 . 2005 HA ( HAI 0 . 13 µg/ml ) but not GII . 4 . 2002 . The HAI profile of the cross-reactive mAbs had a weaker correlation with the blockade assays . NVB 71 . 4 and 37 . 10 each inhibited HA of GII . 4 . 2005 ( HAI 0 . 5 and 0 . 25 µg/ml ) and 2006 ( HAI 0 . 13 and 0 . 25 µg/ml ) . NBV 61 . 3 only inhibited HA of GII . 4 . 2002 at 0 . 25 µg/ml . Our previous work with mouse-derived anti-norovirus mAbs suggested that blockade epitopes are conformation dependent [17] , [34] . To test the effect of protein conformation of human mAb binding , we used both Western blot and EIA analysis to compare antibody binding to GII . 4 . 2006 VLPs and P proteins . P proteins of GII . 4 . 2006 are composed of the C-terminal portion of the major capsid protein ( amino acids 221–531 ) [21] . Expression of the P protein in E . coli results in small particle formation estimated to consist of 12 P dimers that reportedly maintains VLP characteristics in carbohydrate and antibody binding studies [46] , [47] . None of the human anti-GII . 4 mAbs recognized either the denatured VLP or P protein by Western blot analysis , suggesting that the epitopes for these antibodies are conformation dependent ( data not shown ) . Surprisingly , only half of the mAbs that recognized GII . 4 . 2006 VLP ( Figure 8A ) by EIA also recognized GII . 4 . 2006 P protein by EIA ( Figure 8B ) . NVB 71 . 4 and 61 . 3 extended their broad reactivity to P proteins , whereas NVB 37 . 10 did not , indicating that a minimum of three GII . 4 cross-reactive epitopes must exist . NVB 97 also detected P protein by EIA . Neither of the Minerva variant mAbs recognized P protein even at protein concentrations 8-fold above standard EIA conditions ( 1 µg/ml coating protein ) . Further , all seven mAbs detected increasing concentrations of VLP in a linear dose response with signals saturating at 4 µg/ml of VLP when the mAb concentration was held at 1 µg/ml , which is our standard EIA antibody titer ( Figure 8A ) . Antibody reactivity to the P protein saturated at a lower protein concentration than VLP and at optical densities below the linear range of the assay ( compare Figure 8A and 8B ) , suggesting that even among the mAbs that bind to P proteins conformation-based epitopes may be limited in a way not observed with VLPs . These data suggest two important points . First , some of the mAb epitopes are highly sensitive to conformation , and secondly , that the principle P protein conformation is not identical to VLPs at least for some critical blockade epitopes . The evolution of the GII . 4 noroviruses was assessed over a 36-year period of time by comparing strains from 1974 to 2010 . In comparing these sequences , sites of variation in the P2 subdomain were noted , and these sites were mapped onto the crystal structure of the P-domain dimer for the 1997 strain VA387 . Surface-exposed sites of variation were then examined to determine which residues may be close enough to constitute a single epitope , and five epitopes were predicted based upon this variation ( Figure 9A , and [40] ) . Epitope A encodes significant amino acid changes over time and has also been demonstrated to be an evolving GII . 4 blockade epitope using mouse mAbs ( Figure 9A , 9B and [43] ) . Epitope A is conformational and is located on the top of the capsid proximal to the HBGA binding pocket . Six variable sites were close to each other in the region of this putative epitope , suggesting that these residues may work in concert to change the local structure of Epitope A . The variable , surface-exposed residues include positions 294 , 296–298 , 368 and 372 . Of note , Epitope A is continuing to evolve in extant strains , whereby the amino acid at position 294 seems to vary extensively in strains from 2008–2010 ( amino acid replacements P294A , P294S and P294T have been observed at this position ) . Epitope B was predicted based upon two variable residues at positions 333 and 382 . While these residues are buried in the dimer interface between two chains , the patterns of variation at these sites suggest that they play an important role in the evolution of novel strains , perhaps by evolving replacements that allow the more surface exposed residues in other surface exposed epitopes to dramatically change the physiochemical properties of the amino acid replacements . Residues 340 and 376 make up the variable residues of putative Epitope C . This putative conformation dependent epitope is on the surface and lateral edge of the capsid and is directly proximal to the HBGA binding pocket , suggesting that this epitope may play a role in receptor switching along with Epitope D . Epitope D is comprised of three variable residues from positions 393–395 . In the first reported crystal structure for the GII . 4 noroviruses , this region was reported to be a secondary HBGA binding site [16] . However , the location of this epitope on the surface of the capsid , directly proximal to the HBGA binding site , suggests that it likely plays a role in both receptor switching and in escape from herd immunity and perhaps both , simultaneously [13] , [21] , [40] , [43] . Epitope D is close enough to the HBGA binding pocket to contribute to or inhibit carbohydrate binding , and yet variable enough to suggest that it is targeted by the immune response . Putative Epitope E is comprised of variable residues 407 , 412 and 413 , which are surface exposed regions lateral to the HBGA binding pockets and the other epitopes . These residues vary with every major epidemic strain after 2002 , suggesting that it is a hot spot for the emergence of immunologically novel GII . 4 strains . Epitope E is a GII . 4 . 2002 blockade antibody epitope [17] . This putative epitope is lateral to the HBGA binding pockets indicating that antibodies are targeting interior regions below the capsid surface , which suggests that other epitopes may be present in the P1 subdomain . A few variable residues do not necessarily identify the boundaries of a putative epitope . Moreover , it is nearly impossible to predict the surface area of a putative epitope by sequence analysis alone . Therefore , we expanded the putative epitopes to include residues within 8 Å of the variable sites from which the epitopes were predicted ( Figure 9B ) . The described mAbs indicate at least five unique or overlapping GII . 4 blockade epitopes with different specificities: 1 ) early GII . 4 strain specific , 2 ) contemporary GII . 4 strain specific , 3 ) Minerva-variant strain specific , 4 ) genogroup II strain specific , and 5 ) GII . 4 strain specific . Using capsid sequences as a guide , mutant VLPs were designed to contain chimeric combinations of the predicted evolving GII . 4 epitopes ( Figure 10 ) . Each predicted epitope was exchanged between the 1987 and 2006 parental strain VLPs . For example , Epitope A exchange mutant VLP GII . 4 . 1987/2006A retains the backbone sequence of GII . 4 . 1987 but Epitope A has been replaced with Epitope A from GII . 4 . 2006 . Whereas , GII . 4 . 2006/1987A retains the backbone sequence of GII . 4 . 2006 , but Epitope A has been replaced with Epitope A from GII . 4 . 1987 . All epitope exchange VLPs were morphologically intact by electron microscopy visualization and retained the ability to bind PGM ( Figure 10A and B , [43] ) , confirming chimeric VLP structural integrity . Epitope mutant VLPs were compared to wild type strain VLPs for reactivity to the donor plasma sample . Consistent with high EIA reactivity to GII . 4 . 1987 and 2006 VLPs ( Table 2 and Figure S2 ) , donor plasma reacted across the panel of epitope-exchange mutant VLPs ( Figure 10B ) . Donor plasma was able to block each epitope-exchanged VLP binding to PGM ( Figure 11A and C ) . Exchange of all of the epitopes , except Epitope D into either backbone and GII . 4 . 1987 C into GII . 4 . 2006 resulted in significantly different EC50 values compared to the parental strains ( Figure 11B , 11D , and Table S4 ) ( p<0 . 05 ) . Only the exchange of Epitope A between the backbones resulted in an exchanged blockade phenotype , as observed with epitope-specific mAbs [43] . Exchange of Epitope A between the two parental backbones resulted in a chimeric VLP ( GII . 4 . 1987/2006A ) that was blocked with significantly less plasma than the parental GII . 4 . 1987 ( EC50 0 . 0167 µg/ml compared to 0 . 0673 µg/ml ) ( p<0 . 05 ) and a chimeric VLP ( GII . 4 . 2006/1987A ) that was blocked with significantly more plasma than the GII . 4 . 2006 parent ( EC50 0 . 2770 µg/ml compared to 0 . 0353 µg/ml ) ( P<0 . 05 ) . In comparison , exchange of Epitope E between backbones resulted in chimeric VLPs that required significantly more antibody for blockade then either parental VLP ( GII . 4 . 1987/2006E; EC50 0 . 2025 µg/ml and GII . 4 . 2006/1987E 0 . 0991 µg/ml ) ( Figure 11A–D and Table S4 ) ( p<0 . 05 ) . In this individual , these data suggest that Epitope A may be an important evolving GII . 4 neutralization epitope as the blockade response is significant enough to be detected in the polyclonal antibody response . Agreeing with the assumption that epitope-exchange mutants are unlikely to identify epitopes of cross-reactive mAbs , NVB 37 . 10 , 61 . 3 and 71 . 4 reacted with the entire panel of chimeric VLPs by EIA ( Figure 10B ) . In contrast , each of the strain-specific mAbs displayed differential EIA reactivity to exchanged epitopes A and D . NVB 114 , 111 and 43 . 9 each recognized Epitope A . For NVB 114 , exchange of Epitope A between the 1987 and 2006 backbones resulted in loss of antibody binding to and blockade of GII . 4 . 1987/2006A ( no blockade at 2 µg/ml ) without gain of binding to GII . 4 . 2006/1987A ( Figures 12A , 10B and Table S4 ) . Exchange of the other GII . 4 . 1987 epitopes did not eliminate NVB 114 blockade potential ( Figure 12A and B ) . Further , exchange of Epitope A between the 1987 and 2006 backbones resulted in loss of antibody binding to and blockade of GII . 4 . 2006/1987A and gain of antibody binding to GII . 4 . 1987/2006A for both NVB 43 . 9 and 111 ( Figures 12C–F , 10B and Table S4 ) . NVB 111 needed significantly more antibody to block GII . 4 . 1987/2006A compared to GII . 4 . 2006 ( EC50 1 . 152 compared to 0 . 7376 µg/ml ) ( p<0 . 05 ) while NVB 43 . 9 needed slightly less antibody to block GII . 4 . 1987/2006A compared to GII . 4 . 2006 ( EC50 0 . 0366 compared to 0 . 1031 µg/ml ) ( p<0 . 05 ) . For both antibodies GII . 4 . 2006/1987A was not blocked at 2 µg/ml . These data suggest that Epitope A defines a GII . 4 evolving neutralization epitope for the human antibodies . Similarly , the exchange of Epitope D of GII . 4 . 2006 with Epitope D of 1987 ( GII . 4 . 2006/1987D ) ablated binding of and blockade by NVB 97 . Conversely , exchange of Epitope D of GII . 4 . 1987 with Epitope D of 2006 ( GII . 4 . 1987/2006D ) conferred a significant amount of binding to GII . 4 . 1987/2006D and even blockade activity of the VLP binding to PGM ( Figure 13A and B ) . Binding was not restored to wild type levels as the EC50 of GII . 4 . 1987/2006D was 0 . 6349 µg/ml , significantly higher than the blockade EC50 for GII . 4 . 2006 –PGM ( 0 . 1195 µg/ml ) ( Figure 13B and Table S4 ) ( p<0 . 05 ) . Both EIA and blockade data clearly indicate that Epitope D is critical for the binding of NVB 97 and suggest that amino acids 393–395 are important components of a GII . 4 evolving blockade epitope in addition to modulating VLP-carbohydrate ligand binding [13] , [21] . Interestingly , Epitope D has a single amino acid change in GII . 4 . 2004 , explaining the highly conserved binding and blockade responses noted across GII . 4 . 2005 to 2009 VLPs , while ancestral strains display significant antigenic variation across these residues . Together , these data map the GII . 4 evolving blockade epitopes recognized by each of the four strain-exclusive human mAbs described in this study ( Figure 14 ) .
Noroviruses are recognized as a leading cause of viral food-borne gastroenteritis . With the successful vaccination program being developed against rotavirus , focus is shifting to norovirus as the primary causative agent of severe childhood diarrhea resulting in a yearly estimate of 1 . 1 million episodes of pediatric gastroenteritis in developed nations and 218 , 000 deaths in developing nations [9] . The elderly and immunocompromised also suffer sometimes life-threatening or chronic long-term norovirus diarrheal disease characterized by malnutrition and dehydration [48] . In some HIV infected patients , chronic norovirus diarrheal disease is associated with persistent norovirus infection [49] . The economic disease burden of a norovirus outbreak within a care facility has been estimated at over $657 , 000 for a single event [50] . These statistics emphasize the critical need for a norovirus vaccine . Although recent reports strongly support the development and use of an efficacious norovirus vaccine in humans [38] , [51] , a primary obstacle to a successful vaccine is the lack of a definitive correlate to protection coupled with the extreme antigenic variation across the many norovirus strains . In fact , the existence of long-term protective immunity to norovirus infection remains controversial within the field [52] . Human challenge studies conducted before molecular diagnostics of infection and refined immune response assays had indicated that some volunteers could be reinfected with the same norovirus strain , suggesting that norovirus infection did not induce long-term protection [53] . However , recent reports identifying immune responses in norovirus-challenged but uninfected volunteers [44] , [54] have necessitated qualification of these early observations to acknowledge that the findings may be compromised by assay limitations and/or the overwhelming challenge dose in comparison to the very low norovirus infectious dose [44] , [54] . Clearly defining the relationships between pre-exposure history , blockade antibody responses , T cell immunity , virus evolution , and the components of protective immunity represent key challenges for future vaccine and therapeutic design . In addition to the clinical applications of therapy and diagnosis , monoclonal antibodies have also proven to be superior tools for studying viral antigenicity , evolution , and for the treatment of acute viral disease in humans [13] , [34] , [55] , [56] . Characterization of neutralizing mAb escape-mutants has been fundamental to identifying epitopes associated with virus receptor usage , pathogenesis , and fitness [57]–[59] . In this manuscript , we isolated and characterized the first human mAbs against noroviruses , derived from a healthy donor whose pre-exposure history was unknown . The number of unique GII . 4 human monoclonal antibodies in this patient accurately reflects the high prevalence of GII . 4 norovirus infection seen in human populations over the past 25 years . Moreover , distinct antibody cross reactivity patterns support the hypothesis that the GII . 4 genotype is undergoing antigenic variation which not only correlates with loss of antibody blockade activity and emergence of new epidemic norovirus strains , but also changing carbohydrate ligand binding patterns over time . Importantly , antibody-mediated antigenic drift of GII . 4 strains coupled with both mucosal IgA and T cell responses in challenged but uninfected volunteers strongly support the existence of long-term protective immunity against norovirus strains . In fact , the unique antibody reactivity patterns characterized herein are most likely explained as an archeological immune record of successive waves of contemporary GII . 4 infections in this individual over time , implying that successful vaccine design is possible , as previously proposed by our group and others [37] , [44] , [54] . Previously , we have identified two immunological responses associated with protection from infection in norovirus-challenged volunteers . An early ( day 1–3 ) post-exposure salivary IgA response in genetically susceptible volunteers correlated with protection from Norwalk virus infection [54] and an early Th1 response correlated with protection from Snow Mountain virus infection [44] . Historically , the role of IgG in norovirus protection has been unclear . By adulthood , >90% of the population [48] is positive for anti-norovirus IgG , and norovirus strains within a genogroup share a high degree of antigenic cross-reactivity as measured by EIA [44] , [60] . These facts likely skew functional interpretations of the role of serum IgG titers on susceptibility to infection and/or infection outcomes . Although carbohydrate ligand blockade antibody responses have been suggested as correlates of protective immunity [13] , [35] , [36] , it wasn't until recently that these blockade responses were correlated definitively with protection from clinical disease and infection [10] , [38] . Importantly , our surrogate neutralization assay is specific enough to differentiate GII . 4 norovirus strains too similar to be distinguished by EIA but different at key antigenic sites . While human re-challenge studies using the same viral inoculum are necessary to confirm an association between a blockade IgG response and protection from repeat norovirus infection , our findings support the clinical relevance of the antibody blockade assay as a correlate of protective immunity [38] . Monoclonal antibodies coupled with the blockade assay are powerful tools for elucidating the antigenic relationship between GII . 4 strains . While mouse mAbs provide insight into GII . 4 antigenic structure , data in this manuscript argues that human mAbs offer considerable advantages , including: a ) immunologic record of B-cell immunity following repeat GII . 4 infection , b ) relationships between antibody blockade responses and antigenic variation , c ) relationships between immune selection and carbohydrate ligand reactivity , d ) relationships between early infection and downstream immunity , and e ) epitope mapping . We focused on anti-GII . 4 mAbs because of the clinical relevance of the GII . 4 strains . One key finding is a direct relationship between anti-GII . 4 human mAb carbohydrate ligand blockade responses and the emergence of new GII . 4 epidemic strains . While similar findings were also observed for mouse anti-GII . 4 mAbs , key differences were observed including the presence of human mAbs that distinguished between the 1997 and the 2002 VLPs , definitively delineating an antigenic break between the pandemic 1997 ( US 95/96 ) and 2002 ( Farmington Hills ) strains . Equally important is the observation that different GII . 4 antibody-blockade epitopes change with different epidemic strains . The blockade epitope recognized by NVB 114 ( an early version of Epitope A ) is exclusive for the early GII . 4 strains , and doesn't recognize 2002 or other contemporary variant GII . 4 VLPs ( Figure 3 ) . Given the lack of cross reactivity with later strains , the most likely explanation is that NVB 114 was derived from a long-term memory plasma cell that had been elicited some 12–22 years earlier . In support of this idea , examination of human monoclonal antibodies against 1918 H1N1 influenza also identified antibody variants that recognized ancestral or contemporary isolates [61] . The exclusive blockade reactivity of NVB 114 with GII . 4 . 1987 and 1997 supports potential long-term protective immunity . Further , NVB 114 is the first antibody identified to clearly demonstrate antigenic difference between GII . 4 . 1987 and GII . 4 . 1997 , suggesting that antigenic variation may have subtly contributed to the emergence of the GII . 4 US 95/96 pandemic strain from ancestral strains . Human monoclonal antibodies clearly identified two evolving epitopes on the surface of the GII . 4 VLP . Epitopes A and D were both confirmed as evolving GII . 4 antibody blockade epitopes using chimeric VLPs containing a mixture of epitopes derived from early or contemporary strains . We recognize that Epitopes A and D have not been structurally defined as epitopes , supporting the need for structural studies to define the exact mAb binding site on the VLPs . Moreover , we focused on discrete regions of varying residues and all of the residues within 8 Å ( representing approximately 201 Å2 ) to the primary sites that may be influenced directly by an amino acid replacement ( Figure 9B ) . However , Ab binding sites have been reported to be much larger ( 700–800 Å2 ) , suggesting that the epitopes that we have predicted may actually work in concert to form larger Ab recognition sites . By expanding the putative epitopes , we identified other residues that were less variable; however , the exact role that these varying residues play in evolution is less clear . In some cases variation may be required to encode changes that are necessary for the replacement at a primary site . In addition , all of our structural analyses have been conducted using models of the P dimer , representing about 1/90th of the VLP structural surface . Interactions between the epitopes in the context of the superstructure have not been determined . Therefore , these observations indicate that the complex nature of the NoV Ab epitope requires further research to define the specific boundaries and residues that regulate Ab binding . The prediction of five putative epitopes allowed us to gain several important insights into GII . 4 norovirus evolution: 1 ) Discrete sites of variation occur on the GII . 4 norovirus capsid , either directly on the surface or lateral to the HBGA binding sites; 2 ) Secondary variable sites are within 8 Å of the primary variable sites , and these secondary sites could also contribute to epitope remodeling; 3 ) Many of the putative expanded epitopes overlap , suggesting that two or more highly variable epitopes may work in concert to escape from an antibody response; 4 ) Putative epitopes that are buried may exert an effect on the structure by altering the interior fold space , allowing unconventional replacements to be tolerated; 5 ) An underlying amino acid network likely preserves the functional core of the capsid proteins by regulating the variable residues above them; and 6 ) Escape and HBGA binding may be intimately linked via the underlying regulatory network of amino acids that preserve the functional integrity of the capsid core . Epitope A , which likely includes varying amino acid residues 294 , 296–298 and 368 and 372 and potentially other undefined nearby residues , has been mapped as a blockade epitope in both GII . 4 . 1987 and GII . 4 . 2006 Minerva variants . Importantly , the antibodies that recognize Epitope A in GII . 4 . 1987 do not bind GII . 4 . 2006 and the antibodies that recognize Epitope A in GII . 4 . 2006 did not recognize GII . 4 . 1987 ( Figures 3 , 5 , 12 and [43] ) . These data support the idea that unique memory B cells were elicited as a consequence of unique exposure events , most likely years apart in this individual . Further , the significant difference in EC50 values between the 2006 and 2009 Minerva variants for NVB 111 and 43 . 9 ( Figure 5 ) suggests that Epitope A continues to evolve and the epidemic 2009 stain is still diverging from the pandemic 2006 strain at this site , most likely as a consequence of long-term antibody selection . GII . 4 . 2006 and 2009 differ at positions 294 , 368 and 372 within Epitope A ( Figure 9A ) . At this time it is unclear how many and which amino acids in Epitope A are needed to mediate an escape mutant phenotype that is completely resistant to GII . 4 . 2006 antibody blockade . However , it is clear that Epitope A varies , and that the site is conserved as a major target for blockade antibody response between 1987 and 2009 . Although correlative , comparisons of Epitope A variation along with residues that are proximal to those that appear to be evolving over time suggest that changes at positions 292 , 293 , 294 , 295 , 296 , 297 , 298 , 300 , 365 , 367 , 368 and 372 might contribute to an escape phenotype , with residues 294 , 296 , 297 , 298 , 300 , 368 and 372 playing direct roles in this variation ( Figure 9 ) . However , the minor replacements at other positions are likely essential for remodeling the local structural neighborhood such that more profound changes can be tolerated . Supporting the sensitivity of epitopes to the local environment , mAbs that recognized Epitope A differentiated between GII . 4 . 2006 VLPs and GII . 4 . 2006 P dimers . P protein ( P dimer ) is a dimeric , truncated form of the major capsid protein composed of residues 214–539 [62] . P-dimers have been widely used to determine the crystallographic structure of NoV-HBGA interactions and are considered accurate reflections of the VLP surface topology [16] , [21] , [63] . P –particles can assemble as higher ordered structures composed of varying copies of the P dimer [46] , [64] . These subviral particles are reported to have similar characteristics to VLPs [62] , [65]–[67] and have been proposed as a candidate vaccine platforms [68] . To our knowledge , this is the first immunologic characterization of P-dimers vs . VLPs using monoclonal antibodies derived from human infections . Here , P-dimers derived from GII . 4 . 2006 lost binding of mAbs NVB 111 and 43 . 9 , the mAbs that recognize Epitope A in GII . 4 . 2006 . P dimer binding to the Epitope D binding mAb NVB 97 and the broadly cross-blockade mAb NVB 71 . 4 were retained . Recently , P-particle vaccines were shown to be less robust at inducing strong blockade responses , as compared with intact VLP [69] , perhaps because of the loss of blockade Epitope A in this higher ordered structure . While speculative , it is recognized that virions “breathe” suggesting that the possibility that P-dimers and P-particles may become “locked” in a slightly less immunologically reactive state that affects some but not all blockade epitopes on the virion surface [70] , [71] . These data absolutely underscore the critical importance of determining the structures of several of these human mAbs with their appropriate GII . 4 VLP epitopes by either cryoEM or crystallography , for informing targeted mutagenesis to identify the role of key residues in regulating antigenicity and antibody escape . Epitope D is a conformational epitope comprised of varying amino acids 393–395 and likely other nearby residues that are less clearly defined; however , additional mapping and crystallographic studies will be needed to clarify this epitope structure . With the emergence of the pandemic GII . 4 . 2004 Hunter strain , Epitope D elicited robust antibody blockade responses as typified by NVB 97 . These observations suggest that Epitope D has been relatively static since 2004 and may be a good target for vaccine development . Although the blockade epitope is conserved post 2002 , comparison of EC50 titers suggests that the antibody's highest efficacy is against GII . 4 . 2006 , as all other VLPs have significantly less robust EC50 values ( Figure 4 ) . Previously , these residues have been implicated in regulating norovirus VLP-carbohydrate ligand binding interactions [13] , [21] , [43] . The identification of Epitope D as a human antibody blockade epitope that changes over time provides direct support for our previous hypothesis that escape from protective herd immunity may drive changes in carbohydrate ligand binding affinities over time and potential retargeting of virus infection in different human populations [13] , [40] . These data indicate that like influenza , a successful norovirus vaccine regimen will require periodic population sampling to identify future strains for inclusion into the next year's vaccine formulation not unlike the strategy employed by the Influenza Virus Global Surveillance Program . Norovirus population sampling has already begun as monitoring systems for detection of NoV infections have been established in the United States , Europe , and Japan . Identification of GII . 4 evolving antigenic epitopes furthers our understanding of norovirus pathogenesis and provides target epitopes that may be useful for surveillance and prediction of new strain emergence . Identification of GII . 4 conserved epitopes also informs diagnostic and potential therapeutic reagent development and design . Monoclonal antibodies NVB 37 . 10 , 61 . 3 and 71 . 4 all recognize epitopes conserved among the GII . 4 strains from 1987 through 2009 . NVB 37 . 10 and 61 . 3 have enhanced GII VLP recognition , binding not only GII . 4 VLPs but also other GII VLPs , but are unable to block VLP-PGM interaction . The high conservation of the NVB 37 . 10 and 61 . 3 epitopes suggest that these epitopes are highly resistant to antigenic variation within the GII strains , making these mAbs potentially valuable diagnostic reagents as GII strains cause up to 95% of norovirus outbreaks [27] , [72] . The unidentified epitope for NVB 71 . 4 is clearly different from the epitopes recognized by NVB 37 . 10 and 61 . 3 and is conserved throughout the GII . 4 strains . NVB 71 . 4 did not recognize any non-GII . 4 VLPs but , importantly , it exhibited blockade activity for the entire panel of time-ordered GII . 4 VLPs with PGM and Bi-HBGAs . Emphasizing the difference between the two quantitative blockade assays and the qualitative HAI assay , GII . 4 . 2002 HA was not inhibited by NVB 71 . 4 . Noting that blockade assays are not true measurements of neutralization , NVB 71 . 4 has potential as a therapeutic reagent based on its broad GII . 4 blockade potential and the fact that it is by nature a human antibody . Clearly , the effectiveness of NVB 71 . 4 at preventing or treating illness can only be determined empirically . Although one of the blockade-epitope specific mAbs with lower EC50 values/steeper Hill constants may be more effective at select strain neutralization , the breadth of strains neutralized is likely to be limited for these mAbs . There are a number of viral diseases currently being treated with mAbs including RSV , CMV and enterovirus; however , only the anti-RSV humanized mAb palivizumab has FDA approval for prophylactic use in humans [73] , [74] . In outbreak settings or in chronically infected patients , an anti-NoV mAb that could be delivered before symptoms begin and protect from illness could be very useful in care facilities , the military and the cruise industry . Given the acute clinical disease window , it is less likely that therapeutic antibodies will provide relief in those individuals experiencing acute infections , however , therapeutic antibodies may offer opportunities for ameliorating symptomatic disease in chronic infections . The discovery of broadly cross reactive and cross blockade human GII . 4 mAbs dictates the need for a new approach to map epitopes . Our current experimental approach was designed to identify GII . 4 epitopes that change over time and provide insight into broadly conserved epitope locations . Because the identification of the epitopes recognized by NVB 37 . 10 , 61 . 3 , and 71 . 4 has important implications for successful vaccine design , new panels of mutated VLPs and other approaches will be needed to characterize these epitopes in the future . GII . 4 NoVs are significant human pathogens that cause considerable morbidity and mortality , worldwide . The development of mouse mAbs to different time-ordered GII . 4 VLPs has greatly facilitated progress towards understanding the complex antigenic relationships between these strains by clearly demonstrating antigenic variation over time and epidemic strain [34] . Here we have expanded these observations using human anti-GII . 4 mAbs isolated from a healthy adult donor , who has likely experienced multiple norovirus infections throughout his/her lifetime . The identification of highly significant , varying antigenic epitopes that influence VLP-carbohydrate ligand interaction provides important new insights into vaccine design and the development of therapeutics that target norovirus virions . For example , these antibodies represent the first anti-norovirus human mAbs to be characterized , and they confirm findings from studies using mouse mAbs supporting antigenic drift and its linkage with varying carbohydrate ligand binding profiles within the GII . 4 noroviruses . Further , we have demonstrated that the GII . 4 NoV varying epitopes can be exchanged between time-ordered VLPs , providing a robust platform for expanding the antigenic and blockade cross reactivity of future vaccine candidates . Using this approach , we have identified two surface-exposed antibody blockade epitopes that vary over time and were differentially recognized by four of the seven human mAbs . We also identified three antibodies which recognize either overlapping or three unique highly conserved epitopes within the GII . 4 VLP . These data continue to support the hypothesis that norovirus long-term protective immune responses are elicited following acute infection , a concept essential for effective vaccine design . We anticipate that a full understanding of the varying antigenic and blockade epitopes of GII . 4 NoVs may not only help to predict the emergence of new epidemic strains but simultaneously identify key reformulations in vaccine design that will protect public health against contemporary and emerging epidemic strains in the future .
A diverse panel of VLPs representing G1 and GII norovirus strains and epitope mutants was assembled as previously reported [13] , [17] , [75] . To design epitope exchange chimeric VLPs , we first identified surface exposed residue clusters that varied over time . Then , we synthesized a series of chimeric GII . 4 ORF2 genes that exchanged “putative” epitopes between GII . 4 . 1987 and GII . 4 . 2006 VLPs [43] . For all constructs except GII . 4 . 2009 ORF2 [17] , the synthetically derived constructs were inserted directly into the VEE replicon vector for the production of virus replicon particles ( VRPs ) as previously described by our group . VLPs were expressed in VRP-infected BHK cells and purified by velocity sedimentation in sucrose and stored at −80°C . The GII . 4 . 2009 ( New Orleans [17] ) VLPs were expressed in the baculovirus system and purified by cesium chloride gradient centrifugation and were the kind gift of Dr . Jan Vinje , Centers for Disease Control and Prevention , Atlanta , GA . VLP protein concentrations were determined by the BCA Protein Assay ( Pierce , Rockford , IL ) . VLP preparation purity averaged >80% by SDS-Page analysis . In early 2009 , following written consent , blood samples from 63 donors were collected from adult healthy donors at the Lugano and Basel Blood banks ( Switzerland ) . Peripheral blood mononuclear cells ( PBMCs ) and plasma were isolated and cryopreserved . On the day of use , PBMCs from Donor 302898 ( Figure 1 ) , an individual born in 1948 , were thawed and IgG+ memory B cells were isolated using CD22 microbeads ( Miltenyi ) followed by cell sorting , as described [76] . Cells were immortalized at 5 cells/well in multiple cultures using EBV in the presence of CpG oligodeoxynucleotide 2006 ( Microsynth ) and irradiated allogeneic PBMC . After 2 weeks , culture supernatants were screened for the presence of norovirus-specific mAbs by EIA against VLPs and positive cultures were cloned by limiting dilution . Antibodies were recovered from supernatants and purified using protein A affinity chromatography and finally desalted against PBS using a HiTrap FastDesalting column . Human mAb reactivity was determined by EIA , as reported [34] . Briefly , plates were coated at 1 µg/ml VLP in PBS before the addition 1 µg/ml purified IgG or donor plasma ( 0 . 2% ) . Primary antibody incubation was followed by anti-human IgG-alkaline phosphatase and color development with pNPP substrate solution ( Sigma Chemicals , St . Louis , MO ) . Each step was followed by washing with PBS-0 . 05% Tween-20 and all antibodies were diluted in 5% dry milk in PBS-0 . 05% Tween-20 . Data shown represent the average of at least three replicates and are representative of similar data from at least two independent trials . Establishment of EIAs using new mAbs included PBS-coated wells as negative controls and polyclonal anti-norovirus human sera as positive controls . Antibodies were considered positive for reactivity if the mean optical density after background subtraction for VLP-coated wells was greater than three times the mean optical density for PBS-coated wells [34] . For screening donor plasma samples , the binding titers of plasma to respective coated VLPs were determined by EIA as described above by measuring the plasma dilution required to achieve 50% maximal binding ( ED50 ) . EIA reactivity to GII . 4 . 2006 P protein ( amino acids 221–531 [21] ) was measured similarly to reactivity to VLP . GII . 4 . 2006 P protein was the kind gift of B . V . Prasad , Baylor College of Medicine , Houston , TX ) . Pig Gastric Mucin Type III ( PGM ) ( Sigma Chemicals ) has been validated as a substrate for NoV VLP antibody-blockade assays [17] . PGM contains relatively high levels of H and A antigen and more moderate levels of Lewis Y antigen [17] . All of the GII . 4 VLPs used in the blockade assays in this study bind to both PGM and synthetic Bi-HBGA , and binding to PGM is consistent with synthetic Bi-HBGA binding profiles for α-1 , 2-fucose ( H antigen ) and α-1 , 4-fucose ( Lewis antigen ) containing molecules [13] , [17] , [77] . For blockade assays , PGM was solvated in PBS at 5 mg/ml and coated onto EIA plates at 10 µg/ml in PBS for 4 hours and blocked over night at 4°C in 5% dry milk in PBS-0 . 05% Tween-20 . VLPs ( 0 . 5 µg/ml ) were pretreated with decreasing concentrations of test mAb or donor plasma for 1 hour at room temperature before being added to the carbohydrate ligand–coated plates for 1 hour . Bound VLP was detected by a rabbit anti-GII norovirus polyclonal sera made from hyperimmunization with either GII . 4 . 2009 or a cocktail of GII . 4 . 1997 , GII . 3 . 1999 , GII . 1 . 1976 , and GII . 2 . 1976 VLPs , followed by anti-rabbit IgG-HRP ( GE Healthcare ) and color developed with 1-Step Ultra TMB ELISA HRP substrate solution ( Thermo-Fisher ) . The percent control binding was defined as the binding level in the presence of antibody pretreatment compared to the binding level in the absence of antibody pretreatment multiplied by 100 . All incubations were done at room temperature . Each step was followed by washing with PBS-0 . 05% Tween 20 and all reagents were diluted in 5% dry milk in PBS-0 . 05% Tween-20 . All antibodies were tested for blockade potential against the panel of GII . 4 VLPs at two-fold serial dilutions ranging from 0 . 08 to 2 µg/ml . Additional concentrations of blockade antibodies were tested if needed to complete the sigmoid dose-response curve . Blockade of synthetic Bi-HBGAs ( Glycotech , Gaithersburg , MD ) assays were done as described for PGM with the following exception . Bi-HBGAs were bound to Neutri-avidin coated plates ( Pierce ) at 10 µg/ml for one hour prior to the addition of 1 µg/ml VLP for 1 . 5 h . Reported mean % control binding reflects the results of at least two independent experiments with each dilution tested at least in duplicate . An antibody was designated as a “blockade” antibody for a VLP if at least 50% of control binding was inhibited by 2 µg/ml antibody . Blockade data were fitted and EC50 values calculated using Sigmoidal dose response analysis of non-linear data in GraphPad Prism 5 ( www . graphpad . com ) . EC50 values between VLPs were compared using the One-way ANOVA with Dunnett post test , when at least three values were compared or the unpaired t-test when two values were compared . A difference was considered significant if the P value was <0 . 05 . To test for antibody binding that prevents detector antibody from binding to the VLP instead of the VLP binding to the PGM , select blockade assays are performed without using a detector antibody and instead developed directly with an anti-human IgG-HRP . Antibodies tested this way give two responses; 1 ) a bell-shaped response curve for antibodies that are blockade and 2 ) a sigmoidal shaped curve for antibodies that are not blockade . These data indicate that it is the amount of human mAb that is directly blocking the VLP from binding to PGM . Of note , VLP concentrations in blockade assays are in the low nanomolar range and therefore cannot discriminate between antibodies with sub-nanomolar affinities . HAI assays were performed as reported [38] , [39] , [45] . VLPs at 50 ng/reaction were pretreated with antibody as described above for the blockade assays before addition to O+ RBCs at 4°C , pH 5 . 5 . An HAI titer was determined as the lowest antibody concentration that completely prevented NoV VLP-induced HA by visualization . The amino acid sequences of GII . 4 . 1987 , GII . 4 . 2002 , and GII . 4 . 2006 capsids were individually aligned to the VA387 P domain sequence using Clustalx1 . 86 [78] , and the GII . 4 . 2002 domain dimer X-ray crystal structure ( PDB accession: 2OBT ) [16] was used as a template for generating homology models . Homology models were generated using the program Modeller available via the Max Planck Institute Bioinformatics Toolkit ( http://toolkit . tuebingen . mpg . de/ ) . The structural models were analyzed and compared , and figures were generated using Mac Pymol ( Delano Scientific ) . | Noroviruses are the principal cause of epidemic gastroenteritis worldwide with GII . 4 strains accounting for 80% of infections . The major capsid protein of GII . 4 strains is evolving rapidly , resulting in new epidemic strains with altered antigenic sites . To define these sites we prepared the first human monoclonal antibodies ( Hu mAbs ) against GII . 4 noroviruses by immortalizing memory B cells and characterizing antibody reactivity and carbohydrate blockade responses across a ∼20 year panel of time-ordered GII . 4 virus-like particles ( VLPs ) . Reflecting the complex exposure history of the patient , human anti-GII . 4 mAbs grouped into three VLP reactivity patterns: broad ( 1987–2009 ) , contemporary ( 2004–2009 ) , and ancestral ( 1987–2002 ) . We also identified the location of several defined epitopes which evolve over time and drive antigenic change . Our data indicate that antibodies targeting these sites block carbohydrate binding and likely select for the emergence of new strains that escape herd immunity and recognize unique carbohydrates for entry , resulting in new outbreaks of disease in vulnerable human populations . Importantly , these studies critically inform the rational design of broadly active vaccines and immunotherapeutics for the treatment of norovirus disease . | [
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] | 2012 | Immunogenetic Mechanisms Driving Norovirus GII.4 Antigenic Variation |
Prions are self-perpetuating conformational variants of particular proteins . In yeast , prions cause heritable phenotypic traits . Most known yeast prions contain a glutamine ( Q ) /asparagine ( N ) -rich region in their prion domains . [PSI+] , the prion form of Sup35 , appears de novo at dramatically enhanced rates following transient overproduction of Sup35 in the presence of [PIN+] , the prion form of Rnq1 . Here , we establish the temporal de novo appearance of Sup35 aggregates during such overexpression in relation to other cellular proteins . Fluorescently-labeled Sup35 initially forms one or a few dots when overexpressed in [PIN+] cells . One of the dots is perivacuolar , colocalizes with the aggregated Rnq1 dot and grows into peripheral rings/lines , some of which also colocalize with Rnq1 . Sup35 dots that are not near the vacuole do not always colocalize with Rnq1 and disappear by the time rings start to grow . Bimolecular fluorescence complementation failed to detect any interaction between Sup35-VN and Rnq1-VC in [PSI+][PIN+] cells . In contrast , all Sup35 aggregates , whether newly induced or in established [PSI+] , completely colocalize with the molecular chaperones Hsp104 , Sis1 , Ssa1 and eukaryotic release factor Sup45 . In the absence of [PIN+] , overexpressed aggregating proteins such as the Q/N-rich Pin4C or the non-Q/N-rich Mod5 can also promote the de novo appearance of [PSI+] . Similar to Rnq1 , overexpressed Pin4C transiently colocalizes with newly appearing Sup35 aggregates . However , no interaction was detected between Mod5 and Sup35 during [PSI+] induction in the absence of [PIN+] . While the colocalization of Sup35 and aggregates of Rnq1 or Pin4C are consistent with the model that the heterologous aggregates cross-seed the de novo appearance of [PSI+] , the lack of interaction between Mod5 and Sup35 leaves open the possibility of other mechanisms . We also show that Hsp104 is required in the de novo appearance of [PSI+] aggregates in a [PIN+]-independent pathway .
Prions were first described as self-perpetuating infectious agents devoid of nucleic acids that cause several fatal neurodegenerative diseases . Prion diseases , also known as transmissible spongiform encephalopathies ( TSEs ) , were shown to infect a variety of mammals [1] . All known mammalian prion diseases are caused by conversion of largely α-helical cellular prion protein PrPC into fibrous β-sheet-rich ordered aggregates ( amyloids ) called PrPSc ( associated with scrapie ) [2] . Curiously , PrPSc can exist in different heritable forms , called strains , which cause neurodegenerative diseases with different characteristics and pathologies [3]–[5] . A number of other neurodegenerative diseases are also associated with conversion of a soluble protein to amyloid . For example , amyloid-like forms of Aβ and Tau , α-synuclein , huntingtin , FUS/TLS , TDP-43 or SOD1 are linked respectively to Alzheimer's ( AD ) [6] , Parkinson's ( PD ) [7] , [8] , Huntington's ( Htt ) [9] and Amyotrophic Lateral Sclerosis ( ALS ) diseases [10]–[15] . Factors that influence the spontaneous conversion to amyloid are of considerable interest as possible disease risk factors . One important finding is that heterologous amyloid can promote the de novo conversion of a protein to amyloid . For example , Aβ accelerated the in vivo aggregation of tau [16] , and Aβ and α-synuclein seeded each other's aggregation in vitro [17] . Indeed , recently distinct conformational variants of α-synuclein aggregates were shown to differentially promote the aggregation of tau in neurons [18] . Several proteins in the simple eukaryote yeast have been shown to convert from soluble to amyloid . The amyloid forms of these proteins are self-propagating prions associated with transmissible phenotypes [19]–[28] . These proteins provide good models for the amyloid conversion of human disease proteins . For both human and yeast proteins , only a portion of the protein , called the prion domain ( PrD ) , converts to amyloid . This portion of the protein is required for prion induction and propagation [29] , [30] . The PrD of most known yeast prions is glutamine ( Q ) and asparagine ( N ) rich . Likewise , several human aggregating disease proteins e . g . huntingtin , TDP-43 and FUS contain Q/N-rich regions [31] , [32] . In contrast , the recently discovered yeast [MOD+] prion , composed of Mod5 , as well as PrP , Aβ and α-synuclein do not contain Q/N rich domains [27] . Similar to the mammalian PrP strains , yeast prions can also fold into numerous heritable conformations , called variants , leading to different degrees of altered phenotypes [33]–[36] . The most well-studied yeast prion is [PSI+] , the prion form of Sup35 . In its native form , Sup35 ( release factor 3 ) works with Sup45 ( release factor 1 ) to promote translational termination at stop codons [37] . The Sup35 protein consists of three major domains: N-proximal ( N domain ) required for prion induction and propagation; a highly charged middle ( M ) domain conferring solubility to the molecule and containing Hsp104 binding sites [38] and a C-terminal ( C ) domain essential for translational termination and viability [33] , [39]–[41] . [PSI+] forms when Sup35 molecules assemble into amyloid-like aggregates , causing loss-of-function in translation termination , which leads to read-through of stop codons [20] , [42] , [43] . The spontaneous appearance of prions in yeast is extremely rare . Indeed , the conversion of prion-free cells , [psi-] to [PSI+] was determined to be ∼5 . 8×10−7 [44]–[47] . On the other hand , overproduction of full-length Sup35 or its prion containing domain ( Sup35NM ) can increase the de novo appearance of [PSI+] dramatically , presumably by increasing the chance of Sup35 prion domains to misfold and interact [48] . This enhanced formation of [PSI+] requires either the presence of another prion [22] , [49] , [50] or the simultaneous overexpression of heterologous Q/N-rich domains [22] , [51] . The best studied example of this stimulation by a prion involves [PIN+] , the prion form of the Rnq1 protein . Although [PIN+] dramatically enhances the appearance of [PSI+] , it is not required for [PSI+] propagation [49] . Understanding how [PIN+] enhances de novo induction of [PSI+] will help us understand analogous interactions between heterologous human disease proteins . Several models have been proposed ( reviewed in [52] ) . The cross-seeding model suggests that [PIN+] initially acts as a seed for the conversion of the Sup35 prion domain into the [PSI+] conformation . Once [PSI+] is established , it is proposed to create its own seeds independent of [PIN+] , allowing it to continue to propagate efficiently [53] . Several in vitro studies provide evidence in favor of induction of [PSI+] via cross-seeding [52] , [54] , and for the enhanced rate of polymerization of other proteins in the presence of heterologous aggregates [55]–[61] . Most notably , mCherry:FUS fibers were extended in length heterotypically when exposed to monomeric GFP:hnRNPA1 [55] . Definitive evidence for cross-seeding in vivo is much more difficult to obtain . Still , a fusion of the prion domain of Sup35 ( NM ) and Rnq1 lead to the efficient induction of [PSI+] in the presence of [PIN+] , even without Sup35 overexpression [62] , presumably because the fusion efficiently brings Sup35NM to the Rnq1 aggregates , thereby increasing the chance of physical association and resulting cross-seeding . Also , different [PIN+] variants preferentially cause the genesis of different variants of [PSI+] [63] , [64] , which can be easily explained by cross-seeding but not by chaperone titration . The titration model postulates that cellular factors responsible for the disassembly of aggregates and the refolding of misfolded proteins are so busy working on the existing [PIN+] prion that they are not available to prevent the appearance of the new prion , [PSI+] [22] , [51] , [65] . In support of this model , prion-like aggregates have been shown to colocalize with chaperones , reducing the cytosolic level of chaperones and thereby affecting the stability of heterologous prion aggregates in the cell [66]–[70] . Molecular chaperones , which are normally involved in proper protein folding play a critical role in the maintenance of yeast prions ( reviewed in [71] ) . Particularly , the Hsp104 chaperone in conjunction with chaperones of the Hsp70 ( Ssa/Ssb ) and Hsp40 ( Sis1 ) families was shown to shear prion aggregates into smaller fragments that promote fiber growth and transmission to daughter cells [72]–[77] . The shearing activity of Hsp104 is antagonized by millimolar concentrations of guanidine hydrochloride ( GuHCl ) , leading to the loss of [PSI+] [78] , [79] , and other yeast prions [19] , [50] . Hsp104 is required for the propagation of almost all known yeast prions [72] , [80]–[82] . Stimulation of de novo generation of prions in yeast is achieved by inducing overexpression of the corresponding prion protein . The resulting aggregates have been monitored with fluorescent derivatives . The de novo induction of [PSI+] promoted by [PIN+] was shown to display various Sup35 aggregates and go through several stages . Overexpression of Sup35NM-GFP , gave rise to fluorescent dot , line and ring-like assemblies [83]–[85] . The fluorescent rings induced by Sup35NM-GFP overexpression is a hallmark of [PSI+] induction . Indeed , most viable ring/dot-bearing cells gave rise to [PSI+] progeny [83]–[86] . Sup35 dots appeared earlier than rings and lines [84] . Ring-like aggregates were shown to be first peripheral along the cell membrane , and later internal surrounding the vacuole [83] , [85] . When cells with such rings were followed in media that turned down Sup35 overexpression , Sup35NM-GFP appeared as dots in daughter cells , a typical feature of [PSI+] [83]–[85] . Once [PSI+] is established , Sup35NM-GFP overexpression results in one or a few large mature dots , or clumps but rings do not appear at all [29] , [43] . These large dots replace the numerous small Sup35-GFP aggregates seen in [PSI+] cells with endogenous Sup35 tagged with GFP prior to overexpression [75] . When Sup35NM-GFP was constitutively overproduced in [PIN+] cells with a deletion of the Sup35 prion domain , only internal rings were observed prior to the transition to mature dots [87] . In this study , we report that the de novo appearance of [PSI+] aggregates begins with dots that co-localize with the main Rnq1 aggregate near the vacuole , that grow into peripheral rings and lines prior to the appearance of internal rings . Our studies also reveal preferential colocalization of Rnq1 and Pin4C aggregates with newly appearing vs . established [PSI+] aggregates , which is consistent with the cross-seeding model for [PSI+] induction . However , the failure of Mod5 to physically interact with Sup35 during Mod5-promoted [PSI+] induction suggests that cross-seeding is not involved . Finally , we provide evidence for the [PIN+]-independent requirement of Hsp104 during [PSI+] induction in vivo .
We used GFP-tagged SUP35 constructs to visualize the initial conversion of Sup35 from soluble to aggregated protein when [psi-] cells were induced to become [PSI+] by overexpressing Sup35 ( NM ) . Sup35NM-GFP overexpressed in [PIN+][psi-] cells ( Fig . 1A ) progressed over time from diffuse cytoplasmic fluorescence in all cells to some cells with one to three fluorescent foci one of which was always near the vacuole , to more cells with dots . Later , peripheral rings and lines started to replace dots in some cells ( see Table 1 for details ) . In contrast , [pin-] cells showed no aggregates of Sup35NM-GFP at any time point . Even when we dramatically reduced the level of Sup35NM-GFP overexpression by growing cells in 0 . 2 rather than 2% Gal , the type and order of appearance of these aggregates did not change ( S1 Table ) . In another approach , we examined endogenous Sup35 tagged with GFP when untagged Sup35NM was overexpressed in [PIN+][psi-] cells ( Fig . 1B , Table 1 ) . Upon induction of Sup35NM , all cells initially showed diffuse Sup35-GFP fluorescence , which was later seen as cytoplasmic dots one of which was near the vacuole and then , lines and rings in some cells . Similar results were observed when untagged full-length Sup35 was overexpressed ( S1A Fig . ) . As expected , [pin-] cells always displayed diffuse Sup35-GFP molecules in the presence of Sup35NM overexpression ( S1B Fig . ) . Because the diffuse fluorescence of Sup35NM-GFP observed in the experiments above might have masked the visualization of initial Sup35 aggregates during [PSI+] induction , we overexpressed Sup35NM from Bimolecular Fluorescence Complementation [88] , [89] ( BiFC ) constructs , Sup35NM-VN and Sup35NM-VC , simultaneously in [PIN+][psi-] cells ( Fig . 1C , Table 1 ) . Prior to 8 h of induction , no fluorescence was detected . The lack of diffuse fluorescence suggests that Sup35 aggregation does not begin all over the cell . At 8 h , a few cells showed fluorescent dots near the vacuole revealed by FM4-64 staining [90] , but no lines/rings were visible . By 24-55 h , peripheral rings and lines appeared and more cells displayed dots . In control [pin-] cells , no fluorescence was detected . To determine if the dots and rings/lines that appeared within 24 h of induction of Sup35NM-YFP overexpression show amyloid-like properties , we stained the newly appearing Sup35NM-YFP aggregates in [PIN+][psi-] cells with Thioflavin T ( ThT ) ( Fig . 2 ) : 30% of the dots and 60% of the rings were ThT-positive . As expected , Sup35NM-YFP mature dots in [pin-][PSI+] were all stained with ThT . In control [pin-][psi-] cells however , diffuse Sup35NM-YFP fluorescence did not show any ThT fluorescence . These data suggested that Sup35NM-YFP does not always form amyloidogenic aggregates during [PSI+] induction , but eventually becomes amyloid in mature [PSI+] . To further investigate the subcellular localization of the initial Sup35 dots , we used BY4741 cells with genomic HSP42 tagged with GFP [91] ( see Table 2 for details ) . Hsp42 is a small heat shock protein that appears as one big dot near the vacuole , sometimes referred to as the IPOD for the site ( s ) of deposit of insoluble protein aggregates [92]–[94] . Overexpression of Sup35NM-RFP in [PIN+][psi-] HSP42-GFP cells first caused the occasional appearance of cells with 1-6 dots , one of which always colocalized with the Hsp42-GFP dot ( Fig . 3 ) . Later , in some cells , Sup35NM-RFP fluorescence extended from a bright dot that colocalized with the Hsp42-GFP dot as short lines tangent to the vacuole or as lines extending to the cell periphery . Interestingly , the multiple Sup35NM-RFP dots observed initially were never seen later once lines appeared , suggesting that Sup35NM-RFP aggregates that did not colocalize with Hsp42-GFP were solubilized , or may have joined the lines . Eventually , in some cells , Sup35 formed internal rings surrounding the vacuole as seen previously [83] , [84] , intersecting the Hsp42-GFP dot , and in a very few cells , lines were seen to extend from the Hsp42-GFP dot peripherally and around the vacuole simultaneously . To determine the localization of Sup35 newly induced aggregates with respect to the vacuole , we overexpressed Sup35NM-RFP in [PIN+] cells with genomic VPH1 tagged with GFP ( S2 Fig . ) . Vph1 is a subunit of the vacuolar-ATPase protein and marks the vacuolar membrane [95] . We found that Sup35 early dots ( after 24 h of Sup35NM-RFP overexpression ) were localized near the vacuole , and later , short lines extended outward from the vacuole to the periphery of the cell . Then , as expected , Sup35 formed peripheral rings , and eventually perivacuolar rings . In summary , the various experiments above showed that during the de novo aggregation of Sup35 induced by its overexpression , Sup35 initially formed dots , one of which perfectly colocalized with the Hsp42-GFP dot near the vacuole . Then , Sup35 lines extended from this dot to form peripheral and eventually perivacuolar rings , while the other initial Sup35 dots disappeared . To visualize the relationship of Sup35 and Rnq1 during the de novo induction of [PSI+] , we expressed Rnq1-GFP under its own promoter , and overproduced Sup35-RFP in [PIN+][psi-] cells ( Fig . 4A , top ) . Sup35-RFP initially formed fluorescent dots but no lines or rings ( Details in S2 Table ) . All the Rnq1-GFP dots perfectly colocalized with Sup35-RFP dots , but only 60% of the Sup35-RFP dots colocalized with Rnq1-GFP foci . Interestingly , the colocalized Rnq1-Sup35 dots were always associated with the vacuole revealed by FM4-64 staining ( Fig . 4A , middle ) . Additional Sup35 dots that did not overlap Rnq1 were away from the vacuole ( Fig . 4A , gray arrows ) . These Sup35 dots have different characteristics from Sup35 dots seen in mature [PSI+] cells . For example , while the results above showed that newly appearing vacuole-associated Sup35 aggregates perfectly colocalize with Rnq1 , mature Sup35 aggregates in established [PSI+] cells did not entirely overlap Rnq1 ( seen as in two sets intersecting in a Venn diagram ) ( Fig . 4A , bottom ) . Also , additional Rnq1-CFP dots existed in [PIN+][PSI+] cells that did not show any colocalization with Sup35 ( Fig . 4A bottom , arrows , enlarged box ) . In summary , after 6 h of [PIN+]-promoted Sup35-RFP aggregation , all Rnq1 dots perfectly overlapped newly induced Sup35 dots around the vacuole , but additional Sup35 dots ( away from the vacuole ) without overlapping Rnq1 sometimes existed in those cells . In contrast , in established [PSI+] cells , all Sup35 dots partially overlapped Rnq1 dots , but additional Rnq1 dots without overlapping Sup35 also existed . To look for colocalization of Rnq1 with Sup35 rings , we induced overexpression of Sup35-RFP for 24 h in [PIN+] cells also expressing Rnq1-GFP from its own promoter . Sup35-RFP formed rings 70% of which colocalized with Rnq1-GFP ( Fig . 4B ) . In the remaining 30% of cells with Sup35-RFP rings that did not colocalize , Rnq1-GFP fluorescence was instead diffuse or in the form of dots ( S3A Fig . , S3 Table ) . In contrast , essentially all Rnq1-GFP rings colocalized with Sup35-RFP rings ( S4 Table ) . As expected , Rnq1-GFP and Sup35-RFP always remained diffuse in [pin-] cells ( S3B Fig . ) . In another version of this experiment , Sup35NM-YFP was overexpressed in [PIN+][psi-] cells expressing Rnq1-CFP under its own promoter . Sup35NM-YFP overexpressed for 24 h formed fluorescent dots or rings respectively , in 7 and 0 . 8% of the cells . In these cells , 90% of Sup35NM-YFP dots colocalized with Rnq1-CFP dots , and all Sup35NM-YFP rings colocalized with Rnq1-CFP rings ( Fig . 4C top , S5 Table ) . Curiously , these Rnq1-CFP rings looked like beads on a string , rather than an uninterrupted full ring . After 48 h of Sup35NM-YFP overexpression , Sup35NM-YFP formed rings in 11% of the cells , and 75% of these Sup35NM-YFP rings colocalized with Rnq1-CFP rings ( Fig . 4C bottom ) . In the remaining 25% of cells with Sup35NM-YFP rings , Rnq1-CFP showed diffuse or dot fluorescence ( S6 Table ) . On the other hand , essentially all Rnq1-CFP rings colocalized with Sup35NM-YFP rings ( S7 Table ) . In control experiments , [pin-] cells never formed any aggregates when Sup35NM-YFP was overexpressed ( S4A Fig . ) . [PIN+] cells showed only Rnq1-CFP dots , but no lines/rings when Sup35NM-YFP expression remained repressed in 2% Glucose ( S4B Fig . ) and when cells with empty vector expressing YFP were grown in 2% Gal ( S4C Fig . ) . These colocalization data were based on visually checking different planes of the cells by moving the focal plane up and down , and were also confirmed by collecting z-stacks from representative cells ( S5 Fig . ) . Next , we co-overexpressed Rnq1-YFP and Sup35NM-VN in [PIN+][psi-] cells ( Fig . 4D ) . In 24 h , 7% of the cells had one Rnq1-YFP dot with lines extending from it in all directions , referred to as mesh-like aggregates . In controls , when Rnq1-YFP was overexpressed in [PIN+] without overexpressing Sup35NM , 90% of the cells showed multiple fluorescent dots , 10% had diffuse fluorescence , and none had mesh-like aggregates . Also , overexpressing Rnq1-YFP and Sup35NM-VN simultaneously in [pin-] control cells did not result in any aggregate formation . When cells from cultures with Rnq1-YFP mesh-like aggregates ( 7% ) were scored for [PSI+] , 6 . 5% of these cells formed pink or white colonies and were able to grow on media lacking adenine ( SD-Ade ) , indicative of [PSI+] ( See Methods ) . To visualize if Sup35 and Rnq1 have a close physical interaction during [PSI+] induction , we co-overexpressed Sup35NM-VN and Rnq1-VC in [PIN+][psi-] cells ( S6 Fig . , S8 Table ) . Initially ( 16 h post induction ) 1 . 8% of the cells showed dots , but no lines/rings; but later ( 40 h post induction ) peripheral rings , lines and mesh-like aggregates appeared and more cells displayed dots . We also co-overexpressed Sup35NM-VN and Rnq1-VC in established [PSI+] as well as in [pin-][psi-] cells and did not observe any fluorescence . These data indicate that Rnq1 and Sup35 interact in a close proximity during [PSI+] induction , but not in established [PSI+] . As expected , overexpression of untagged Sup35NM caused Rnq1-CFP expressed from its own promoter to align in ring/line-like aggregates in 10% of the [PIN+] cells ( Fig . 4E ) . The Rnq1-CFP lines looked like beads on a string as seen previously in the presence of overexpressed YFP-tagged Sup35NM ( Fig . 4C top ) . Such beads on a string never appeared in [PIN+] cells without overexpressed Sup35NM , where Rnq1-CFP fluorescent dots remained dispersed , or in [pin-] , where Rnq1-CFP remained diffuse ( S7 Fig . ) . When cells from the culture with Rnq1-CFP beads on a string ( 10% ) were scored for [PSI+] , 11% of these cells formed pink or white colonies , indicative of [PSI+] . The above experiments show that during the de novo aggregation of Sup35 in [PIN+] cells , overexpression of Sup35NM induced Rnq1 to form mesh-like or line/ring-like aggregates . Essentially all Rnq1 line/rings perfectly overlapped Sup35 line/rings , while some Sup35 line/rings did not overlap Rnq1 . BiFC between Rnq1 and Sup35 confirmed that they form a close physical interaction during the induction of [PSI+] , and initially form dots , and then lines/meshes; while they do not form such an interaction in established [PSI+] . In order to determine what other proteins ( particularly chaperones ) colocalize with Sup35 during its aggregation in the presence of [PIN+] , we overexpressed Sup35NM-RFP in [PIN+] cells with endogenously tagged GFP proteins [91] . As seen previously [96] , we found that the molecular chaperones Hsp104 , Sis1 , and Ssa1 involved in [PSI+] propagation via their involvement in prion shearing [72] , [97]–[104] , colocalized with Sup35 rings and dots perfectly during de novo induction of [PSI+] ( Fig . 5A , S8 Fig . ) . However , Ydj1 , a Hsp40 co-chaperone shown to co-immunoprecipitate with [PSI+] aggregates as a minor component along with Hsp104 , Ssb , Sis1 , Sse1 [104] , [105] did not colocalize with Sup35 rings ( Fig . 5A ) . We also asked if proteins other than chaperones , previously found to influence the maintenance or induction of [PSI+] [22] , [106] , [107] , would colocalize with newly appearing Sup35 aggregates . We found that Sup45-GFP perfectly colocalized with newly appearing Sup35NM-RFP aggregates , as well as with established [PSI+] aggregates ( Fig . 5B ) . Upon testing other candidate proteins ( Cyc8 , New1 , Pin3 , Pin4 , Tup1 , Mod5 , Sgt2 ) , we found that none of them displayed any colocalization with Sup35NM-RFP aggregates ( S9 Fig . ) . Next , we investigated if high levels of Pin4C ( 120–668 a . a . ) , which were previously shown to substitute for [PIN+] in promoting de novo induction of [PSI+] [22] , [66] , would overlap Sup35 aggregates during [PSI+] induction in the absence of Rnq1 . We simultaneously overexpressed Pin4C-RFP and Sup35NM-GFP in 74D-694 rnq1Δ [psi-] cells ( Fig . 6 , Table 3 ) . Both proteins initially remained diffuse , but by 8 h , tiny Pin4C-RFP fluorescent dots appeared in some of the cells , all of which still had diffuse fluorescence of Sup35NM-GFP . At 16 h , Sup35NM-GFP fluorescent dots appeared and essentially all of these colocalized with Pin4C-RFP near the vacuole . At 24 h , Sup35NM-GFP started to appear as fluorescent rings in addition to dots . In these cells , essentially all Sup35NM-GFP aggregates overlapped Pin4C-RFP . At 48 h , the number of cells with Sup35NM-GFP dots decreased , while cells with rings increased , and all Sup35 aggregates still overlapped Pin4C-RFP . At 72 h , the Sup35NM-GFP dots still colocalized with Pin4C-RFP . However , almost all of the cells that had Sup35NM-GFP rings failed to show Pin4C-RFP rings . Instead , they contained large fluorescence spots of Pin4C-RFP that did not colocalize with Sup35NM-GFP . In control rnq1Δ cells that separately overexpressed either Sup35NM-GFP or Pin4C-RFP for 72 h , respectively , Sup35NM-GFP always remained diffuse , while in 50% of the cells ( n≈450 ) Pin4C-RFP formed large fluorescent dots ( S10A Fig . ) . As expected , [PSI+] appeared de novo in rnq1Δ cultures with overexpressed Sup35NM-GFP and Pin4C-RFP ( S9 Table ) . To determine the location of Pin4C aggregates relative to the vacuole during Sup35 de novo aggregation , we overexpressed Pin4C-RFP in [pin-] HSP42-GFP cells in the presence vs . absence of Sup35NM overexpression ( S10B Fig . ) . In the presence of Sup35NM overexpression , Pin4C-RFP formed one to a few foci , one of which perfectly ( in 6 . 5% of the cells; n∼800 ) or partially ( in 93 . 5% of the cells ) overlapped the Hsp42-GFP dot . In the absence of Sup35NM overexpression , Pin4C-RFP dots never perfectly overlapped the Hsp42-GFP dot; rather one of the Pin4C-RFP aggregates was juxtaposed to , or partially colocalized with the Hsp42-GFP dot . This suggests that Sup35NM overexpression promotes a more frequent closer association of the Pin4C-RFP aggregate and the vacuole-associated Hsp42-GFP protein deposit . When we simultaneously overexpressed the non-Q/N rich prion protein Mod5 tagged with GFP and Sup35NM-RFP in 74D-694 rnq1Δ cells , Sup35NM-RFP initially formed dots , and then rings/lines , while Mod5-GFP always remained diffuse ( Fig . 7A , Table 4 ) . In control rnq1Δ cells that separately overexpressed either Sup35NM-RFP or Mod5-GFP , both proteins remained diffuse ( S11A Fig . ) . Since we could not see fluorescent aggregates of Mod5-GFP , we turned to BiFC to look for an interaction between Mod5 and Sup35NM ( Fig . 7B , S11B Fig . ) . Overexpression of Mod5-VN and Sup35NM-VC did not result in any fluorescence in [pin-] cells , although [PSI+] was induced in this culture with a frequency of 0 . 9% ( n∼1000 ) suggesting that cross-seeding may not be universal for [PSI+] induction . Curiously , in [PIN+] cells , overexpression of Mod5-VN and Sup35NM-VC resulted in first diffuse fluorescence and then the formation of a single ( near the vacuole ) to multiple dots over time in 15% of cells ( Fig . 7B ) . Also , Mod5-VN and Mod5-VC overexpression in [pin-] cells did not show any fluorescence , but in [PIN+] cells they showed diffuse fluorescence ( S11C Fig . ) . Possibly , newly appearing Sup35NM aggregates in [PIN+] cells are attracted to the Mod5 aggregates seen as diffuse fluorescence . These findings indicate that during the de novo aggregation of overexpressed Sup35 promoted by overexpression of Q/N-rich Pin4C in the absence of Rnq1 [22] , [66] , Sup35 aggregates initially colocalize with Pin4C aggregates ( near the vacuole ) , but Pin4C falls off the Sup35 rings later . Furthermore , Pin4C-RFP perfectly overlapped Hsp42-GFP only in the presence of Sup35 overexpression . The data is consistent with the cross-seeding of Sup35 aggregation by Pin4C aggregates in the absence of Rnq1 . However , although the overexpression of the non-Q/N rich protein Mod5 promotes [PSI+] induction [27] , we could not visualize Mod5-Sup35 direct interaction in the absence of [PIN+] suggesting that Mod5-promoted de novo Sup35 aggregation occurs via a different mechanism . The Hsp104 chaperone requirement for the maintenance of [PSI+] [72] and the colocalization of Hsp104 with Sup35 dots and rings during the induction of [PSI+] ( [96] , Fig . 5A ) led us to ask if Hsp104 is also required for the de novo aggregation of Sup35 during [PSI+] induction . Since Hsp104 is required for the maintenance of [PIN+] , and the requirement for [PIN+] in the de novo induction of [PSI+] can be overcome by overexpressing certain Sup35NM-containing fragments , e . g . with a short extension of hydrophobic residues [108] , we overexpressed Sup35NM with a short extension of hydrophobic residues ( magic tail ) , previously shown to induce [PSI+] even in [pin-] cells [49] , [108] . Overexpression of Sup35NM with this magic tail ( Sup35NM-mt ) in [pin-] HSP104 cells , caused endogenous Sup35-GFP molecules to form dots and short lines in 6% of the cells ( n≈1200 ) ( Fig . 8A ) and this increased to 15% ( n≈1400 ) of the cells in the presence of [PIN+] . Unlike the Sup35 dots induced in [PIN+] cells by 24 h of overexpression of Sup35NM without magic tail , Sup35 dots induced by Sup35NM-mt in [pin-] HSP104 or [PIN+] HSP104 cells did not always appear near the vacuole . In [pin-] hsp104Δ cells however , no dots were seen and only 0 . 4% of the cells ( n≈1700 ) formed Sup35-GFP lines . Furthermore , all these lines appeared to be at the cell membrane as opposed to those seen in the cytoplasm in HSP104 cells . In an alternative approach to test the role of Hsp104 in [PSI+] induction , we used Pin4C overexpression to substitute for [PIN+] . We co-overexpressed Sup35NM-GFP and Pin4C-RFP in [pin-] hsp104Δ cells ( Fig . 8B ) , and Sup35NM-GFP remained diffuse , while in control [pin-] HSP104 or [PIN+] HSP104 cells , as expected , Sup35NM-GFP formed dots and rings/lines respectively in 7% and 9% of the cells . Also , Pin4C-RFP aggregates were not affected by the presence vs . absence of Hsp104 in [pin-] cells , but were larger in the presence of [PIN+] ( S12 Fig . ) . Co-overexpression of Sup35NM-GFP and Pin4C-RFP in [pin-] HSP104 cells in the presence of GuHCl , which inhibits Hsp104's ATPase activity [79] resulted in the formation of only Sup35NM-GFP dots in 2 . 8% of cells , but no rings/lines and failed to induce any [PSI+] cells ( Fig . 8C ) . Taken together , the striking differences in the level and types of Sup35 aggregate formation in the presence vs . absence of Hsp104 and in the presence vs . absence of GuHCl suggest that Hsp104 is required for the formation of de novo Sup35 aggregates , and induction of [PSI+] de novo .
Protein aggregates have been implicated in a wide variety of diseases including Amyotrophic Lateral Sclerosis , Alzheimer's , Parkinson's and prion disease [109] , [110] . Interactions between proteins associated with protein misfolding diseases ( PMD ) are of great interest since molecular cross-talk between disease aggregates of one protein can accelerate the de novo appearance of heterologous disease protein aggregates [16] , [60] , [111]–[115] . Several reports implicate cross-seeding as a mechanism to explain this [17] , [18] . Here , our data provide insight into the mechanism of prion induction , which is a model for such heterologous interactions in human diseases . Our data suggest that cross-seeding is not the only mechanism for this cross-talk phenomenon . While our findings that [PIN+] or Pin4C aggregates physically interact with Sup35 de novo aggregates are consistent with the cross-seeding model , the failure of Mod5 to interact with Sup35 suggests the existence of another mechanism , possibly via hindering the chaperone network . We stimulated the de novo generation of a prion in yeast by overexpressing fluorescent derivatives of the prion protein and then monitored its aggregation status . Based on our findings ( Fig . 1–3 , 6 , S1–2 Fig . ) , we propose a model to explain the pathway followed by Sup35 during its de novo conversion into mature [PSI+] ( Fig . 9A ) . Bimolecular complementation [88] , [89] using BiFC-tagged Sup35NM ( Fig . 1C ) showed that Sup35NM molecules do not associate throughout the cytoplasm , but first interact at specific sites in the cell . This means that the de novo aggregation of Sup35 first occurs at these sites rather than being brought to them as pre-existing aggregates . This may be true of other prion-like aggregating proteins as well . How could prion-like proteins first interact within discrete inclusions ? We speculate that upon initial expression , Sup35 is soluble , but upon overexpression , some molecules of the intrinsically unstructured Sup35NM misfold . We suggest that this misfolded protein could be captured by quality control compartments ( QCCs ) as inclusions , i . e . recently discovered Q-bodies [116] , where misfolded proteins accumulate en route to degradation . The high local concentration of Sup35 at these sites increases the likelihood of prion induction . Furthermore , [PIN+] prion aggregates , which are required for [PSI+] induction [21] , [22] , [51] , are also located at these sites , where they could facilitate nucleation for Sup35 [53] , [87] , [117] , [118] to polymerize Sup35 into amyloid . In Pin4C-promoted [PSI+] induction , Pin4C appears to take over the role of [PIN+] aggregates . This suggests that the co-existence of misfolded protein with heterologous amyloid in inclusions accelerates de novo conversion of the misfolded protein into amyloid . However , not all of these inclusions give rise to larger Sup35 fibrils . Rather , Sup35 aggregates away from the perivacuolar site disappear , and Sup35 lines and rings emanate only from the single inclusion in the cell near the vacuole ( Fig . 1–3 , 6 ) . This perivacuolar inclusion also differs from the other inclusions because it alone colocalizes with Hsp42 . Furthermore , the finding of only one fluorescent dot in [PIN+] cells with overexpressed BiFC-tagged Sup35NM and Rnq1 ( S6 Fig . ) suggests that Sup35 and Rnq1 interact only at the perivacuolar site . It is unclear what happens to the other inclusions , they could be solubilized , degraded or join the remaining perivacuolar aggregate . This suggests that the fibrillar growth of de novo aggregates requires site-specific chaperones . Curiously , heterologous aggregates are not only involved in the initial cross-seeding , but continue to be associated with some newly seeded heterologous fibrils . This is surprising since once nucleated by [PIN+]/Pin4C amyloid , Sup35 polymerization should continue without the need for Rnq1/Pin4C seed . Indeed , due to the higher efficiency of homotypic polymerization [55] , [118] , [PIN+]/Pin4C aggregates are not expected to incorporate into the growing Sup35 fibrils . Paradoxically , Rnq1 frequently ( Pin4C always ) are found to overlap newly appearing Sup35 rings ( Fig . 4 , 6 ) . We propose that although the initial step in nucleation is heterotypical , [PIN+]/Pin4C aggregates might also grow in length homotypically in close proximity to the Sup35 aggregates via a lateral interaction , possibly with the help of chaperones that are associated with the aggregates . Indeed , our findings that all Rnq1/Pin4C rings colocalized with Sup35 rings ( S4 Table ) ; and that Rnq1/Pin4C formed mesh/ring-like aggregates only in the presence of Sup35 overexpression ( Fig . 4D–E , S6 Fig . ) support this hypothesis , which predicts that Sup35 rings template the continued growth of Rnq1/Pin4C into rings and not vice versa ( see Fig . 9B ) . Mature [PSI+] dots do not associate with [PIN+] in the same manner as newly induced [PSI+] aggregates do . Indeed , although Rnq1 was found to co-immunoprecipitate with newly appearing Sup35 aggregates [63] , [119] , it was not detected in purified [PSI+] aggregates [104] . Here , we show the formation of fluorescent dots and mesh-like aggregates by co-overexpressed Rnq1-VC and Sup35NM-VN during [PSI+] induction , and the inability of Rnq1-VC and Sup35NM-VN to cause fluorescence in established [PSI+] , suggesting that Rnq1 and Sup35 are in close proximity during [PSI+] induction , but not so close in established [PSI+] ( S6 Fig . , S8 Table ) . Mature and newly induced Sup35 aggregates also differ in their amyloid characteristics as our data showed that all of the mature [PSI+] aggregates were stained in situ with amyloid-binding dye , thioflavin T , while only 30% and 60% of respectively , newly appearing Sup35 dots and rings were stained with ThT ( Fig . 2 ) . This could be either because cross-talk between heterologous amyloid aggregates may not always convert the prion-like protein into amyloid vs . amorphous aggregates , or interference of other proteins attracted to aggregates in situ may cause false negative results . We favor the latter possibility as most viable Sup35 ring-bearing cells give rise to [PSI+] progeny [84] , [85] . However , it is possible that dead cells have non-amyloid Sup35 rings . Alternatively , it is also possible that newly appearing Sup35 aggregates that are stained with Thioflavin T harbor Rnq1 amyloid , leading to the ThT staining , while those Sup35 aggregates that are not stained do not harbor Rnq1 amyloid , leading to the failure of ThT staining . This would imply that the Sup35 molecules in the dot and ring structures are not amyloid . While colocalization of a protein with heterologous aggregates is consistent with cross-seeding , it is not proof of cross-seeding . Indeed , the strict and permanent colocalization of Sup45 with Sup35 newly appearing aggregates and with mature [PSI+] aggregates ( Fig . 5B ) suggests that Sup45-GFP simply decorates all Sup35 aggregates . However , the considerable and transient colocalization of respectively , Rnq1 and Pin4C with Sup35 newly appearing aggregates , but only partial and no colocalization of respectively , Rnq1 and Pin4C [66] with mature [PSI+] aggregates supports the idea that as opposed to Sup45 , Rnq1 and Pin4C actually cross-seed Sup35 de novo aggregates . It is noteworthy that Sup45 is not required for [PSI+] induction [86] , but [PIN+] , or one of its substitutes , Pin4C is . Also , the colocalization of the molecular chaperone Hsp104 with all Sup35 aggregates ( Fig . 5A , [120] ) suggests that Hsp104 decorates rather than cross-seeds Sup35 . Such decoration could enable Hsp104 to perform its known shearing activity of [PSI+] aggregates that is required for [PSI+] propagation [72] , [80]–[82] . We showed that Hsp104 itself is also required for de novo induction of [PSI+] by finding inhibition of the de novo aggregation of Sup35 in [pin-] cells lacking Hsp104 ( Fig . 8A , B ) and inhibition of de novo induction of [PSI+] in [PIN+] cells in the presence of GuHCl ( Fig . 8C ) , which inhibits Hsp104's activity [79] . This is consistent with a previous report that overexpression of Hsp104 enhances prion appearance [121] . Although cross-seeding is generally thought to explain the cross-talk that enables amyloid aggregates to promote conversion of heterologous prion-like protein to amyloid , our data suggest that another mechanism is also involved . Indeed , we showed that in the absence of [PIN+] , overexpression of the non-Q/N rich prion protein Mod5 enhances [PSI+] formation without direct physical interaction with Sup35 ( Fig . 7B , S11B Fig . ) . Possibly , instead of cross-seeding which requires a physical interaction , excessive amounts of misfolded Mod5 proteins in [pin-] cells sequester chaperones away from newly forming Sup35 aggregates in the cell , and thus allow them to mature into a prion . Since Mod5-promoted [PSI+] induction is rare compared to [PIN+]-promoted induction , cross-seeding appears to be more efficient than the other mechanism in promoting de novo prion formation . [PIN+] also appears to influence de novo aggregation of Mod5 . Bimolecular complementation using BiFC-tagged Mod5 ( S11C Fig . ) showed that Mod5 prion protein interacts with itself , resulting in diffuse fluorescence only in [PIN+] , but not in [pin-] cells . Curiously , an interaction between Sup35NM-VC and Mod5-VN is also seen as diffuse fluorescence , and again only in [PIN+] cells ( Fig . 7B ) . Possibly , the Mod5 diffuse aggregates present in [PIN+] cells attract and interact with Sup35NM aggregates . The data presented here aid our understanding of how prion formation occurs in yeast , and provide clues to the molecular mechanisms underlying many human aggregating neurodegenerative diseases , particularly these arising more frequently in people with preexisting neurodegenerative disease .
Yeast plasmids and strains used in this study are listed in Tables 5 and 6 , respectively . All [PIN+] cells used in the study were high [PIN+] [34] . GF657 , GF658 and GF844 are , respectively , [PSI+][PIN+] HSP104 , [psi-][pin-] HSP104 and [psi-][pin-] hsp104Δ versions of 74-D694 with endogenous SUP35 replaced with SUP35-GFP ( kindly supplied as SY80 , SY84 , and SY97 by T . R . Serio , U . Arizona ) [75] . L3107 and L2903 were obtained independently by curing GF657 of [PSI+] by overexpressing Pin4C [66] . GF852 and GF855 , respectively , are [psi-][PIN+] and [psi-][pin-] versions of 74-D694 with RNQ1-CFP under its own promoter integrated into the genomic TRP1 ( kindly supplied as 645 and 651 by L . Li , Northwestern U . ) . GF647 was constructed by replacing chromosomal RNQ1 with KanMX4 in 74D-694 [122] . All other yeast strains used in the studies of colocalization with Sup35 are from the BY4741 GFP library strain ( Life Technologies , CA ) harboring the gene of interest tagged endogenously with GFP [91] . To obtain [pin-] versions of these cells , they were grown on YPD plates with 5 mM GuHCl for three passes [50] . All overexpression plasmids in this study were driven by the GAL1 promoter unless otherwise stated . p1951 ( Sup35NM-GFP ) was constructed by inserting the SUP35NM BamHI-NotI fragment , and the GFP NotI-SacI fragment in-frame into the pRS413GAL1 plasmid backbone . p1893 ( Sup35NM-VN ) was constructed by replacing the GFP NotI-SacI fragment in p1951 with the VN173 NotI-SacI fragment PCR-amplified from pFA6a-HIS3MX6-pGAL1-VN173 [88] . p1893-2 was constructed by moving the GAL1-SUP35NM-VN XhoI-SacI fragment in p1893 to the pRS415 backbone . p2170 was constructed by replacing the SUP35NM BamHI-NotI fragment in p1893 with the MOD5 BamHI-NotI fragment PCR-amplified from the genome . p2171 was constructed by replacing the SUP35NM BamHI-NotI fragment in p1892 with the MOD5 BamHI-NotI fragment PCR-amplified from the genome . p1892 ( Sup35NM-VC ) was constructed by ( 1 ) replacing the GFP NotI-SacI fragment in p1951 with the VC155 NotI-SacI PCR-amplified from pFA6a-HIS3MX6-pGAL1-VC155 [88] , and ( 2 ) moving this GAL1-SUP35NM-VC155 XhoI-SacI fragment into the XhoI-SacI sites of pRS414 . p1894 was constructed by replacing the SUP35NM BamHI-NotI fragment in p1892 with the RNQ1 BamHI-NotI fragment PCR-amplified from the genome . p1984 was constructed by cloning the XmaI-Sal1 fragment of p1156 into p742 . p2036 was constructed by replacing the YFP SpeI-XhoI fragment in p1752 with the NM ( TAA ) SpeI-XhoI fragment PCR-amplified from the genome [122]–[124] . p1753 was described previously [87] , [96] , [125] , [126] . p2017 and p2018 vectors ( Sup35NM-RFP ) with URA3 or LEU2 markers , respectively were constructed in a two-step cloning: ( 1 ) The GFP NotI-SacI fragment in p1951 was replaced with the RFP NotI-SacI fragment amplified from p1708 . ( 2 ) Then , this GAL1-NM-RFP XhoI-SacI fragment was cloned into pRS416 ( URA3 ) and pRS415 ( LEU2 ) backbones , respectively . All other plasmids listed in Table 5 were described previously [49] , [62] , [66] , [85] , [122] , [127] . Yeast strains were cultivated using standard media and growth conditions [128] . Rich media contained 2% dextrose ( YPD ) . Synthetic complete media contained all amino acids except for those used for selection and 2% dextrose ( SD , 2% Dex ) or 2% galactose ( 2% Gal ) . Synthetic liquid media contained amino acids lacking the selective ones and 2% raffinose plus ( SRGal ) or minus 2% Gal ( SRaf ) . Yeast cells with Sup35 overexpression plasmids were grown in synthetic liquid selection media ( SRaf ) overnight . Unless otherwise stated , 2% Gal was added to the culture ( OD∼0 . 5 ) to induce de novo Sup35 aggregation . In time course experiments where time exceeded 48 h , cultures were diluted back to OD∼0 . 5 in a fresh growth media to keep cells in exponential phase . After de novo [PSI+] was induced in [psi-][PIN+] cells , they were grown on synthetic dropout media with 2% dextrose ( SD ) for many generations to maintain [PSI+] ( ∼8 days ) . Then , they were grown in 0 . 05% Gal for 3-4 h to allow Sup35NM-YFP to decorate existing [PSI+] aggregates . [PSI+] induced de novo was scored in yeast as described previously [33] , [49] , [72] , [129] , [130] . [PSI+] but not [psi-] causes read-through of the nonsense mutation , ade1-14 . The ade1-14 mutation causes the accumulation of a red by-product in the adenine biosynthesis pathway , so [psi-] ade1-14 cells are red . In [PSI+] cells , when nonsense mutations are suppressed , ade1-14 cells become pink or white in rich media ( YPD ) . In addition , the read-through of the ade1-14 allele in [PSI+] allows them to grow in media lacking adenine ( SD-Ade ) , while [psi-] cells cannot grow on this medium [49] . To confirm that Ade+ cells are of [PSI+] rather than suppressor mutants , they were mated with a tester strain ( [psi-] SUP35-GFP , GF658 ) to look for multiple fluorescent dots formed by endogenous Sup35-GFP in only [PSI+] cells . To locate the vacuole , cells were stained with FM4-64 as described previously [90] . Yeast cells were stained with Thioflavin T according to a protocol adapted from ref . [131] with the addition of two extra washes in PMST [0 . 1M KPO4 ( pH 7 . 5 ) , 1 mM MgCl2 , 1 M Sorbitol , 0 . 1% Tween 20] . Aggregates formed in cells by fluorescently labeled proteins were examined with a Nikon Eclipse E600 fluorescent microscope ( 100X oil immersion ) and/or an Olympus FV1000 confocal microscope ( 60X oil immersion , with 1 . 6 magnifier ) . Colocalization was visualized by the confocal microscope using the channels of interest and by moving the focal plane up and down . Z-stacks were analyzed to confirm colocalization of proteins with 8-12 layers , with 0 . 5-1 µm increments . In dual color RFP/GFP studies , the RFP channel was always examined first to prevent visualization of activated GFP in the RFP channel . Upon the induction of overexpression of proteins tagged with VN or VC with galactose , cells were lysed as described previously [132] . Equal amounts of total proteins in precleared lysates were analyzed by Western blot using previously described antibodies [27] , [63] , [66] , [104] . | Certain proteins can misfold into β-sheet-rich , self-seeding aggregates . Such proteins appear to be associated with neurodegenerative diseases such as prion , Alzheimer's and Parkinson's . Yeast prions also misfold into self-seeding aggregates and provide a good model to study how these rogue polymers first appear . De novo prion appearance can be made very frequent in yeast by transient overexpression of the prion protein in the presence of heterologous prions or prion-like aggregates . Here , we show that the aggregates of one such newly induced prion are initially formed in a dot-like structure near the vacuole . These dots then grow into rings at the periphery of the cell prior to becoming smaller rings surrounding the vacuole and maturing into the characteristic heritable prion tiny dots found throughout the cytoplasm . We found considerable colocalization of two heterologous prion/prion-like aggregates with the newly appearing prion protein aggregates , which is consistent with the prevalent model that existing prion aggregates can cross-seed the de novo aggregation of a heterologous prion protein . However , we failed to find any physical interaction between another heterologous aggregating protein and the newly appearing prion aggregates it stimulated to appear , which is inconsistent with cross-seeding . | [
"Abstract",
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] | 2015 | Heterologous Aggregates Promote De Novo Prion Appearance via More than One Mechanism |
Sparganosis is a neglected but important food-borne parasitic zoonosis . Clinical diagnosis of sparganosis is difficult because there are no specific manifestations . ELISA using plerocercoid crude or excretory–secretory ( ES ) antigens has high sensitivity but has cross-reactions with other helminthiases . The aim of this study was to characterize Spirometra erinaceieuropaei cysteine protease ( SeCP ) and to evaluate its potential application for serodiagnosis of sparganosis . The full length SeCP gene was cloned , and recombinant SeCP ( rSeCP ) was expressed and purified . Western blotting showed that rSeCP was recognized by the serum of sparganum-infected mice , and anti-rSeCP serum recognized the native SeCP protein of plerocercoid crude or ES antigens . Expression of SeCP was observed at plerocercoid stages but not at the adult and egg stages . Immunolocalization identified SeCP in plerocercoid tegument and parenchymal tissue . The rSeCP had CP activity , and the optimum pH and temperature were 5 . 5 and 37°C , respectively . Enzymatic activity was significantly inhibited by E-64 . rSeCP functions to degrade different proteins and the function was inhibited by anti-rSeCP serum and E-64 . Immunization of mice with rSeCP induced Th2-predominant immune responses and anti-rSeCP antibodies had the potential capabilities to kill plerocercoids in an ADCC assay . The sensitivity of rSeCP-ELISA and ES antigen ELISA was 100% when performed on sera of patients with sparganosis . The specificity of rSeCP-ELISA and ES antigen ELISA was 98 . 22% ( 166/169 ) and 87 . 57% ( 148/169 ) , respectively ( P<0 . 05 ) . The rSeCP had the CP enzymatic activity and SeCP seems to be important for the survival of plerocercoids in host . The rSeCP is a potential diagnostic antigen for sparganosis .
Spirometra erinaceieuropaei ( syn . S . erinacei or S . mansoni ) is an intestinal tapeworm of wild and domesticated carnivores [1] and is most commonly seen in Asia , whereas Spirometra mansonoides is mainly found in North America [2] . Sparganosis is a zoonotic parasitic disease caused by the plerocercoids of the genus Spirometra . Plerocercoid infections in humans are acquired by ingesting raw or uncooked reptilian or amphibian flesh , placing frog or snake flesh on open lesions or inflamed areas , or drinking water contaminated with cyclops harboring procercoids . When the plerocercoid infects humans , it migrates widely in subcutaneous tissues and visceral organs where it undergoes no further development [3 , 4] and causes cutaneous and visceral larva migrans . In some cases , the larvae localize in vital organs or the central nervous system causing seizures , headache , blindness , epilepsy , paralysis , and even death . Ocular sparganosis is especially prevalent in China and Vietnam [5] . Sparganosis is one of a neglected tropical disease , but it is an important food-borne parasitic zoonoses . The diagnosis of sparganosis is very difficult and is often misdiagnosed because the larvae have no predilection for particular sites in the human body and specific clinical manifestations are lacking . A diagnosis of subcutaneous sparganosis can be made by detection of the larvae in a biopsy specimen , but a definitive diagnosis is very difficult for visceral and cerebral sparganosis as the larvae can be found only by surgical removal [6] . ELISA with crude or excretory–secretory ( ES ) plerocercoid antigens has high sensitivity for the detection of anti-plerocercoid antibodies , but the main disadvantage is the existence of an early “blind window” of time that results in false negatives during the early stages of infection and cross-reactions with serum samples from patients with other helminthiases ( cysticercosis , paragonimiasis , clonorchiasis , etc . ) [7 , 8] . Furthermore , the preparation of crude or ES plerocercoid antigens for ELISA requires the collection of plerocercoids from naturally infected hosts or experimentally infected laboratory animals , which is practically inconvenient in terms of cost , labor , and time . Recombinant proteins can be produced easily in large amounts by using the in vitro expression system and can be used as a good alternative to the crude or ES antigens in a standardized ELISA for serodiagnosis of sparganosis . Hence , studies on the sensitive and specific recombinant plerocercoid antigens will improve the early diagnosis and subsequent treatment of the disease . Cysteine protease ( CP ) is a type of protein hydrolase that has cysteine residues in the active center of the enzyme and plays a principal role in the development and survival of parasites . CP has been used as a diagnostic marker and vaccine target for some parasitic diseases because of their immunogenicity [9] . Purified native or recombinant CP has been used for the diagnosis of sparganosis [10] , schistosomiasis [11] , fascioliasis [12] , clonorchiasis [13] , paragonimiasis [14] and ascariasis [15] . CP with different molecular weights ( 53 , 36 , 27 or 21 kDa ) has been found in S . erinaceieuropaei plerocercoid soluble antigens [16–18] . The 36 kDa protein is the main antigenic component of plerocercoid ES proteins [19] . Some plerocercoid CP have been identified , and their biochemical properties and biological roles have been identified [10 , 20 , 21] . In our previous studies , S . erinaceieuropaei CP ( SeCP , BAB62816 , GI:15146346 ) was identified from the crude and ES proteins of S . erinaceieuropaei plerocercoids by two-dimensional electrophoresis ( 2-DE ) and Western blotting combined with MALDI- TOF/TOF-MS [22 , 23] . The structure and function of SeCP were predicted using bioinformatics . The results showed that SeCP was a type of proteolytic enzyme with a variety of biological functions , and its gene sequence was 1 053bp length with the largest ORF at 1 011bp encoding 336 amino acids . SeCP contained a signal peptide , a complete cathepsin propeptide inhibitor domain , and a peptidase_C1A conserved domain located outside the membrane . No transmembrane domain was predicted . The secondary structure prediction for SeCP showed that there were 8 α-helixes , 7 β-strands , and 20 coils . S . erinaceieuropaei had the closest evolutionary status to S . mansonoides based on the SeCP phylogenetic analysis . SeCP had 15 potential antigenic epitopes and 19 HLA-I restricted epitopes , and it might be a potential diagnostic antigen for sparganosis [24] . The aim of this study was to express and characterize SeCP encoding a 36 kDa protein ( BAA09820 , GI:1834307 ) and to evaluate its potential application in the serodiagnosis of sparganosis .
This study was carried out in accordance with the National Guidelines for Experimental Animal Welfare ( MOST of People’s Republic of China , 2006 ) . All animal procedures and the use of the patients’ serum samples in this study were approved by the Life Science Ethics Committee of Zhengzhou University ( no . 2011–016 ) . Before the patients’ serum samples were used , oral informed consent was obtained from all individuals . Plerocercoids were obtained from subcutaneous tissues and muscles of naturally infected frogs , which were collected from Henan province , China . The morphological and molecular analysis showed that all plerocercoid isolates in Henan province belonged to S . erinaceieuropaei plerocercoids . The plerocercoids were maintained by serial passage in BALB/c mice every 10–12 months . Adult S . erinaceieuropaei worms were collected from the small intestines of cats experimentally infected with plerocercoids at 2 months post infection [25 , 26] . The adults were washed with cold physiological saline disposed by DEPC . The samples were used immediately for RNA preparation or stored in liquid nitrogen until use . Specific pathogen free ( SPF ) female BALB/c mice aged 5–6 weeks were used for the immunological studies . All mice were purchased from the Experimental Animal Center of Henan province ( Zhengzhou , China ) . Ten female BALB/c mice were orally inoculated with 3 plerocercoids , and blood samples were collected when euthanized at 4 weeks post infection . The pre-infection serum samples from mice were used as a negative control . The serum samples of patients with sparganosis , echinococcosis , cysticercosis , schistosomiasis , paragonimiasis , clonorchiasis or trichinellosis were collected from our department . These patients were confirmed by a positive parasitological examination or specific serum antibodies . Healthy person sera were obtained from normal healthy individuals who were negative for serum specific antibodies of the above-mentioned parasitic diseases . Crude antigens and ES antigens from S . erinaceieuropaei plerocercoids were prepared as described previously [22 , 23 , 27] , and the protein concentration was determined by the Bradford method at 4 . 2 mg/ml and 1 . 04 mg/ml , respectively . The full-length cDNA sequence of the SeCP gene was obtained from GenBank ( D63670 , protein is BAA09820 , GI:1834307 ) and analyzed by bioinformatics [24] . SeCP has a signal peptide with 19 amino acids . While designing the specific primers , the N-terminal signal peptide sequence was omitted and the SeCP molecular weight was approximately 36 kDa . The SeCP gene was amplified by nested PCR . First , the target cDNA underwent the first run of PCR with the first set of primers ( forward , 5' TAGGATGAAGTTCGTAATATACGTTGCC 3'; reverse , 5'-CCAAA AGATGTTTATTTACTCCACAGGTG-3’ ) , and the cycling protocol was as follows: 28 cycles of 94°C for 1 min , 50°C for 45 s and 72°C for 1 min . The products underwent a second run with the second set of specific primers carrying EcoRIand Hind III restriction enzyme sites ( bold and italicized ) ( forward , 5’-CGGAATTCTCGACTGAA AGTGAGACGTACGTCC-3’ and 5’- CCCAAGCTTTTACACG GTTGGATAGCTTGCCAT -3’ ) , and the cycling protocol was as follows: 28 cycles of 94°C for 1 min , 56°C for 45 s and 72°C for 1 min . The final PCR products were purified , digested , and cloned into the pGEM-T vector ( Promega , USA ) and subsequently sub-cloned into the expression vector pMAL-c2X ( New England Biolabs , USA ) . The recombinant plasmid was then transformed into Escherichia coli TB1 ( New England Biolabs , USA ) . Expression of rSeCP was induced by adding 0 . 1 mM IPTG at 30°C for 3 h . The rSeCP was purified by Amylose Pre-packed Column ( NEB Ltd , China ) and identified by SDS-PAGE . Images of gels were recorded using ImageScanner ( GE Healthcare , Fairfield , CT ) . Another gel was prepared by the same method and used for the Western blotting analysis described below . Thirty BALB/c mice were randomly divided into three groups of ten animals each . The immune mice were subcutaneously vaccinated with 20 μg of purified rSeCP with an equal volume of complete Freund’s adjuvant followed by three boosts with the same dose of the incomplete adjuvant at 10-day intervals [28] . The control group of mice was injected only with adjuvant or PBS using the same immunization schedule . Approximately 50 μl of tail blood were collected at 0 , 10 , 20 , 30 , and 40 days post-immunization from the vaccinated mice . The specific anti-rSeCP antibody levels of IgG and its subtype ( IgG1 and IgG2a ) in serum samples of immunized mice were assayed using ELISA with rSeCP ( 2 . 5 μg/ml ) as described previously [29] . The purified rSeCP and the crude and ES plerocercoid antigens were separated by SDS–PAGE ( 12% gel ) and transferred onto nitrocellulose ( NC ) membranes ( Millipore , USA ) at 18 V for 35 min by semi-dry transfer cell ( Bio-Rad , USA ) . Western blotting of rSeCP antigenicity was performed as described previously [25 , 30] . To observe transcription of the SeCP gene at different S . erinaceieuropaei developmental stages , total RNA was extracted from the plerocercoids of frogs or mice and the adults from cats . RT-PCR was performed as previously described [28] and the primers specific to SeCP were the first set of primers described above . As an internal control , S . erinaceieuropaei glyceraldehyde-3- phosphate dehydrogenase ( GAPDH , GenBank accession No . AB031067 . 1 ) was used as the housekeeping gene for this study and the PCR product size of the internal control was 670 bp . Amplified PCR products were analyzed on a 1% agarose gel . Negative control reactions , which contain all of the reagents except Milli-Q water being substituted for cDNA as the template , were included to ensure that the reaction system was not contaminated . The entire experiment was carried out three times . IFT was used to locate the position of SeCP in the cestode . The tissue sections of S . erinaceieuropaei plerocercoids and adult worms was first retrieved after microwaving for 20 min with a 0 . 01 M citric acid buffer ( pH 6 . 0 ) , blocking with 5% normal goat serum in PBS , and then incubating at 37°C for 1 h with a 1:10 dilution of anti-rSeCP serum , serum of mice infected with plerocercoids , normal mouse serum or PBS . After washing three times in PBS , the sections were incubated with a 1:50 dilution of FITC-labeled anti-mouse IgG ( Santa Cruz , USA ) , and the nuclei were stained with propidium iodide ( PI ) at 37°C for 15 min . After washing five times with PBS , the sections were examined under a fluorescent microscope ( Olympus , Japan ) [31] . The enzymatic activity of rSeCP was assayed by substrate gel electrophoresis with a 12% SDS–PAGE gel copolymerized with 0 . 1% gelatin as the substrate , as previously reported [32 , 33] . The enzymic activity of rSeCP was also determined by cleavage of the fluorescent substrate Z-carbobenzoxy-L-phenylalanyl-L-arginine- ( 7-amino-4-methylcoumarin ) ( Z-Phe-Arg-AMC , Sigma ) as previously described [34] . Briefly , the substrate was prepared at a concentration of 2 mM dissolved in dimethylsulfoxide ( DMSO ) . The reaction was carried out in a volume of 240 μl of standard assay buffer ( 100 mM sodium acetate , 5 mM dithiothreitol ( DTT ) ; pH 5 . 5 ) coupled with an appropriate quantity of enzyme . The rSeCP was pre-incubated in assay buffer at a volume of 160 μl at 37°C for 30 min , while substrate at a final concentration of 3 μM was pre-incubated in assay buffer as well . The reaction was started by mixing the two samples together . The fluorescence intensity was continuously measured with spectrophotofluorometry ( Synergy H1 , BioTek , USA ) using excitation and emission wavelengths of 355 nm and 460 nm , respectively . The pH activity profiles were established using the following buffers: 100 mM sodium acetate buffer ( pH 3 . 0–5 . 5 ) , 100 mM sodium phosphate ( pH 6 . 0–7 . 5 ) , and 100 mM Tris–HCl ( pH 8 . 0–8 . 5 ) containing 5 mM DTT . The optimal temperature for rSeCP activity was assayed at 10°C , 20°C , 28°C , 37°C , 45°C and 50°C . The residual activity in the samples and the control ( without reagents ) was also determined . The highest enzyme activity was used as the control ( 100% of relative activity ) . The influence of metal ions on rSeCP activity was determined and different concentrations of Cu++ , Mn++ and Zn++ metal ions ( 0 . 01 mM , 0 . 1 mM , 1 mM , 10 mM , and 100 mM ) were added to the assay in the form of CuCl2 , MnCl2 and ZnCl2 , respectively . The relative fluorescence unit ( RFU ) was used to express catalytic activity . rSeCP was also pre-incubated with inhibitor at 37°C for 30 min . Substrate was added , and incubated at 37°C for 30 min . Inhibitors included PMSF , phenylmethylsulfonyl fluoride; AEBSF , 4- ( 2-Aminoethyl ) benzenesulfonyl fluoride; EDTA , ethylenediaminetet-raacetate; E-64 , and L-trans-epoxysuccinyl-leucylamide ( 4-guanidino ) butane . Percentages are based on activity in the presence of 10 mM DTT without inhibitors . Rabbit immunoglobulin ( Ig ) , human Ig ( Laboratorios LANDERLAN . S . A . Spain ) , bovine hemoglobin ( Hb ) , fibronectin , and bovine serum albumin ( BSA , Sigma ) were used to determine the hydrolytic function of rSeCP . Each protein ( 1 mg/ml ) was incubated with rSeCP ( 1 μg ) in 100 mM sodium acetate ( pH 5 . 5 ) or 100 mM sodium phosphate ( pH 7 . 0 ) containing 5 mM DTT at 37°C overnight . Each protein ( 1 mg/ml ) was also incubated with different rSeCP concentrations ( 1 , 2 or 3 μg ) in 100 mM sodium acetate ( pH 5 . 5 ) . The inhibition of anti-rSeCP serum on SeCP catalytic activity was determined by using human Ig as the substrate for rSeCP activity as described previously [35] . For the inhibition assay , 3 μg of rSeCP was incubated with anti-rSeCP serum at 37°C for 1 h , following by incubation at 37°C overnight with the addition of 1 mg/ml final concentration of human Ig . The total volume of the mixture was 40 μl . Anti-rSeCP serum used in this assay was diluted at 1:50 , 1:100 , 1:500 , and 1:1000 , respectively . The inhibitor E-64 was also used to determine the enzymatic activity with the same method . After incubation , 5 μl of each sample was analyzed with 12% SDS–PAGE as described above [36] . To determine the cytotoxic effects of anti-rSeCP antibodies to plerocercoids an in vitro ADCC assay was performed as described previously [37] . Sera from plerocercoid-infected mice were used as the positive control , normal mouse sera served as negative controls , and PBS as the blank control . Briefly , the ADCC assay was performed by adding 10 plerocercoids to a suspension of 2×105 mouse peritoneal macrophages ( MPM ) collected from normal BALB/c mice . Sera were diluted at 1:10 with RPMI 1640 media and added to the suspension to make a final volume of 2 ml . The suspension was then added to 6 well culture plates and incubated at 37°C and 5% CO2 for 48 h . Plerocercoid viability was identified by the morphology and activity under a light microscope at different time intervals after incubation . Worms that were limp or straight without movements were counted as non-viable and disintegrated worms were counted as dead . The live larvae were active and wriggling [37 , 38] . Results were expressed as the ratio of immobile or dead parasites to the total number of parasites recovered within each experiment . ELISA with rSeCP ( rSeCP-ELISA ) and ES antigens ( ES-ELISA ) were performed as previously described [27] . Briefly , the ELISA plates ( Corning , USA ) were coated with rSeCP ( 2 . 5 μg/ml ) and ES proteins ( 2 . 5 μg/ml ) in 100 μl of bicarbonate buffer ( pH 9 . 6 ) at 4°C overnight . After blocking with 5% skim milk in PBST at 37°C for 1 h , the following reagents were sequentially added and incubated at 37°C for 1 h as follows: ( 1 ) sera diluted at 1:100 in PBST , and ( 2 ) HRP-conjugated anti-human IgG ( Sigma , USA ) diluted at 1: 5 000 . After the final wash , the reactions were detected by the substrate ortho-phenylene diamine ( OPD , Sigma , USA ) plus H2O2 and stopped with 50 μl/well of 2 M H2SO4 . Optical density ( OD ) values at 490 nm were determined with a microplate reader ( TECAN , Austria ) . All samples were run in duplicate . Test sera/negative serum OD values <2 . 1 were regarded as negative and those ≥2 . 1 as positive . The cut-off values of rSeCP-ELISA and ES-ELISA were 0 . 34 and 0 . 42 , respectively . All statistical analyses were performed with SPSS for Windows , version 17 . 0 ( SPSS Inc . , Chicago , IL ) . The chi-square test and repeated measures of analysis of variance ( ANOVA ) were used to determine the difference among the groups at various periods . Intra- and intergroup statistical analyses were performed with one-way ANOVA ( LSD test ) . The statistical significance was defined as P < 0 . 05 .
The sequenced SeCP gene cloned in this study was 99 . 42% identical to the SeCP gene sequence in GenBank ( D63670 . 1 ) and had an active site containing the classic catalytic triad , Cys-His-Asn triad ( Cys145 , His283 , Asn303 ) . The coding sequence of the SeCP gene was cloned into the prokaryotic expression vector pMAL-c2X . After induction with 0 . 1 mM IPTG , TB1 bacteria harboring the recombinant plasmid pMAL-c2X-SeCP expressed a soluble fusion protein . On SDS-PAGE analysis , the molecular size of rSeCP was 79 kDa and consistent with the predicted combined size of the protein encoded by the cDNA clone ( 36 kDa ) and maltose-binding protein ( MBP ) tag from the vector ( 43 kDa ) ( Fig 1A ) . The concentration of rSeCP was 0 . 42 mg/ml . A Western blotting analysis showed that rSeCP was recognized by the serum of mice infected with plerocercoids and anti-rSeCP serum ( Fig 1C ) . Anti-rSeCP serum recognized the native proform SeCP protein with 36 kDa of crude and ES plerocercoid proteins . Additionally , another approximately 27 kDa band of crude and ES plerocercoid proteins , which might be the mature form of the 36 kDa SeCP , was also weakly recognized by anti-rSeCP serum . The results indicated that SeCP is one component from both the crude and ES proteins of plerocercoids . The mRNA transcription ( 1045 bp ) for the SeCP gene was observed at different plerocercoid stages from frogs or mice . Furthermore , the primers for a standard gene ( GAPDH ) generated the expected size band ( 670bp ) in all of the samples ( Fig 2 ) . Immunolocalization showed that specific fluorescent staining was observed in tegument and parenchymal tissue of plerocercoid collected from infected mice and frogs using anti-rSeCP serum , but no fluorescent staining was detected in the adult worm and egg sections ( Fig 3 ) . The protease activity of purified rSeCP was investigated using a gelatin SDS-PAGE assay . When the gels were incubated in an acidic buffer ( pH 5 . 5 ) , a zone of hydrolysis was visible , and the successful inhibition of enzymatic activity with E-64 , a specific cysteine protease inhibitor , demonstrated that purified rSeCP was the expected cysteine protease . To further confirm the proteolytic activity of rSeCP , the conventional enzyme assay was carried out with the use of fluorogenic peptide substrates . rSeCP showed a broad pH range , from 3 . 5 to 8 . 5 , and maximum activity was detected at pH 5 . 5 . The optimum temperature was 37°C ( Fig 4 ) . When added to the assay environment in the form of chlorides , rSeCP catalytic activity was inhibited by irons ( Cu++ , Mn++ and Zn++ ) ( Fig 5 ) . Under the same conditions , rSeCP enzymatic activity could be significantly inhibited only by E-64 , which is known to inhibit cysteine proteases at the concentrations commonly used in these assays ( Table 1 ) . The inhibition of rSeCP catalytic activity by irons and E-64 was dose-dependent . To investigate the putative biological roles of rSeCP , the proteolytic activity of rSeCP against several natural substrate proteins including Rabbit Ig , mouse Ig , bovine Hb , fibronectin and BSA was assayed . The results showed that the proteins were readily hydrolyzed by rSeCP at an acidic pH of 5 . 5 , but no degradation was observed at a neutral pH of 7 . 0 ( Fig 6A ) . BSA showed no hydrolysis at acidic and neutral pHs . Furthermore , when different concentrations of rSeCP were used to test its proteolytic activity , the result showed that the proteins were degraded more thoroughly with an increase in rSeCP ( Fig 6B ) . Evaluation of the inhibition of rSeCP catalytic activity by anti-rSeCP antibodies was determined using human Ig as the substrate for rSeCP activity . The results showed that the catalytic activity of rSeCP was inordinately inhibited by different dilutions of anti-rSeCP sera , while the catalytic activity was effectively inhibited by E-64 ( Fig 7 ) . The specific IgG antibodies to rSeCP in the serum of immunized mice were determined by ELISA using rSeCP as antigens , and the IgG antibody titer of anti-rSeCP serum was 1:106 , suggesting that rSeCP has good immunogenicity . Anti-rSeCP IgG levels in mice immunized with rSeCP were greatly increased following the first and second immunization ( Fig 8 ) . However , none of the mice vaccinated with adjuvant or PBS showed a significantly detectable specific anti-rSeCP antibody responses . The results of the IgG subclass antibody assay showed that after the second and third immunization , the levels of IgG1 were significantly higher than that of IgG2a ( t20d = 52 . 043 , t30d = 61 . 425 , P<0 . 01 ) . The ADCC results showed that anti-rSeCP serum promoted adherence of MPM to plerocercoids and the cytotoxicity increased with longer incubation times in the infection serum and anti-rSeCP serum groups ( F = 86 . 408 , P <0 . 05 ) ( Fig 9 ) . At 48 h after incubation , anti-rSeCP serum significantly induced plerocercoid death ( 70 . 00% cytotoxicity ) compared to plerocercoids incubated with normal mouse sera ( 25 . 33% , P <0 . 05 ) and PBS control ( 13 . 33% , P<0 . 05 ) , while there was no significant difference compared to mouse infection sera ( 76 . 67% , P>0 . 05 ) ( S1 Table ) . The sensitivity of both rSeCP-ELISA and ES-ELISA for detecting the serum samples of patients with sparganosis was 100% ( 20/20 ) ( Table 2 ) ; however , the specificity of rSeCP-ELISA for detecting sera of patients with cysticercosis , echinococcosis , schistosomiasis , paragonimiasis , clonorchiasis and trichinellosis , and healthy persons was significantly greater than the specificity of ES-ELISA at 98 . 22% ( 166/169 ) and 87 . 57% ( 148/169 ) ( χ2 = 22 . 604 , P<0 . 01 ) , respectively .
Cysteine protease is a candidate diagnostic antigen with good specificity for some helminth infections , including Angiostrongylus cantonensis [33] , Necator americanus [39] , Toxocara canis [15] , Paragonimus westermani [14] , Schistosoma japonicum [40] , Clonorchis sinensis [41] , Taenia solium [42] , and S . erinaceieuropaei [17] . The E . coli prokaryotic expression system has been considered as the most fully explored and commonly used system for gene engineering to produce recombinant proteins due to its security , simplicity , rapidity and high efficiency . In this study , SeCP encoding a 36 kDa protein from S . erinaceieuropaei plerocercoids was successfully cloned and expressed using the MBP fusion-based pMAL-c2X vector system , which contained a mutation in the translocation signal and thus would yield only cytoplasm-associated recombinant proteins [43] . The recombinant fusion protein was highly soluble in the bacteria’s cytoplasm and had good immunogenicity in mice; therefore , it could be used as an immunogen to produce antibodies after purification by affinity chromatography with amylose resin . Our results showed that the purified rSeCP induced a strong specific humoral immune response in immunized BALB/c mice , and the specific IgG antibody titer of anti-rSeCP serum was 1:106 as determined by rSeCP-ELISA . On Western blotting analysis , anti-rSeCP serum strongly recognized the native 36 kDa SeCP protein of plerocercoid crude or ES antigens . The results demonstrated that SeCP was a component of both the crude and ES antigens of S . erinaceieuropaei plerocercoids . Meanwhile , another band of approximately 27 kDa in plerocercoid crude and ES antigens was also weakly recognized by anti-rSeCP serum . The results suggested that the 36 kDa SeCP protein is an inactive proform while the 27 kDa protein is an enzymatically active mature form . Previous studies showed that an approximately 28 kDa SeCP from the plerocercoid crude and ES antigens , which was purified by ion-exchange chromatography and thiopropyl-Sepharose , had cysteine protease enzymatic activity and was consistent with the mature form of the 35 kDa protein [17] . The molecular weight of purified native SeCP was very similar to those of the proteins recognized by anti-rSeCP serum in crude and ES antigens in our study . The molecular weight difference might be the result of subjective analysis and judgment of these protein bands . Another study also demonstrated that the 27 kDa SeCP purified from crude plerocercoid antigens had cysteine protease activity [44] . The results of the RT-PCR analysis and IFT indicated that SeCP was expressed in the plerocercoid stage of different hosts ( frogs and mice ) but not in the adult worm and egg . A previous study showed that a 27 kDa cathepsin L-like cysteine protease was expressed in the coracidium and plerocercoid stages of S . erinaceieuropaei but not in immature eggs and adults [44] . These results suggest that the 27 kDa cysteine protease is only expressed in the invasive and migratory stages of the parasite . Our results also demonstrated that SeCP is the plerocercoid-specific protein . Expression of different types of cysteine proteases in different developmental stages has been observed in other parasites , including Schistosoma and Fasciola hepatica [32 , 45] , suggesting that these cysteine proteases may have stage-specific functions , such as degrading different tissue barriers or contrasting protein composition . For the intracellular localization of SeCP , the bioinformatics prediction results indicated that the SeCP was cathepsin L , which is a lysosomal cysteine protease that plays a major role in intracellular protein catabolism [24] , suggesting that SeCP might be located in the lysosomes or secretory granules of cells . The location of 36 and 29 kDa proteins in S . erinaceieuropaei plerocercoids were analyzed by immunohistochemical staining using serum from mice immunized with crude plerocercoid extract , and the two proteins were located in the syncytial tegument , tegumental cells , muscles and parenchymal cells , and lining cells of excretory canals; when the monoclonal antibody reacting to the 36 and 29 kDa protein was used , and the two proteins were located in the syncytial tegument and tegumental cells [46] . In Schistosoma mansoni , the cathepsin B and Ll-like cysteine proteases were located in the cortex and the cecum intestinal epithelial cells of adult worms [47] , while the cathepsin L2 in female and male adults existed in the reproductive system and the subcortical cortex cells of the gynecophoral canal [48] . The Fasciola hepatica cysteine protease was synthesized in the intestinal epithelial cells [49] . Previous studies demonstrated that many extracellular parasite proteases function to aid in the invasion of tissues and cells , hatch of eggs or evasion of host immune system . Cysteine protease is the major factor in parasitic pathogenicity because it induces tissue damage and facilitates invasion or enables the parasites to salvage metabolites from host proteins [50] . It has been shown that S . erinaceieuropaei plerocercoids secrete plentiful cysteine proteases [51] . The results of gelatin substrate gel digestion showed that rSeCP had CP enzymatic activity , possibly because the recombinant inactive proform enzyme was refolded and converted to an enzymatically active mature form after being fused with MBP in E . coli by altering the inhibitor domain and exposing the active site . It is also possible that because the inactive proform enzyme contained the mature domain and leader peptide , which is a type of effective enzyme inhibitor , the leader peptide and the mature domain were combined together tightly in the neutral environment but were separated rapidly in the acidic environment and the proform was converted into the enzymatically active mature form [52 , 53] . However , the activation mechanism of an inactive 36 kDa proform converted to the enzymatically active 27 kDa mature form is not well known . The optimum pH for rSeCP protease activity in acidic conditions suggested that the rSeCP was specially fit for enzymatic activity under acidic conditions . Additionally , our results also showed the rSeCP enzyme activity was inhibited by metal irons in a dose-dependent manner . The results were similar with those reported by Fricker et al . [54] . The physiological concentrations of metal ions are able to modulate the activity of Cathepsin L , even under conditions simulating an extracellular level . It seems that the role of metal ions is important for regulating SeCP enzyme activity . S . erinaceieuropaei cysteine protease can hydrolyze Hb , IgG and collagen , and may be associated with digestion of host tissue in invasion , migration and pathogenesis [17 , 55] . Considering the broad specificity of SeCP against various host proteins ( e . g . , Ig and Hb ) , the main biological role of SeCP may be related with digestion of host’s protein for parasite’s nutrition [17 , 47 , 55]; this is consistent with the role of cysteine proteases during blood meal feeding . In this study , our results indicated that the rSeCP could hydrolyze Hb , IgG and fibronectin . Combined with the SeCP expressed only in penetrating and migratory stages in the host tissues [44] , SeCP might have a potential role in tissue invasion and/or migration . It has been shown that cleaving host IgG is a mechanism of escaping host immune responses utilized by helminthes [55 , 56] . The cleaving of IgG and fibronectin by rSeCP suggests a possible role for the SeCP in helping plerocercoids evade immune activity by modulating host immune response . The neutralization of SeCP enzymatic activity might have harmful effects on the parasite . To determine whether neutralizing rSeCP activity will interfere with the function and protection of SeCP , the neutralization test and in vitro ADCC assay were performed in this study . Our results showed that the enzymatic activity of rSeCP can be neutralized by anti-rSeCP antibodies , suggesting that anti-rSeCP antibodies participated in the killing of infective plerocercoids . Although the immunization of mice with rSeCP induced a Th2-predominant immune responses ( high levels of IgG1 ) and anti-rSeCP antibodies have the potential capability to kill plerocercoids in ADCC reactions , the plerocercoids can survive for a long time in infected mice . However , the SeCP excreted or secreted by plerocercoids during natural infection produced only partial protective immunity . Like most parasites ( e . g . , Taenia solium , Wuchereria bancrofti and Trichinella spiralis ) , during the long parasitism and evolution , the plerocercoids might have developed multiple strategies of immune escape to survive in hosts , such as cleaving host IgG , shedding the surface tegument , and producing neutralizing or blocking antibodies [37 , 56 , 57] . To evaluate the sensitivity and specificity of rSeCP for detecting anti-plerocercoid antibodies , rSeCP-ELISA was used for detection of serum samples from patients with sparganosis , and the results were compared with ES-ELISA . The results showed that the sensitivity of rSeCP-ELISA and ES-ELISA for detecting anti-plerocercoid antibodies was 100% ( 20/20 ) , but the specificity of rSeCP-ELISA was significantly greater than that of ES-ELISA ( P <0 . 01 ) . The results demonstrated that rSeCP might be a potential antigen for serodiagnosis of sparganosis . In conclusion , the present study demonstrated that SeCP is a plerocercoid stage-specific protein and located in the teguments and parenchymal tissues of plerocercoids . rSeCP has cysteine protease enzymatic activity , and functions to degrading various host proteins . Immunization with rSeCP induced a Th2-predominant immune responses and anti-rSeCP antibodies had the potential to kill plerocercoids in an ADCC assay . rSeCP had a high sensitivity and specificity for detecting anti-plerocercoid antibodies , and might be a potential antigen for serodiagnosis of sparganosis . | Sparganosis is a neglected tropical disease; its diagnosis is difficult and it is often misdiagnosed . ELISA using the crude or ES antigens of plerocercoids cross reacts with other helminthiases . Cysteine protease is a type of hydrolase and plays important roles in the development and survival of parasites; it has been used for diagnostic markers and vaccine targets for some parasitic diseases . In this study , a 36 kDa Spirometra erinaceieuropaei cysteine protease ( SeCP ) was expressed and purified . The results showed that SeCP was a plerocercoid stage-specific protein located in the teguments and parenchymal tissue . The rSeCP had cysteine protease activity and functioned to degrade host proteins . Vaccination of mice with rSeCP induced high levels of IgG1 and anti-rSeCP antibodies with the ability to kill plerocercoids in an ADCC assay . The rSeCP had a high sensitivity and specificity for detecting anti-plerocercoid antibodies , and could be used as a potential antigen for serodiagnosis of sparganosis . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Characterization of Spirometra erinaceieuropaei Plerocercoid Cysteine Protease and Potential Application for Serodiagnosis of Sparganosis |
A longstanding puzzle in human genetics is what limits the clinical manifestation of hundreds of hereditary diseases to certain tissues , while their causal genes are expressed throughout the human body . A general conception is that tissue-selective disease phenotypes emerge when masking factors operate in unaffected tissues , but are specifically absent or insufficient in disease-manifesting tissues . Although this conception has critical impact on the understanding of disease manifestation , it was never challenged in a systematic manner across a variety of hereditary diseases and affected tissues . Here , we address this gap in our understanding via rigorous analysis of the susceptibility of over 30 tissues to 112 tissue-selective hereditary diseases . We focused on the roles of paralogs of causal genes , which are presumably capable of compensating for their aberration . We show for the first time at large-scale via quantitative analysis of omics datasets that , preferentially in the disease-manifesting tissues , paralogs are under-expressed relative to causal genes in more than half of the diseases . This was observed for several susceptible tissues and for causal genes with varying number of paralogs , suggesting that imbalanced expression of paralogs increases tissue susceptibility . While for many diseases this imbalance stemmed from up-regulation of the causal gene in the disease-manifesting tissue relative to other tissues , it was often combined with down-regulation of its paralog . Notably in roughly 20% of the cases , this imbalance stemmed only from significant down-regulation of the paralog . Thus , dosage relationships between paralogs appear as important , yet currently under-appreciated , modifiers of disease manifestation .
Hereditary diseases are caused by germline aberrations that are common to cells throughout the human body . For hundreds of these diseases , these germline aberrations have been identified and mapped to causal genes [1] , and many more causal genes are likely to be identified in coming years owing to the extensive usage of sequencing techniques in medical settings [2] . However , the identification of a causal gene is often just the starting point for understanding the molecular basis of each disease . The genotype-to-phenotype relationship between a causal gene and the respective disease phenotype is typically complex [3 , 4] , and , for numerous hereditary diseases remains to be elucidated . By shedding light on these relationships , we hope to obtain better understanding of disease mechanisms and advance the search for cures . Tissue-selectivity is a hallmark of many hereditary diseases [5] . For example , familial mutations in BRCA1 gene increase the risk for breast and ovarian cancers , and familial mutations in RB1 gene lead primarily to retinoblastoma . From an evolutionary point of view , tissue-selectivity is not surprising given that limited manifestation is probably less detrimental than whole body diseases , and thus more likely heritable . Yet , tissue-selectivity is intriguing due to the pattern of expression of causal genes . For example , both BRCA1 and RB1 are expressed ubiquitously across most human tissues without eliciting disease phenotypes in those tissues . In fact , most causal genes exhibit tissue-specific disease manifestation along with tissue-wide expression [5 , 6] . Several molecular mechanisms may lead to this phenomenon . In some cases , the disease-manifesting tissue ( denoted disease tissue henceforth ) has unique features [7 , 8] , such as long-lived neurons and age-related protein misfolding diseases [9] . In other cases , the tissue-selective effect may depend on the specific isoform expressed in that tissue [10] . Meta-analysis studies showed that causal genes tend to have elevated expression preferentially in their disease tissues [5 , 6] , hinting to a quantitative basis for tissue selectivity . Previously , we showed that causal genes tend to form tissue-specific interactions preferentially in their respective disease tissues , suggesting that these interactions contribute to tissue selectivity [5] . Yet for many hereditary diseases , the molecular mechanisms that underlie them remain hidden . Here , we consider the role that paralogs of causal genes may play in determining the tissue-selectivity of hereditary diseases . Paralogs , namely homologous genes within the same species resulting from gene duplication events , have been repeatedly shown to have redundant functions and to compensate for the loss of each other ( reviewed in [11] ) . At a systems level , paralogs were shown to be less essential than genes lacking paralogs ( singletons ) in yeast [12] , worms [13] , mice [14] and plant [15] . A recent measurement of the essentiality of over 17 , 000 human genes showed that the same tendency holds for human paralogs [16] . The impact of paralogs was also demonstrated in the context of disease . For example , a mouse model of retinoblastoma that carries a homozygous deletion in the Rb gene , the homolog of human RB1 gene , does not develop retinoblastoma [17] , unless one of the paralogs of Rb , p107 [18] or p130 [19] , is removed . Interestingly , in several cases the compensatory impact of paralogs was found to be dosage-dependent . For example , mouse embryos that are homozygous for Mek1 gene deletion and which typically die due to placental defects , survive if two copies of Mek2 gene are inserted , while one copy of Mek2 is not sufficient [20] . Similarly , the Eif2s3y gene on the mouse Y chromosome was shown to be replaceable by its X-linked homolog Eif2s3x gene for spermatogenesis initiation , but more copies of Eif2s3x were required for progression through meiosis [21] . In human , the essentiality of each of the two paralogous helicases , the genes DDX3Y and DDX3X , was inversely correlated with the expression level of the other paralog , stressing that their functional redundancy is dosage-dependent [16] . We hypothesized that tissue-selectivity of some hereditary diseases may be related to quantitative relationships between causal genes and their paralogs . Accordingly , owing to the functional redundancy between paralogs , a paralog of an aberrant causal gene can generally compensate for its malfunction ( Fig 1A ) . However , when the quantitative relationships between them change , compensation may become insufficient and disease phenotypes will emerge . This might occur when the causal gene is up-regulated in the disease tissue without a similar change in the level of the paralog ( Fig 1B ) . Alternatively , the causal gene may be expressed at an intermediate level in the disease tissue , but the paralog is down-regulated at the disease tissue ( Fig 1C ) . While dosage-dependent compensation relationships between paralogs were demonstrated previously ( e . g . , [16 , 20 , 21] ) , this phenomenon was never analyzed systematically at large-scale in the context of tissue-selective diseases . In this study , we analyze quantitatively the relationships between 80 causal genes and their paralogs across 112 hereditary diseases . We focused on hereditary diseases that manifest selectively in distinct tissues , including the brain , skeletal muscle , heart , skin , liver , thyroid or testis . We took advantage of various omics data including 420 RNA-sequencing profiles of 45 human tissues made available by the Genotype-Tissue Expression ( GTEx ) consortium [22] , to assess quantitatively the relationships between causal genes and their paralogs across tissues . The majority of the causal genes were functionally-overlapping with their paralogs , and causal genes were less essential than singleton genes . Next , we computed the expression ratios between causal genes and their paralogs in different tissues . The ratios were typically similar across tissues , except for the disease tissues where the ratios were significantly high . These high ratios were observed for causal genes with different numbers of paralogs and in various disease tissues . To distinguish between the possible scenarios leading to imbalanced expression ( Fig 1B and 1C ) , we carried differential expression analysis across the different tissues . In 26% of the cases , the causal gene was significantly up-regulated in the disease tissue . In 19% of the cases a paralog was significantly down-regulated in the disease tissue , and in additional 24% of the cases both occurred . These results suggest that paralogous compensation can shed light on the tissue-selective manifestations of hereditary diseases .
We started by creating a high-confidence dataset of tissue-selective hereditary diseases . For this , we manually curated hereditary diseases that manifested clinically in one of the following tissues: brain , skeletal muscle , heart , skin , liver , thyroid or testis . We included diseases with various modes of inheritance , since in both dominant and recessive disorders paralogous compensation may contribute to the robustness of unaffected tissues . For each disease , we extracted its known causal genes from the OMIM database [1] , and identified paralogs of the causal gene based on phylogeny and sequence identity ( see Methods ) . The causal genes contained various types of aberrations , several of which can lead to partial or complete loss of the gene product and its function , due to , e . g . , protein truncation or in-frame missense mutations [23 , 24] . Other aberrations could lead to gain-of-function for which paralogous compensation may not be relevant , but these were shown in a systematic screen to occur at low frequency [23] . Next , we examined the pattern of expression of causal genes across tissues , to avoid causal genes that are tissue-specific and thus inevitably elicit tissue-specific phenotypes . For this , we used RNA-sequencing profiles of human tissues made public by the GTEx consortium [22] ( see Methods ) . We computed the number of tissues expressing each causal gene above a certain threshold ( see Methods ) , and limited our analysis to causal gene and their paralogs that were co-expressed in at least five tissues . Henceforth , we analyzed 112 hereditary diseases caused by germline mutations in 80 causal genes ( Fig 2A and S1 Table ) . Some of the genes were causal for distinct diseases ( due to distinct mutations ) that manifested in different tissues , resulting in 93 pairs of causal genes and disease tissues ( S2 Table ) . The majority of the causal genes were expressed ubiquitously across tissues ( 83% , Fig 2B and S1 Fig ) . Thus , in agreement with previous studies [5 , 6] , tissue-selectivity of their respective diseases could not stem simply from tissue-selective expression of the casual genes . Most causal genes were associated with one or two paralogs ( 76% , Fig 2C ) , and many paralogs were also globally expressed ( 66% , Fig 2B ) . Monogenic disease genes and their paralogs were shown previously to be frequently functionally overlapping , based on their co-expression relationships [25] and overlap in interaction partners [26] . We used similar measures to test for functional overlap between causal genes and their paralogs in our dataset . For each causal gene and its paralog , denoted causal gene–paralog ( CGP ) pair , we computed the expression correlation between them across all tissues , and the overlap in their protein interaction partners ( see Methods ) . The majority of the CGP pairs were significantly functionally overlapping by at least one measure , and , as expected , functional overlap was more frequent among pairs with higher sequence identity ( Fig 2D ) . The functional overlap between causal genes and their paralogs suggests that causal genes in our dataset would have a lower tendency to be essential , relative to singleton genes . This was recently shown for human genes with paralogs in general [16] . We repeated the same test for the causal genes in our dataset ( Fig 2E ) . Indeed , causal genes were significantly less essential than singleton genes ( Kolmogorov-Smirnov test , p = 0 . 02 ) , in agreement with the presence of a functionally redundant paralog . According to the imbalance hypothesis , the relative levels of a causal gene and its paralog are comparable across tissues , except for the disease tissue , where we expect to find a shift in balance ( Fig 1 ) . To test this hypothesis , we computed the ratio between the expression levels of causal genes and their paralogs across the different tissues ( see Methods ) . We then compared the ratios obtained in disease tissues to the ratios obtained in other tissues ( Fig 3A , left ) . The ratios in the disease tissue were significantly higher than the median ratios in unaffected tissues , in accordance with the imbalance hypothesis ( Mann-Whitney , p<10−15 ) . A similar shift in balance was evident upon considering only causal genes with a single paralog ( Fig 3A , middle , p = 0 . 0058 ) . In case a causal gene has multiple paralogs , paralogs might have distinct compensatory behaviors or a cumulative effect . Thus , for causal genes with multiple paralogs , we additionally tested whether imbalance was still observable upon combining all the paralogs of each causal gene ( see Methods ) . Indeed , these ratios too were significantly higher in the disease tissue relative to unaffected tissues ( Fig 3A , right , p = 0 . 0012 ) . We further tested the generality of the imbalance by dividing causal genes according to their disease tissues and repeating this test . Notably , the ratios obtained for pairs in their respective disease tissue were higher than the ratios obtained for the same pairs in the six unaffected tissues , for all disease tissues except testis and thyroid , which included a single causal gene ( Fig 3B–3E and S2 Fig ) . We extended this test to include all tissues . Upon comparing the ratios for CGP pairs in their disease tissue to their ratios in all other tissues , we find that with the exception of testis and thyroid , the highest ratios were obtained consistently in the disease tissue and its closely related tissues , such as different regions of the heart , skin that is sun-exposed and unexposed , and closely related brain regions ( Fig 3F and S3 Fig ) . Thus , imbalanced expression of causal genes and their paralogs is prevailing among hereditary diseases . Our next goal was to analyze quantitatively the causes for the shift in balance observed for causal genes and their paralogs in their respective disease tissues . In general , their balance could be shifted due to up-regulation of the causal gene or down-regulation of its paralog in the disease tissue relative to other tissues , or both , as shown schematically in Fig 4A . The CGP pair CAV1 , CAV3 presented in Fig 1B demonstrates the first scenario , while the CGP pair VRK1 , VRK2 presented in Fig 1C demonstrates the second scenario . To distinguish between these scenarios and to quantify their frequency in our dataset , we used differential expression analysis . We focused on the 36 tissues for which five or more samples were available . For each disease tissue , we calculated the differential expression of genes in this tissue relative to all other tissues . This allowed us to identify rigorously genes that were up-regulated or down-regulated significantly in the respective disease tissue ( 2-fold change and p<0 . 01 , see Methods ) . We then analyzed the frequency of the different scenarios among our CGP pairs ( Fig 4B ) . The most common scenario was the up-regulation of the causal gene , which we observed in 52% of the CGP pairs . In additional 15% of the pairs , this was combined with down-regulation of the paralog . Notably , in another 9% of the pairs the paralog alone was significantly down-regulated . To test the generality of these trends , we repeated this analysis for several partitions of the causal genes . We observed the same trends upon analyzing separately genes that share the same disease tissue ( e . g . , Fig 4C and S4 Fig ) . The different scenarios were evident also when analyzing causal genes with a single paralog ( Fig 4D , left ) . Specifically , 36% of the causal genes were up-regulated , including 7% where the paralog was down-regulated . In additional 20% of the genes , only the paralog was down-regulated ( Fig 4E ) . We further tested whether these scenarios occurred preferentially in the disease tissue by carrying randomization tests ( see Methods ) . We found that each scenario was significantly more frequent in the disease tissue than in unaffected tissues . This included up-regulation of the casual gene ( p<10−3 ) , down-regulation of the paralog ( p<10−3 ) , or both ( p<0 . 05 ) . We repeated this analysis for genes with multiple paralogs by combining CGP pairs of the same causal gene ( see Methods , Fig 4D , right ) . The frequency of each scenario in the combined dataset including all genes was significantly larger than expected by chance ( Fig 4F ) . This suggests that imbalance in general , and specifically imbalance due to paralog down-regulation , occurs preferentially in the disease tissue . An example for down-regulation of a paralog is presented by the charged multivesicular body protein 1a ( CHMP1A ) gene . CHMP1A is causal for pontocerebellar hypoplasia type 8 , an autosomal recessive neurodevelopmental disorder [27] . Two germline mutations in CHMP1A were identified independently in patients , both leading to lack of CHMP1A expression in patient-derived cells [28] . Our data shows ubiquitous expression of CHMP1A across tissues , with intermediary expression in the cerebellum ( Fig 5A , left ) . CHMP1A has a paralog , CHMP1B , with considerable sequence identity ( 55 . 6% ) and significantly overlapping protein interaction partners . CHMP1B was significantly under-expressed in the cerebellum ( Fig 5A middle ) , leading to imbalance and potentially insufficient compensation specifically in the disease tissue ( Fig 5A , right ) . Additional examples appear in Fig 5B–5E .
Paralogous compensation is a key mechanism for maintaining genetic robustness [12–15 , 25] . Paralogs result from gene duplication events , and may be retained in the genome following sub- or neo-functionalization [29] or the sharing of gene dosage [30] . Their ability to compensate for each other relies on their functional similarity , and in some cases involves changes in the abundance of the functional paralog , its cellular localization or protein interactions ( reviewed in [11] ) . Paralogous compensation is more frequent among young paralogs that have not diverged much [15 , 25] , but was also observed among ancient paralogs [31] . Here we harnessed the concept of paralogous compensation to illuminate a fundamental question: What makes certain cell types or tissues succumb to a germline aberration while others remain robust . We hypothesized that paralogous compensation acts in various tissues throughout the body , however is limited and thus insufficient in the disease tissue , which therefore becomes vulnerable to germline mutations ( Fig 1 ) . We tested our hypothesis on genes causal for 112 hereditary diseases that manifest predominantly in a single tissue ( Fig 2 ) . The causal variants of the genes we analyzed contained various types of aberrations , several of which can lead to partial or complete loss of the gene product or its function , due to , e . g . , protein truncation or in-frame missense mutations [23 , 24] . Other aberrations can lead to gain-of-function for which paralogous compensation may not be relevant , but these were shown in a systematic screen to occur at low frequency [23] . The causal genes and their paralogs in our dataset appeared to be functionally related by various measures , and , in accordance , were less essential than singleton genes ( Fig 2D and 2E ) . Dosage sharing between paralogs was suggested to be one of the first steps following gene duplication [30] . Previous studies in yeast , fly and Arabidopsis observed that duplicate genes have higher expression divergence compared to singleton genes [32–34] . In human , variation in gene expression was shown to be far greater among tissues than among individuals [35] , and was high among disease-related genes [36] , as we also observed for the paralogs that we studied . Here , we analyzed systematically for the first-time dosage relationships between genes that are causal for tissue-selective hereditary diseases and their paralogs . For this , we exploited transcriptional profiles of 36 human tissues sampled from deceased donors with no genetic diseases [22] . Together , these profiles provided an atlas of gene expression in normal tissues and a baseline indicating the relevance of a gene within a specific tissue . While expression levels of wildtype alleles in patients carrying causal aberrations might differ from the levels observed in the general population , such changes were assessed previously and shown to be very limited [37–39] . Using these data , we found that the ratio between the expression levels of causal genes and their paralogs tend to be significantly high particularly in their disease tissues ( Fig 3 ) . This agrees with our hypothesis that , upon causal aberration , paralogous compensation will be limited specifically in the disease tissue , thereby making this tissue more vulnerable than other tissues expressing the same causal gene . The relatively high expression ratios could stem from up-regulation of the causal gene in the vulnerable tissue , or from down-regulation of its paralog ( Fig 1 ) . To differentiate between these scenarios , we carried a rigorous differential expression analysis , which was enabled by the large numbers of samples available per tissue . The largest fraction of the cases included causal genes that were up-regulated significantly in their disease tissues , as previously observed [5 , 6] . However , in many other cases the causal gene was not upregulated and there was no tissue-specific isoform , yet a paralog was down-regulated significantly ( Fig 4E and Fig 5 ) . Notably , the frequency of each of these scenarios was higher than expected by chance ( p<0 . 05 , randomization test ) . A specifically interesting example involved two paralogous causal genes that were down-regulated at each other’s disease tissue ( Fig 5E ) . LDLR and VLDLR belong to the low-density lipoprotein receptor gene family and are functionally overlapping ( >47% sequence identity and significantly overlapping interactions ) . LDLR is causal for familial hypercholesterolemia that manifests in the liver , and VLDLR is causal for cerebellar hypoplasia and mental retardation . Each of them was expressed at intermediate levels at its respective disease tissue , and down-regulated at the disease tissue of its paralog , suggesting that by this they elicit tissue-specific phenotypes . There remains a subset of causal genes for which imbalanced expression or significant expression changes were not observed . This includes cases where paralogous compensation may be irrelevant , due to limited functional overlap between paralogs or their tissue-specific isoforms , or a gain-of-function aberration . Interestingly a recent study showed that some paralogs in yeast are dependent on each other , and thus when mutated impart fragility rather than robustness [39] . We identified one such disease-related pair in human . BRAF and RAF1 are two functionally-related paralogous genes of the RAF family of serine/threonine protein kinases , known to be causal for various types of Noonan and Leopard syndromes . Interestingly , they were shown to form a heterodimer , thus explaining their dependency and common phenotypes [40] . Additional cases of paralogous compensation may remain hidden due to under-sampling of relevant cell types , or to lack of post-transcriptional profiling [38] . These might come to light upon analyzing data from specific cell types , or by rigorous proteomic analyses at large scales . In the future , it will be intriguing to extend the concept of compensation to higher-order entities such as pathways ( e . g . , [15 , 41] ) . Our results show that systematic analysis of large-scale datasets illuminates dosage relationships and paralogous compensation events . They suggest that compensatory factors underlie tissue-selective genotype-phenotype relationships and particularly disease susceptibility , and point to paralogs as new and effective modifiers of tissue robustness .
The disease set included hereditary diseases with known protein-coding causal genes according to OMIM [42] that were predicted to manifest in either the brain , heart , liver , skeletal muscle , skin , testis or thyroid [6] . We used literature and expert curation to validate their clinical association and to filter out diseases with multiple affected tissues . Causal genes were downloaded from OMIM [42] . Paralogs were extracted from Ensembl-Biomart [6 , 43 , 44] and limited to paralogs with reciprocal sequence identity of 40% or more . RNA sequencing profiles were obtained from the GTEx portal on 2/22/17 ( version 6p ) [44] . In the expression quantification of genes by GTEx , only uniquely mapped reads were considered [45] . Only samples from individuals with traumatic injury as cause of death were included as proxy for healthy tissues ( S3 Table ) . We verified the absence of possible confounders , including gender and age group , by applying mixed linear models to each tissue separately . To evaluate the expression distribution of a gene across tissues , we considered a gene as expressed in a certain tissue if its level exceeded 0 . 3 RPKM in at least half of the samples of that tissue . For each gene , the number of tissues expressing that gene was recoded . We included in the analyses only CGP pairs that were co-expressed in at least 5 tissues . Ratios between RPKM gene expression levels were calculated per sample . A distinct ratio was computed for a causal gene and each of its paralogs . In the combined analysis , a ratio was computed between the expression level of a causal gene and the sum of the expression levels of its paralogs . The ratio in a specific tissue was set to the median ratio across all samples of that tissue . To assess the general difference in expression patterns between paralogs that were not filtered for causal genes , we analyzed paralogs with at least 40% identity that were expressed in at least 5 common tissues ( similarly to causal genes and their paralogs ) . For each pair , we calculated the expression ratio in each sample , across all samples of the same tissue . We correlated between the expression levels of a causal gene and each of its paralogs across tissues by using Pearson correlation . For each gene , its expression level per tissue was set to the median RPKM level over samples of that tissue . We downloaded data of experimentally-detected protein-protein interactions from BioGRID [46] , DIP [47] and IntAct [48] by using myProteinNet [49] and computed the number of proteins that interact with a causal gene , with its paralog , and with both . The CRISPR scores of genes , which represent their essentiality , were extracted from [16] . Differential expression analysis was applied to 36 GTEx tissues with at least five samples . Raw counts were extracted from GTEx portal and normalized using the TMM method by the edgeR package ( 27 ) , to obtain the same library size for every sample . Genes with less than 10 counts in all samples were removed before normalization . In each sample , we transformed RNA-sequencing normalized counts using VOOM [50] , and calculated differential expression using a linear model in the R-package Limma [51] . Specifically , all samples of the same tissue were compared to a background set containing all other samples ( not limited to tissues with 5 samples or more ) . Only genes with an absolute 2-fold change or more and FDR adjusted P-values <0 . 01 were considered differentially expressed . We used mixed linear models to predict the expression of a causal gene in each tissue by the expression levels of its paralogs , by the number of its paralogs , by whether its expression was measured in the disease tissue and by the amount of tissues which manifest a disease associated with this gene . We accounted for the clustered structure of the donors by including a random intercept in all of the models . Mixed linear models were computed by using IBM SPSS Statistics , Version 23 . 0 . We compared between the expression distributions of causal genes and their paralogs across tissues by using the Kolmogorov-Smirnov test . The significance of protein interactions overlap between a causal gene and its paralog was computed by using Fisher exact test . We compared between essentiality scores of causal genes and protein-coding genes without paralogs by using the Kolmogorov-Smirnov test . This test was also used to compare between the distribution of ratios obtained in disease tissues versus unaffected tissues . We used a randomization test to assess whether causal genes ( and their paralogs ) are over-expressed ( or under-expressed ) preferentially in the disease tissue relative to other tissues . Specifically , in each randomized run each causal gene was assigned a randomly selected disease tissue out of the set of GTEx tissues expressing the causal gene and its paralog . For causal genes with multiple paralogs , the disease tissue was selected randomly from the set of GTEx tissues expressing the causal gene and at least one of its paralogs . We then counted the number of causal genes that were significantly over-expressed , had an under-expressed paralog , or both , in the randomly selected disease tissues . We repeated this analysis 1 , 000 times . Statistical significance was set to the fraction of randomized runs in which the number of causal genes in a given subset was at least as high as the fraction observed for these pairs in the original dataset . | A longstanding enigma in human genetics is what limits the clinical manifestation of hundreds of hereditary diseases to certain tissues or cell types , while their causal genes are present and expressed throughout the human body . A general conception was that the tissue-wide robustness to the causal aberration is achieved owing to the presence of a compensatory factor , and that disease phenotypes emerge wherever this factor is limited . Here , we tested this general conception at large-scale for the first time . We focused on paralogs of disease-causing genes , which share their functionality and may compensate for their aberration . Based on quantitative analyses of several types of omics data , we show that paralogs of causal genes are down-regulated relative to the disease-causing gene preferentially in the respective disease-manifesting tissue . This tendency is common across various subsets of causal genes , diseases , and tissues . Thus , paralogs of causal genes appear to contribute to the tissue-wide robustness against causal aberrations , and serve as important , yet currently under-appreciated , modifiers of disease manifestation . | [
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] | 2018 | Role of duplicate genes in determining the tissue-selectivity of hereditary diseases |
The Clostridium difficile exotoxin , TcdB , which is a major virulence factor , varies between strains of this pathogen . Herein , we show that TcdB from the epidemic BI/NAP1/027 strain of C . difficile is more lethal , causes more extensive brain hemorrhage , and is antigenically variable from TcdB produced by previously studied strains of this pathogen ( TcdB003 ) . In mouse intoxication assays , TcdB from a ribotype 027 strain ( TcdB027 ) was at least four fold more lethal than TcdB003 . TcdB027 caused a previously undescribed brain hemorrhage in mice and this correlated with a heightened sensitivity of brain microvascular endothelial cells to the toxin . TcdB003 and TcdB027 also differed in their antigenic profiles and did not share cross-neutralizing epitopes in a major immunogenic region of the protein . Solid phase humoral mapping of epitopes in the carboxy-terminal domains ( CTD ) of TcdB027 and TcdB003 identified 11 reactive epitopes that varied between the two forms of TcdB , and 13 epitopes that were shared or overlapping . Despite the epitope differences and absence of neutralizing epitopes in the CTD of TcdB027 , a toxoid form of this toxin primed a strong protective response . These findings indicate TcdB027 is a more potent toxin than TcdB003 as measured by lethality assays and pathology , moreover the sequence differences between the two forms of TcdB alter antigenic epitopes and reduce cross-neutralization by antibodies targeting the CTD .
Clostridium difficile is the leading cause of hospital-acquired diarrhea in developed countries [1] , [2] , [3] , [4] . This spore-forming anaerobic bacterium contaminates hospital environments and infects patients undergoing antibiotic therapy within health care facilities [2] , [5] , [6] . Despite these problems , historically , treatment with antibiotics such as metronidazole and vancomycin has been an effective means of treating this disease [7] , [8] . Yet , disturbing trends of increased morbidity and mortality , as well relapse of C . difficile infected patients have become apparent over the past decade [9] , [10] , [11] , [12] , [13] , [14] , [15] . These trends correlate with the emergence of the BI/NAP1/027 strain of C . difficile [10] , [12] , [16] , [17] . Although an absolute association between BI/NAP1/027 strains and increased disease severity has not been made in all cases [18] , [19] , [20] , [21] , extensive clinical surveillance over the past ten years has shown a strong correlation between BI/NAP1/027 frequency and mortality rate [22] , [23] . This C . difficile strain has now been found in a majority of states in the US and is prominent both in Europe and Canada [16] , [24] . To date , many factors such as antibiotic resistance , sporulation ability , and toxin production have been proposed to contribute to the potential difference in virulence of historical ribotypes and C . difficile 027 [13] , [25] , [26] , [27] , [28] , [29] . Yet , the relevance of these factors is still greatly debated [30] , [31] , leaving us with a poor understanding into how this emergent strain correlates with increased mortality . C . difficile produces two large clostridial toxins , TcdA and TcdB , which cause extensive tissue damage and are major virulence factors in human disease [32] , [33] , [34] . Our work has focused on understanding how variations in the toxins produced by historical and epidemic strains change the extent of C . difficile virulence [35] , [36] . Of particular interest are the differences in the sequence and activities of TcdB , which has been implicated as a critical C . difficile virulence factor [37] , [38] . We hypothesize that variation between TcdB from previously predominant ribotypes and BI/NAP1/027 strains , is a major contributing factor to the increased virulence of the recently emerged forms of C . difficile . TcdB ( ∼270 kDa; 2366 amino acids; YP_001087135 . 1 ) is a single chain polypeptide toxin where the glucosyltransferase domain is located at the N-terminus ( GTD: 1–543 ) , followed by an autoprocessing site between amino acid 543 and 544 which is subject to intramolecular cleavage by the cysteine protease domain ( CPD: 544–807 ) , a hydrophobic transmembrane domain ( TMD: 956–1128 ) , and a putative receptor binding domain at the C-terminus ( CTD: 1651–2366 ) [39] , [40] , [41] , [42] , [43] , [44] , [45] . The gene encoding TcdB is located within a pathogenicity locus on the chromosome of C . difficile along with genes encoding TcdA ( enterotoxin; YP_001087137 . 1 ) , TcdE ( YP_00108136 . 1 ) , and regulators of toxin gene expression ( TcdC , YP_001087138 . 1 and TcdR , YP_00108134 . 1 ) [46] . While the sequence of TcdA , TcdE , TcdR , and TcdC are almost identical between ribotype 012/003 and BI/NAP1/027 strains , TcdB is more variable ( 96% similarity , 92% identity ) [35] . These differences in the sequence of TcdB may explain the observations of Wren and colleagues , who found that TcdB from a BI/NAP1/027 strain ( TcdB027 ) is more potent on cultured cells than TcdB from a historical ribotype 012 strain [47] . In line with this we also found that TcdB027 causes more extensive and broader tissue pathologies than TcdB from the commonly referenced strain , VPI 10463 ( TcdB003 ) , in a zebrafish embryo model [35] . As a possible underlying mechanism for these differences in activity , we found previously that TcdB027 is translocated into cells more rapidly and is autoprocessed more efficiently than TcdB003 [35] . The greatest sequence variation between the two forms of TcdB is found in the C-terminal domain ( CTD ) , which we define as the region of the toxin between amino acid 1651 and the terminal residue at position 2366 . There is an overall 88% sequence identity between TcdB0271651-2366 and TcdB0031651-2366 . The CTD of TcdB encodes combined repetitive oligopeptides ( CROPs ) , which are thought to be responsible for the recognition of glycans on target cells [39] , [48] , and as such the CTD is often referred to as the receptor binding domain . However , the role of the CTD as the receptor binding domain is still very much debated as no receptor has been identified , and studies in TcdA have shown that this region contributes to , but is not required for cellular uptake of the toxin [49] . The CTD is also antigenic and known to contain neutralizing epitopes [50] , [51] . Yet , whether sequence differences in the CTD of TcdB027 and TcdB003 alter the tropism or antigenic profiles of these two forms of the toxin is not known . In the current study , we examined differences in the lethality and in vivo pathologies of TcdB027 and TcdB003 . The data indicate TcdB027 exhibits a lethal dose substantially lower than TcdB003 . We also show that while both toxins caused pronounced hemorrhaging in major organs , TcdB027 caused brain pathologies in vivo , as well as an increased cytotoxicity on brain microvascular cells in vitro . This study also characterized the influence of the CTD on this cell tropism and the possible contribution of sequence variation to changes in antigenicity . The data suggest that the CTD may not occupy the same role in TcdB027 as TcdB003 , and identifying these key differences is a critical step toward understanding the virulence and systemic effects of C . difficile associated disease .
In previous work we found that that TcdB027 is more cytototoxic and causes broader tissue damage in a zebrafish embryo model than TcdB003 [35] . To determine how this difference in activity might impact systemic damage and lethality between the two forms of the toxin , in the first set of experiments in this study we determined and compared the lethal doses of TcdB003 and TcdB027 in a murine systemic intoxication model . The previously published lethal dose of 220 µg/kg ( i . p . ) for TcdB003 [32] was used to establish a range of toxin concentrations for these treatments , but the lethality we observed via i . v . injection was much higher than previously reported . As a result , the initial doses of 100 µg/kg ( data not shown ) , 50 µg/kg , and 25 µg/kg of TcdB003 were much more potent than anticipated , and resulted in a very rapid time to death ( Fig . 1A ) . Therefore , the remaining mice were subjected to much lower doses of 5 µg/kg and 2 . 5 µg/kg of TcdB003 . Based on the results of the TcdB003 treated mice , the TcdB027 group started with a dose of 10 µg/kg and was continued with 1∶2 dilutions down to 625 ng/kg of TcdB027 . After the mice were injected with TcdB003 or TcdB027 , they were followed for up to 7 days and the survival curves of the data from these experiments are shown in Fig . 1B . The data shown in Fig . 1 indicate mice injected with TcdB027 succumb to the toxin at a lower dose than that observed in mice injected with TcdB003 . Within 26 h of treatment all of the mice administered 5 µg/kg of TcdB027 died or reached a moribund condition . In comparison , mice administered the same dose of TcdB003 did not succumb to the toxin until after 40 h and as long as 57 h with a median survival of 48 hr ( Fig . 1C ) . At the next lower dose ( 2 . 5 µg/kg ) , no mice survived TcdB027 treatment , while all of the mice treated with TcdB003 survived ( Fig . 1D ) . Based on these outcomes we estimated the LD50 of TcdB027 to be between 625 ng/kg and 1 . 25 µg/kg of body weight . In comparison , a higher range for TcdB003 was estimated and fell between 2 . 5 µg/kg and 5 µg/kg of body weight . Thus , in line with previous studies demonstrating more potent effects on cultured cells and zebrafish embryos , TcdB027 also appears to be more toxic than TcdB003 in a rodent model of intoxication . The results shown in Fig . 1 , combined with our earlier findings in the zebrafish model [35] , all point to the fact that TcdB027 is more toxic than TcdB003 . Recent work by Steele and colleagues detected TcdA and TcdB circulating in the bloodstream of piglets infected by C . difficile , and this correlated with systemic effects that could be blocked by passive administration of antibodies against the toxins [52] . This led us to question whether TcdB027 might also cause more extensive systemic damage than TcdB003 due to its higher potency . To assess this , mice were administered TcdB003 ( 2 . 5 µg/kg to 50 µg/kg ) or TcdB027 ( 625 ng/kg to 10 µg/kg ) and tissue pathologies were examined . Tissues and organs from mice administered sublethal doses of the toxins did not reveal pathologies that differed from that of control ( Fig . 2A ) . In contrast , abnormal tissue histologies were found in several of the major organs examined from mice intoxicated with lethal doses of TcdB . Mice treated with either TcdB003 or TcdB027 showed pronounced liver damage with extensive blood-pooling , parenchymal cell loss , and evidence of hemorrhage , which can be visualized by the appearance and expansion of the dark red patches as the survival time progresses ( Fig . 2A ) . To a lesser extent , acute hepatocellular coagulative necrosis and hemorrhage in the spleen along with follicular necrosis and possible apoptotic cells was also detected ( data not shown ) . The severity of the observed pathologies was more related to the length of time of toxin exposure rather than toxin concentration . Figure 2A shows representative liver sections from TcdB003 and TcdB027 treated mice , illustrating that the damage is the more extensive in mice receiving the minimum lethal dose and surviving for the longest period of time . Despite the difference in lethality , the majority of the in vivo effects of TcdB003 and TcdB027 were identical , with the exception of moderate to severe hemorrhage detected in the brain of TcdB027 treated mice . Indeed , brain hemorrhage was the most obvious difference between mice exposed to the two forms of TcdB . The brains of mice treated with TcdB003 displayed only small lesions while the brain hemorrhage of TcdB027-treated mice was profuse with large multi-focal areas of blood accumulation within the cerebellum and cerebrum ( Fig . 2B ) . These data suggest there may be a loss of endothelial integrity in mice challenged with TcdB , as well as a significant difference in the in vivo targeting and tropism of TcdB003 versus TcdB027 . Experiments were next performed to determine the toxicity of the two forms of the TcdB on endothelial cell lines as a possible correlation with the differences in the amount of brain hemorrhage . We first wanted to determine whether endothelial cells displayed increased sensitivity to TcdB compared to the epithelial-like cells ( e . g . CHO cells ) that are normally used in cytotoxicity assays . Rat Aortic Endothelial Cells ( RAEC ) exposed to TcdB003 and TcdB027 displayed very similar cytotoxic doses ( Fig . 3A ) . The concentration needed to cause toxicity in 50% of culture cells ( TCD50 ) for TcdB003 was 6 . 07±1 . 41×10−12 M and 2 . 74±1 . 16×10−12 M for TcdB027 . Since the major differences in pathology between TcdB003 and TcdB027 occurred in the brain , we next tested rat brain microvascular endothelial cells ( RBMVEC ) for differences in sensitivity to the two forms of TcdB . Interestingly , there was a 10-fold difference in the cytotoxicity of TcdB027 on the RBMVECs , with the TCD50 being 6 . 32±1 . 16×10−13 M compared to the TCD50 of 8 . 46±1 . 12×10−12 M for TcdB003 ( Fig . 3B ) . These data indicated that TcdB was highly cytotoxic on endothelial cells , as the previous published observations of TcdB003 and TcdB027 toxicity on CHO cells is 2 . 53×10−11 and 2 . 37×10−13 respectively . Additionally , the RBMVECs had a greater susceptibility to TcdB027 , which correlates with the brain pathologies in Fig . 2B . To further study the differences in the cell and organ targeting between TcdB003 and TcdB027 , we focused on the CTD , which is thought to be important in facilitating cell interactions [39] , [53] . We hypothesized that if this region is indeed important in cell targeting , then the sequence differences between TcdB003 and TcdB027 in this region could be an important factor in the distinct cell tropism and animal pathologies between the toxins . We also predicted that these differences could change the profile of antigenic epitopes , and perhaps neutralizing epitopes , in the CTD . We designed a set of experiments to address both of these possibilities . In order to evaluate differences in the CTD of TcdB003 and TcdB027 we expressed and purified protein fragments representing this region of each toxin . These fragments consisted of the final 721 amino acids of the TcdB protein , including the CROP region along with approximately 206 residues amino terminal to the CROP region . Based on previous sequence comparisons , there are 89 residues that differ between CTD003 and CTD027[35] . Initially , each CTD was used as an antigen to immunize rabbits for the collection of CTD antisera , which were then used in TcdB neutralization assays to further determine the impact of the CTD on the activity of both TcdB003 and TcdB027 . We first investigated the impact of αCTD003 on the cytotoxicity of both TcdB003 and TcdB027 and found that treatment with αCTD003 neutralized the cytotoxic and cytopathic effects of TcdB003 ( Fig . 4A ) . However , αCTD003 caused no detectible reduction in the cytotoxicity of TcdB027 ( Fig . 4A ) . ELISA analysis confirmed that while αCTD003 was only able to neutralize TcdB003 in cell culture , the polyclonal serum could recognize both TcdB003 and TcdB027 in vitro ( Fig . 4B ) . When the αCTD027 antibody was used in the neutralization assay , we found no protection against either TcdB003 or TcdB027 , although the serum strongly reacted with both forms of the toxin as determined by ELISA ( Fig . 4A and 4B ) . The data shown in Fig . 4 suggested that CTD027 and CTD003 differ in their profile of neutralizing epitopes ( i . e . sequences where antibody binding blocks intoxication ) . It was also possible that TcdB027 shared the same sequences of TcdB003 neutralizing epitopes , but , unlike TcdB003 , TcdB027 did not depend on these regions for cellular intoxication . To address this alternative explanation , serum against CTD003 was incubated with a 100-fold excess of CTD003 or CTD027 , and the mixture was tested for its ability to neutralize cytotoxicity of TcdB003 . We reasoned that if CTD027 contains sequences that are targets for antibody-mediated neutralization of TcdB003 then the preincubation with CTD027 should prevent the antiserum from neutralizing TcdB003 . As expected , the addition of CTD003 in the neutralization assay resulted in the inhibition of antibody activity and a return to full cytotoxicity of TcdB003 ( Fig . 4C and 4D ) . In line with the possibility that TcdB027 contains sequences that are neutralizing epitopes in TcdB003 , preincubation with CTD027 also blocked the neutralizing effects antiserum against TcdB003 ( Fig . 4C and 4D ) . The data from the analysis of antiserum against the two forms of TcdB suggested there is likely to be shared epitopes between the two proteins , but the extent of shared and unique epitopes was difficult to predict . In order to begin to identify shared and unique epitopes between TcdB027 and TcdB003 we used solid phase peptide based ELISAs to map antibody reactive sequences in the CTD of TcdB . In all , 358 decamer peptides , overlapping by 8 residues and covering the entire CTD003 sequence , were synthesized and tested for reactivity to CTD003 and CTD027 sera . Sera was collected from rabbits immunized with CTD003 or CTD027 ( n = 2 ) , and when we compared the peptides recognized by αCTD003 to those recognized by αCTD027 we found an overall difference in the pattern of peptides recognized by antisera from the 2 groups ( Fig . 5 ) . Each serum sample was analyzed individually , and the average response of αCTD003 and αCTD027 to the CTD003 peptides is shown in Fig . 5 . The analysis identified identical epitopes , overlapping epitopes , and epitopes unique to each form of the toxin . The analysis identified approximately 7 regions that were recognized only by αCTD003 ( Fig . 5 ) . The analysis also found 4 regions recognized by only αCTD027 and 13 regions where there was overlap or exact matches in the epitopes recognized by both sera ( Fig . 5 ) . The majority of the peptides identified are localized in the CROP domain , and many of the epitopes that differ in recognition between αCTD003 and αCTD027 are located sequentially , within the first seven repeats of the CTD . As summarized in Fig . 5 , peptides recognized by only the αCTD003 serum were variable regions between the two toxins , with as many as 6 amino acid differences as in the case of peptide 21 . In contrast , the peptides recognized by only αCTD027 were highly conserved between the two forms of TcdB , with only one peptide ( #7 ) , with a single amino acid change . These data suggest that sequence variation of TcdB027 impacts antibody recognition of sequential epitopes and may contribute to differences in conformational epitopes as well . The observation that the CTD of TcdB027 is a poor target for the production of antibodies that prevent toxicity on CHO cells , raised concerns about the overall antigenicity of TcdB027 . The majority of the amino acid sequence variation between TcdB003 and TcdB027 occurs in the CTD , so we reasoned that producing antibodies using the holotoxin as an antigen could have better potential to be broadly neutralizing . Both TcdB003 and TcdB027 were inactivated using formaldehyde to create ToxoidB003 and ToxoidB027 . These toxoids were used as antigen to immunize mice and test for protective antibodies against TcdB . After two subsequent boosts , serum was collected from the mice , and the neutralizing effects were tested in vitro . The data in Fig . 6A shows that the mouse antiserum toward ToxoidB027 protected against the cytotoxic effects of both TcdB003 and TcdB027 , while anti-Toxoid003 was not cross-neutralizing and only maintained the cell viability of the CHO cells treated with TcdB003 . The immunized mice were next tested for protection from TcdB in vivo , using a 2-fold minimum lethal dose of TcdB003 or TcdB027 . Consistent with the in vitro neutralization data , all mice immunized with ToxoidB027 were completely protected from i . v . challenge of both TcdB003 and TcdB027 ( Fig . 6B and 6C ) . Immunization with ToxoidB003 provided only a slight , yet significant protective effect , increasing the median survival from 15 h to 24 h in mice injected with TcdB003 , but only from 9 h to 13 h in mice challenged with TcdB027 ( Fig . 6B and 6C ) . Eventually , all of the ToxoidB003 mice succumbed to the effects of TcdB027 , and only two ToxoidB003 mice were fully protected from TcdB003 ( Fig . 6B and 6C ) . Whereas the antisera to the CTD of TcdB027 showed no effect , antibodies to the toxoid form of TcdB027 successfully inhibited toxicity , suggesting that the protective effect against TcdB027 is better conferred by the full-length toxin rather than the CTD in this system .
C . difficile infection is a complex illness commonly involving colitis and , in more severe cases , systemic complications [54] , [55] , [56] . In the current study we sought to determine how systemic complications vary between two forms of TcdB . To focus on the systemic events mediated by the different forms of TcdB , we bypassed the intestinal stage of this illness by directly administering toxin intravenously . This analysis found that TcdB027 was more lethal and caused more pronounced systemic damage than TcdB003 . Further studies revealed this effect correlated with differences in the extent of specific cellular tropisms between the variants of TcdB . Assessing the CTD of TcdB found that this region may contribute to not only differences in tropism , but also accounts for a variability in the antigenic make-up of this domain . Collectively , the data support the notion that TcdB027 is not only more potent than TcdB003 , but may have sequence alterations that prevent cross neutralization . Several recent observations led us to predict that the increased virulence of C . difficile BI/NAP1/027 is due to altered TcdB activity . First , the sequence of TcdB , but not TcdA , varies between the two strains [35] , [57] . Second , in cell culture systems , TcdB027 is more potent on a broad range of cell types [35] , [47] , [57] . Thus , we hypothesized that TcdB027 could have a lower lethal dose and cause more extensive tissue damage in vivo . Our findings support this hypothesis . When experiments compared the lethal doses of TcdB027 and TcdB003 the BI/NAP1/027 toxin was found to be 4 times more lethal than the ribotype 003 toxin ( Fig . 1 ) . More importantly , TcdB027-treated mice died much more quickly and , in some cases , in less than half the time than TcdB003-treated mice . In regards to the pathologies , TcdB027 clearly caused brain damage that was less prominent in mice treated with TcdB003 ( Fig . 2 ) . These findings provide insight into the differences in the in vivo effects of TcdB027 and TcdB003 , and this variation in toxicity could contribute to more severe disease caused by recently emerged strains of C . difficile . Very little is known about the underlying mechanisms of C . difficile-induced systemic damage and complications . The extent to which the pathologies observed in toxin-treated mice reflect systemic complications in humans is not known and there is clearly a need for more studies in this area . However , several reports make it reasonable to suspect the toxins contribute to the systemic complications in this disease [54] , [55] , [56] . The idea that toxin enters the bloodstream during disease is supported by recent work using a piglet model of C . difficile infection where TcdA and TcdB were detected in the bloodstream of the infected animals [52] . Other work has demonstrated that serum IgG , and not mucosal IgA , against the toxins correspond with protection against illness and relapse [58] , [59] , [60] further supporting the notion of systemic effects of these toxins . Thus , the more extensive systemic damage caused by TcdB027 may explain in part why C . difficile NAP1/BI/027 is associated with more severe disease . Our previous studies found that TcdB003 is cardiotoxic and targets cardiomyocytes with an equal efficiency to TcdB027 [35] , [61] . In vivo and in vitro data support the notion that the two forms are TcdB are very similar in their cardiotoxic effects , but the sequence differences in TcdB027 allow the toxin to target other tissues an cell types more effectively than TcdB003 . Consistent with this idea , the TCD50 for TcdB027 and TcdB003 was found to be very similar on aortic endothelial cells , but substantially lower for TcdB027 on brain microvascular endothelial cells . Thus , the evidence to date supports a model where both forms of TcdB are cardiotoxic , but TcdB027 is more potent on other tissue and cell types . The fact that TcdB027 is a more potent toxin than TcdB003 is now well established by several in vivo and in vitro analyses [35] , [47] , including the ones used in this study . Yet , the sequence changes accounting for these differences in activity have not been defined . There are 198 residue differences between TcdB027 and TcdB003 and each of the residues known to be critical for TcdB activities are conserved between the two forms of this toxin . In previous work we found that TcdB027 undergoes more complete autocleavage because it is able to engage intramolecular substrate more effectively than TcdB003 [36] . This implies the conformation of TcdB027 may be different than that of TcdB003 . We have also shown that TcdB027 undergoes dramatic pH-dependent conformational changes more extensively and at a higher pH than TcdB003 [35] . Again , this is unlikely to be related to a single residue change and could be the result of the collective sequence differences . The finding that antibodies against the CTD neutralized TcdB003 but not TcdB027 on CHO cells could be the result of TcdB027 using an alternative means of cell recognition . Interestingly , Olling et al . have reported that the CROP domain of TcdA is involved in cellular uptake of the toxin , but it is not entirely responsible for cell recognition and binding [49] . In a like manner , it is plausible that the role of the CTD has become less significant in TcdB027 and variations have little effect on the toxin . If so , TcdB027 could bind cells by an alternative manner , which helps explain the current data that TcdB027 has a broad effect in mice , as well as previous data that shows extensive necrosis in a zebrafish model of intoxication . The data from the peptide arrays showed αCTD003 reactivity with many epitopes in which the sequence varied in TcdB027 . Whether these sequence variations evolved as a way of allowing TcdB027 to avoid immune recognition or if this is a means of TcdB027 altering its activity , is not yet clear . If the former is true , it could be possible that a change to one single epitope could be responsible for the lack of neutralization of TcdB027 . However , work by Torres and Monath suggests that while the CTD is quite antigenic , antibodies to a single peptide epitope fail to prevent cytotoxicity of TcdB [50] . Finally , in further support of the idea that the two toxins are not identical in their overall structure , three of the epitopes recognized by serum against TcdB027 were not recognized by serum against TcdB003 despite the fact that these sequences were the same ( Fig . 5 ) . The conformational differences in the two forms of TcdB could determine whether identical sequences are antigenic . It is also important to consider this variation in the context of virulence of C . difficile , as well as vaccination . Our previous work suggests that TcdB027 enters cells more rapidly and efficiently than TcdB003 [35] . Given that the CTD is believed to facilitate interactions with the cell surface , it is possible that antigen recognition occurs , but the toxin overcomes this by utilizing a more effective mechanism of cell entry . Arguing against this possibility is the fact that we did not detect even a minor change in the rates of TcdB027-induced cell rounding or the overall level of cell killing . It's also important to note that our experiments involved preincubating TcdB027 with the antiserum . Therefore , if the toxin overcame the neutralizing effect by more efficient cell entry , we would expect to see at least a nominal change in toxicity , but this doesn't appear to be the case . We believe the reasonable explanation is that the neutralizing epitopes of TcdB027 are sufficiently altered to avoid toxin neutralization or that the toxin has a different mechanism of interacting with and entering the cell . These data also suggest successful vaccines targeting TcdB will need to include antigens from multiple forms of this toxin or , alternatively , be designed to target highly conserved neutralizing epitopes shared among variants of TcdB . Although further studies are needed , the toxoid of TcdB027 could provide a vaccine that generates a broadly neutralizing response . Given that the CTD027 did not generate an antibody response that protected CHO cells from TcdB027 , and past studies have found that TcdB toxoid is not a highly effective vaccine [62] , [63] , we were surprised to find the toxoid of TcdB027 stimulated a potent neutralizing response in mice . It has been known for many years that anti-serum does not cross neutralize TcdA and TcdB , making it reasonable to consider the possibility that anti-serum to the variant forms of TcdB also do not cross neutralize . This does not appear to be the case . As shown in Fig . 6 , mice vaccinated with the toxoid form of TcdB027 were completely protected against both TcdB003 and TcdB027 . In line with a prior study by Wang et al . [64] , the toxoid of TcdB003 evoked only marginal immunoprotection against TcdB , and we found this to be true for mice challenged with either the historical or ribotype 027 form of the toxin . This raises the possibility that converting TcdB003 into a toxoid alters the protein in a way that reduces immunogenicity , but sequence differences in TcdB027 make this form of the toxin more effective as a toxoid . Overall , these findings demonstrate critical differences between TcdB produced by ribotype 003 and ribotype 027 strains of C . difficile . The sequence variations in TcdB027 impact the toxin's cytotoxicity , lethality , and antigenic make-up , and likely contribute to the overall heightened virulence of C . difficile BI/NAP1/027 strains .
The animal immunization and toxin challenge studies were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . All animal procedures reported herein were approved by the Institutional Animal Care and Use Committee and Institutional Biosafety Committee at OUHSC ( IACUC protocol # 09-092-I and 11-016-I ) . The procedures precluded the use of anesthesia for in vivo lethal challenge assays . To minimize pain and distress , the mice were monitored at least twice daily and any animals with signs of distress such as labored breathing , lethargy , inability to eat or drink , ruffled fur , disorientation , or loss of 20% body weight were euthanized immediately . This method was approved by the IACUC and monitored by a qualified veterinarian . C . difficile VPI 10463 , a ribotype 003 strain ( produces TcdB with identical sequence to the 630/ribotype 012 strain ) , and C . difficile BI17 6493 , a ribotype 027 strain ( a gift from Dr . Dale Gerding ) , were used as sources of to purify TcdB003 and TcdB027 respectively . Female BALB/cJ and C57B/6J mice ( Jackson Laboratories ) , aged 8 weeks , were purchased from The Jackson Laboratories ( Bar Harbor , ME ) and handled in accordance with IACUC guidelines at University of Oklahoma Health Science Center . Rat Brain Microvascular Endothelial Cells ( RBMVEC ) and Rat Aortic Endothelial Cells were a generous gift from the laboratory of Dr . Eric Howard ( University of Oklahoma Health Sciences Center ) and have been described previously [65] , [66] . CHO-K1 cells were purchased from American Type Culture Collection ( ATCC ) . RBMVEC and RAEC were grown in DMEM containing 10% FBS while CHO cells were grown in F12-K with 10% FBS . All cell types were used between passage 15–30 , and were maintained in tissue culture treated T-75 flasks ( Corning ) at 37°C in the presence of 6% CO2 . C . difficile was cultured using the dialysis method as previously described [35] and TcdB was isolated using anion-exchange ( Q-Sepharose ) chromatography in 20 mM Tris-HCl , 20 mM CaCl2 , pH 8 . 0 , following a thyroglobulin affinity chromatography protocol to first remove TcdA [67] . Purification of TcdB was confirmed by visualization of a single 270 kDa band by SDS-PAGE , and LC/MS/MS analysis ( University of Oklahoma Health Science Center ) . Toxoid versions of TcdB003 and TcdB027 were prepared by mixing 500 µl of TcdB ( 0 . 4 µg/µl ) into 500 µl of 8% formaldehyde with 8 . 5 mg of lysine to help prevent precipitation and aggregation of the formalinized protein [68] , [69] , and incubating at 37°C overnight . The volume was then brought up to 10 ml with PBS , yielding 20 µg/ml of ToxoidB in 0 . 4% formaldehyde with 0 . 425 mg/ml lysine . Both toxoid preparations lacked toxic activity as confirmed by the absence of cytopathic effects on CHO cells . The CTD-encoding region of tcdb gene ( YP_001087135 . 1: nucleotides 4961–7111 ) from the strain VPI 10463 was codon optimized and cloned into pET15b ( Genscript ) . The CTD of the tcdb gene ( YP_003217086 . 1: nucleotides 4961–7111 ) from the NAP1 strain was cloned from a pET15b plasmid containing full-length tcdb that had been codon optimized by Genscript . The CTD gene was amplified using primers 5′-GATCATATGCTGTATGTGGGTAACCG-3′ and 5′-AACGGATCCTTATTCGCTAATAACCA-3′ containing BamHI and Nde1 sites for cloning into pET15b . The CTDs were expressed using Escherichia coli BL21 star DE3 ( Invitrogen ) at 16°C overnight and then purified by Ni2+ affinity chromatography ( HisTrap , GE Life Sciences ) resulting in proteins representing TcdB1651–2366 from both TcdB003 and TcdB027 . To determine the differences in the minimum lethal dose of TcdB003 and TcdB027 , 100 µl of TcdB003 or TcdB027 dilutions in phosphate-buffered saline was injected intravenously into the tails of BALB/cJ mice using a 27-gauge needle . Twenty mice were given TcdB003 in groups of 4 , receiving doses of 2 µg , 1 µg , 500 ng , 100 ng , and 50 ng . Twenty additional mice were injected with doses of 200 ng , 100 ng , 50 ng , 25 ng , and 12 . 5 ng of TcdB027 ( n = 4 ) . The animals were monitored for up to 7 days post challenge for toxin effects and mortality , and mice were euthanized if they became significantly distressed or moribund . Survival was graphed using Kaplan-Meier analyses on GraphPad Prism ( GraphPad Software , Inc . , La Jolla , CA ) . Immediately after death , the mice were dissected and major organs and tissues were submerged in formalin fixative overnight . Tissue sectioning , slide preparation , H&E staining , and pathology analysis was performed by the Department of Comparative Medicine at OUHSC . Two rabbits per group were immunized with 0 . 1 mg of the CTD fragment of TcdB003 or TcdB027 in complete Freund's adjuvant on day 1 and boosted with 0 . 1 mg in incomplete Freund's adjuvant on days 14 , 21 , and 49 . Blood samples were collected on days 0 , 35 , and 56 . These experiments were carried out by Cocalico Biologicals Inc . ( Reamstown , PA ) . BALB/cJ mice ( 20 mice each for ToxoidB003 and ToxoidB027 ) were injected in equal portions subcutaneously and intraperitoneally with 2 µg of toxoid in PBS emulsified 1∶1 in 100 µl of complete Freund's adjuvant on day 1 and boosted with 2 µg in incomplete Freund's adjuvant on day 10 . Control mice were similarly immunized and boosted using an unrelated peptide . Blood samples were collected via tail bleeds on day 0 and 24 , and each bleed was tested by ELISA to evaluate toxoid response . After completion of the immunizations , the mice were subjected to i . v . challenges of TcdB003 and TcdB027 . Each immunization group ( ToxoidB003 , ToxoidB027 , control ) contained 20 mice , and 9 from each group were injected via the tail vein with a 2-fold lethal dose of either TcdB003 or TcdB027 . The previously established minimum lethal dose was used to set the 2×LD100 at 200 ng per mouse for TcdB003 and 50 ng per mouse for TcdB027 . The remaining 2 mice from each group were euthanized and exsanguinated for serum collection . The animals were monitored for up to 7 days post challenge for toxic effects and mortality , and mice were euthanized if they became significantly distressed or moribund . Survival was graphed using Kaplan-Meier analyses and compared with the Log-rank test on GraphPad Prism ( GraphPad Software , Inc . , La Jolla , CA ) . Direct antigen ELISAs were used to measure the antibody reactivity in animal sera . 1 µg of purified TcdB or CTD fragment was coated per well in polystyrene plates at 4°C overnight . The plates were washed and blocked with 0 . 1% BSA in PBS for 1 h at room temperature . Then , the rabbit sera diluted at 1∶100 and 1∶1000 in PBS-Tween with 0 . 1% BSA was added in triplicate and incubated for 2–3 h at room temperature . Plates were washed with PBS-Tween and incubated with anti-rabbit IgG conjugated to alkaline phosphatase ( Jackson ImmunoResearch Laboratories , Inc ) at a dilution of 1∶5 , 000 for 3 hours at room temperature then washed and developed with p-Nitrophenyl Phosphate substrate ( Sigma ) . Plates were read at 405 nm using a Tecan-infinite plate reader ( Tecan Group , Ltd . ) . Plates were read when the positive control reached an OD of 1 . 0 and the assay was considered invalid if the negative control was over OD 0 . 2 . Cells were seeded in 96 well plates at a density of 1–2×104 cells per well in DMEM or F12-K ( ATCC ) containing 10% FBS ( ATCC ) . For TcdB sensitivity measurements on endothelial cells , dilutions of TcdB003 or TcdB027 were added to each well in triplicate , and the cells were incubated 24 h and cell viability was measured by CCK-8 ( Sigma ) . In order to measure neutralization of TcdB , a 1∶10 dilution of serum raised in rabbits against the CTD or mouse serum to the toxoid was preincubated with 37 pM TcdB003 or TcdB027 alone , or with 3 . 7 nM CTD003 or CTD027 , for 1 h at 37°C in F12-K media ( ATCC ) . CHO cells were treated with the toxin/antiserum mixture or toxin alone and incubated at 37°C for up to 24 h . Cells were analyzed under the microscope for cell rounding at 2–4 h and cell viability was measured at 24 h using a CCK-8 assay according to manufacturers instructions ( Sigma ) . The 358 decapeptides overlapping by 8 amino acids covering the length of the CTD region from TcdB003 , were covalently synthesized on polyethylene solid phase supports ( pins ) as previously described and used to assay antibody specificity with a modified ELISA assay [70] . Blocking was performed in 3% milk in PBS for 1 h at room temperature , then the peptides were incubated in 100 µl/well of sera diluted 1∶100 in 3% milk-PBS with 0 . 05% Tween for 2 h at room temperature . The pins were washed 4 times for 8 min with mild agitation in PBS-Tween and then incubated with 100 µl/well of a 1∶5 , 000 dilution of anti-rabbit IgG conjugated to alkaline phosphatase in 3% milk-PBS with 0 . 05% Tween at 4°C overnight ( Jackson ImmunoResearch Laboratories ) . Next , washes were performed as previous and the peptide ELISAs was developed using 100 µl/well of a 1 mg/ml solution of p-nitrophenyl phosphate dissolved in 150 mM carbonate buffer pH 10 . 4 containing 100 mM glycine , 1 mM MgCl2 and 1 mM ZnCl2 . The absorbance was read at 405 nm using a Tecan-infinite plate reader ( Tecan Group , Ltd . ) , and the results were normalized to the standard positive control peptide having an OD of 1 . 0 . Positive epitopes were defined as at least two consecutive peptides with an OD greater than 2 standard deviations above the mean of pre-bleed serum . Relevant SwissProt accession numbers are P18177 ( TcdB003/CTD003 ) , P16154 ( TcdA003 ) , C9YJ35 ( TcdB027/CTD027 ) , C9YJ37 ( TcdA027 ) , | During the past decade , the C . difficile BI/NAP1/027 strain has emerged and in some settings predominated as the cause of C . difficile infection . Moreover , in some reports C . difficile BI/NAP1/027 has been associated with more severe disease . The reasons for association of this strain with more severe disease and relapse are poorly understood . We compared the toxicity and antigenic profiles of the major C . difficile virulence factor , TcdB , from a previously studied reference strain and a BI/NAP1/027 strain . The results indicate TcdB027 , the toxin from the BI/NAP1/027 strain , is more lethal and causes more extensive brain hemorrhaging than TcdB003 , the toxin produced by a reference strain of C . difficile . Furthermore , the results show that the antigenic carboxy-terminal domain ( CTD ) encodes at least 11 epitopes that differ between the two forms of TcdB . In line with this , experiments demonstrate that antiserum against the CTD does not cross-neutralize TcdB003 and TcdB027 toxicity against CHO cells , and TcdB027 appears to be devoid of neutralizing epitopes in this domain . These findings indicate differences in TcdB003 and TcdB027 contribute to increased virulence of C . difficile BI/NAP1/027 and reduce the likelihood of acquired immunity providing cross-protection against infection by these strains . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"immunology",
"biology",
"microbiology"
] | 2013 | Clostridium difficile 027/BI/NAP1 Encodes a Hypertoxic and Antigenically Variable Form of TcdB |
Many natural and artificial networks contain overrepresented subgraphs , which have been termed network motifs . In this article , we investigate the processes that led to the formation of the two most common network motifs in eukaryote transcription factor networks: the bi-fan motif and the feed-forward loop . Around 100 million y ago , the common ancestor of the Saccharomyces clade underwent a whole-genome duplication event . The simultaneous duplication of the genes created by this event enabled the origin of many network motifs to be established . The data suggest that there are two primary mechanisms that are involved in motif formation . The first mechanism , enabled by the substantial plasticity in promoter regions , is rewiring of connections as a result of positive environmental selection . The second is duplication of transcription factors , which is also shown to be involved in the formation of intermediate-scale network modularity . These two evolutionary processes are complementary , with the pre-existence of network motifs enabling duplicated transcription factors to bind different targets despite structural constraints on their DNA-binding specificities . This process may facilitate the creation of novel expression states and the increases in regulatory complexity associated with higher eukaryotes .
One of the most fundamental questions in biology is how incremental evolutionary changes lead to the observed complexity in biological systems . The advent of genome sequencing and associated functional genomic technologies have provided the first evidence for the origins of complexity on an organism-wide scale . Modularity is an emergent property of biological networks that has been observed in metabolic [1] , protein–protein interaction [2] , and transcription factor networks ( TFNs ) [3] . Several explanations have been put forward for the evolution of modular biological systems , which include robustness to mutational [4] and environmental perturbations [5] , insulation against cross-reactivity between alternative signalling cascades [6] , and selection for survival in multiple environments [7] . Parallel studies of small , artificial TFNs have demonstrated that alterations in network topology and components can be used to create a wide range of dynamic properties such as bistability and oscillations . However , relatively few local topologies are widely observed in natural networks [3 , 8] . For example , although a circuit composed of two inhibitory transcription factors ( TFs ) arranged in a feedback loop has been shown to act as a stable memory element in the lambda phage virus and artificial systems [9] , this topology is uncommon in both the Escherichia coli and Saccharomyces cerevisiae transcriptional networks so far uncovered [3 , 8] . An outstanding question is whether the absence of these and other local topologies is a result of mechanistic or functional constraints on network evolution . In this article , transcription regulatory interactions in the yeast S . cerevisiae were defined using the large-scale chromatin immunoprecipitation ( ChIP-on-chip ) dataset of Harbison et al . [10] These interactions were used to define a network with nodes representing genes and directed edges binding of a protein encoded by a TF gene to the promoter of a target gene . We begin by investigating several growth models for the formation of bi-fan motifs , which involve a pair of TFs that bind the promoters of two target genes , as shown in Figure 1 . The bi-fan motif is typically embedded in extended structures that we term the bi-fan array , involving a pair of TFs that both regulate a larger number of common target genes . Figure 1 illustrates how the number of bi-fan motifs within an array grows quadratically as target genes are added . In later sections , we demonstrate a specific structural relationship between bi-fan arrays and the feed-forward loop ( FFL ) motif , and a common origin for many of these network structures . The topology of the bi-fan motif suggests several evolutionary mechanisms for its formation , including duplication of either TFs or target genes [11] . It is also possible that the motifs could have arisen from rewiring of regulatory interactions as a result of cis-sequence evolution in genic promoter regions or the trans-evolution of the protein sequences encoding TFs . The cis-sequence evolution refers to mutations in noncoding regions that alter the binding affinity of TFs for a particular promoter , thus affecting the expression of genes in close proximity on the chromosome [12 , 13] . Conversely , trans-evolution typically involves mutations in the sequences encoding TFs that alter , for example , their DNA-binding specificity . These trans-changes have the potential to alter the expression of large numbers of genes [12 , 13] . In this article , the relative contributions of these mechanisms are investigated by defining a common evolutionary origin for pairs of genes using the whole-genome duplication ( WGD ) event that occurred in S . cerevisiae after its divergence from Kluyveromyces waltii [14 , 15] .
We investigated the organisation of bi-fan motifs in the yeast TFN using two algorithms that have been used previously for detecting motifs in directed networks [3 , 8] . These algorithms fix both the in-degree and out-degree of each node and then randomly replace the edges in the network . This approach can then be used to detect motifs that occur more frequently in the native network than a large ensemble of random networks ( see Methods for further details ) . Although the original methods for detecting network motifs involved exhaustive enumeration of all small ( typically 2- to 6-node ) subgraphs in the network , previous work [3 , 16] suggests that bi-fan motifs are embedded in larger structures within the yeast and E . coli TFNs . In fact , it is possible to show ( see Methods for details ) that the overrepresentation of bi-fan motifs in any directed network is associated with the array structures shown in Figure 1 . Bi-fan arrays were identified in the yeast TFN by searching for pairs of TFs with a number of shared targets that exceeded the number found in the randomized networks with p < 10−4 . A description of the p-value calculation is included in the Methods section . A total of 442 bi-fan arrays were identified at this strict significance threshold . These arrays account for a total of 1 . 25 × 105 ( 68% of the total ) bi-fan motifs compared with an expected number of 7 . 3 × 103 under the null model . The overrepresentation of bi-fan motifs in the Saccharomyces TFN ( shown in Table 1 ) can therefore be attributed to a relatively small number of bi-fan arrays that , on average , regulate a large number of target genes . The following two sections investigate the influence of gene duplication on formation of the bi-fan array structure . Two approaches were used to identify genes that have arisen from duplication . The first method involves using genes that were created from the most recent WGD in the evolution of S . cerevisiae [14 , 15] . These data are likely to be of very high fidelity because of the requirement for genes to reside in regions of doubly conserved synteny with the K . waltii genome [15] . Another advantage of defining common origin using WGD data is that duplication of all genes occurred simultaneously , and duplicates initially possessed very similar promoter regions . This provides a means to estimate the relative cis- and trans-conservation rates upon gene duplication , as shown in Table 2 . Table 2 shows that the trans-conservation rate is relatively high , which is caused by nine of the 17 WGD duplicates forming statistically significant bi-fan arrays . These arrays contain a substantial proportion of the network's bi-fan motifs . Conversely , the cis-conservation rate for all promoters duplicated by WGD is low , with relatively few bi-fan motifs arising from conserved interactions . In the case of promoters of genes that are diverging rapidly , the conservation rate is only slightly above that expected for randomly selected promoters and indicates substantial plasticity in promoter binding . It is also possible to rule out more recent single-gene duplications as a significant source for bi-fan motifs , as these have been estimated to occur very infrequently in S . cerevisiae , at a rate λ = 1–6 × 10−5 per gene per million y [17] . An upper bound for the number of single-gene duplications that have occurred since the divergence of S . cerevisiae from K . waltii can be calculated by assuming that the rate of duplication is at the upper limit and that the rate of loss is zero . The number of gene duplications is then given by the exponential growth model where NG = 3 , 500 is the approximate number of single-copy genes in S . cerevisiae , and T = 100–150 million y is the time since WGD [17] . Equation 1 suggests that the number of single-gene duplications that have occurred since WGD , NG , is less than 35 . Conservation at the levels shown in Table 2 would not result in a large number of bi-fan motifs originating from target gene duplication . WGD is a feature in the evolution of most known eukaryote organisms , including chordates [18] . However , fewer than 10% of yeast proteins originated from the latest WGD in the Saccharomyces lineage . More ancient gene duplications account for the majority ( 90% ) of proteins encoded in the yeast genome [19] . For this reason , we identified duplicates with a more ancient common origin using domain assignments from the Pfam HMM library [20] ( see Methods for further details ) . The results shown in Table 2 have demonstrated that the promoter-binding patterns of duplicate target genes are likely to have diverged on time-scales longer than 100–150 million y , so the analysis is restricted to TFs with common origin identified with the structure of their DNA-binding domains . These results indicate that a total of 27 bi-fan arrays involve TFs with structurally similar DNA-binding domains , accounting for a total of 14 . 4% of the bi-fan motifs . 239 bi-fan arrays containing 49 . 2% of the motifs involve two nonhomologous TFs with the remainder involving at least one TF with an unknown structure . This suggests that more ancient TF duplications have also contributed to the formation of bi-fan motifs in the network ( see Figure S1 ) . In summary , the redundancy of duplicated TFs results in the formation of bi-fan arrays , although the majority of these network structures do not arise directly from gene duplication . Conversely , the duplication of target genes does not appear to contribute greatly to formation of bi-fan arrays because the network is subject to greater cis-plasticity . This difference also arises from the different statistical properties of the ( compact ) in-degree distribution and the ( power-law ) out-degree distributions [21] . Taken together , these results suggest that the two major processes that contribute to the formation of bi-fan motifs are duplication of TFs and the accumulation of common target genes , as depicted in Figure 2A–2B . The colocalization of nonhomologous TFs at genic promoters is likely to involve a combination of two physical mechanisms . The first mechanism involves the presence of binding sites for the two TFs that occur independently in the same set of genic promoters [22] . This process could also enable cooperative binding if a TF displaces nucleosomes that occlude the binding site of a second TF [23] . The plasticity in the promoters of duplicated genes , shown in Table 2 , suggests that bi-fan arrays could have arisen from mutations in promoter regions and subsequent selection for TF binding at numerous dispersed loci . The second mechanism involves protein interactions between the TFs that enable cooperative binding to DNA . For example , mitogen-activated protein kinases without intrinsic DNA-binding affinity are localised to actively transcribed genes during the stress response in yeast via interactions with other proteins [24] . It has also been shown previously [8] that protein–protein interactions tend to occur between pairs of TFs that form bi-fan motifs , and we have confirmed that this property also applies to the bi-fan array structure ( Figure S1 ) . In the following section , we investigate how gain and loss of protein–protein interactions could cause duplicated TFs with similar DNA-binding specificities to bind different targets in vivo . The existence of bi-fan arrays involving nonhomologous TFs suggests that TF duplication could also increase the frequency of these network features . For example , duplication of a TF that forms a regulatory complex would create two further bi-fan arrays , as depicted in Figure 2C . These network features appear as triplets of TFs that form bi-fan arrays with each other , and where two members of the triplet are related by WGD . The network includes 39 of these triplets , containing a total of 2 . 47 × 104 bi-fan motifs . The statistical significance of the triplets of bi-fan arrays involving a pair of TFs originating from WGD can be computed by constructing a null model where the 442 bi-fan arrays are fixed and the 17 WGD relationships are added randomly to the network . This approach can then be used to compare the frequency of these network topologies to that in a large number of randomized networks . The expected number of triplets in the random model is 2 . 96 with p < 10−6 , demonstrating that these network features are a statistically significant property of the network . Further details are provided in Figure S2 . Since the WGD duplications occurred simultaneously [14] , can be identified with high confidence [15] , and were not succeeded by a large number of subsequent duplications [17] , it is possible to assign half of the bi-fan motifs in these arrays to trans-regulatory interactions that were conserved after gene duplication . This accounts for a further 9 . 9% of the bi-fan motifs , and suggests that almost one-fifth of the motifs in the 442 bi-fan arrays can be attributed to a single WGD event . A notable feature of the TFs duplicated by WGD is their very similar consensus DNA-binding specificities . Examples include the TFs MSN2p and MSN4p , which bind the stress response element AGGGG [25] and the leucine zippers YAP1p and YAP2p , which both bind the canonical sequence TTAGTCAGC . These are not isolated examples; almost all pairs of TFs that originate from WGD have similar DNA-binding motifs where these are known [10] . It is therefore not surprising that binding cross-reactivity causes duplicated TFs to occupy similar sets of promoters with the associated conservation of common bi-fan arrays . A more pertinent question is therefore which physical mechanisms enable these TFs to bind different targets in vivo . The most likely mechanism for the divergence of promoter occupancy is that one of the duplicated TFs binds DNA cooperatively with another TF or cofactor via protein–protein interactions [26] or the modification of chromatin structure [23] . The second TF , which lacks such an interaction , cannot bind these promoters with high affinity . A specific example is provided by the forkhead TFs FKH1p and FKH2p , which bind overlapping sets of promoters and have identical DNA-binding preferences in vitro . It has been shown experimentally that differential promoter occupancy is achieved in vivo by FKH2p binding DNA cooperatively with the second TF , MCM1p [27] . This process is recapitulated by our analysis , which indicates that FKH2p forms a bi-fan array with MCM1p , but that this interaction is not shared by FKH1p . Our analysis also implicates the cell-cycle regulator SWI6p as being involved in creating the differential promoter occupancy between the two forkhead TFs . The processes by which the TFs diverge in promoter binding propensities can be understood in terms of conventional models for the functional divergence of gene duplicates [28 , 29] . Immediately after duplication , the derived TFs are involved in an identical set of bi-fan arrays to the ancestral TF . The gain of an interaction that enables cooperative DNA-binding in one member of the pair is known as neofunctionalization , with subfunctionalization involving the loss of such interactions , depicted in Figure 2D . Of the two mechanisms for functional divergence , subfunctionalization is likely to be the dominant source of binding diversity , since the loss of a protein interaction may involve only a few degenerative mutations in one of the TFs , whereas gain requires formation of a novel interaction and subsequent accumulation of target genes [28–30] . This is supported by the rates of sequence evolution [15] in duplicated TFs . In the two pairs of whole-genome–duplicated TFs that have accelerated evolutionary rates compared with their K . waltii orthologue ( the cell-cycle regulators FKH1p and FKH2p , and the stress response genes SKN7p and HMS2p ) , the faster-evolving proteins are involved in bi-fan arrays with fewer partner TFs than the more slowly evolving paralogue ( see Table S3 ) . In summary , many bi-fan motifs in the Saccharomyces TFN originate from WGD . We have provided evidence that the functional divergence of duplicated TFs , which is likely to be involved in the generation of novel expression states , can be understood in terms of the patterns of gain and loss of bi-fan motifs within the overall structure of the network . The following section investigates the influence of WGD on the formation of FFL motifs . Having suggested putative evolutionary models for the formation of bi-fan motifs in the S . cerevisiae TFN , we now turn our attention to the FFL . Although the FFL has a topology that appears distinct from the bi-fan motif , the presence of bi-fan arrays suggests another simple mechanism for formation of large numbers of FFL motifs . This process is depicted in Figure 3 . In total , there are 43 stastically significant bi-fan arrays that form at least one regulator–regulator interaction , accounting for a total of 1 , 773 ( 61 . 2% of the total ) FFL motifs in the TFN . Since these pairs of transcription regulators are expected to be involved in only 36 FFLs , these network features are sufficient to explain the deviation from the null model . The yeast WGD data indicate that four FFL arrays arise directly from WGD containing 334 ( 18 . 8% ) FFL motifs . A further 11 FFL arrays , containing 299 ( 16 . 8% ) FFL motifs , involved one of the bi-fan arrays conserved after TF duplication . In none of these cases were the FFL-forming interactions conserved between duplicated TFs . We investigated whether FFLs were a statistically significant feature of the network given its bi-fan structure by randomizing edges between transcription regulators while holding interactions between transcription regulators and nonregulators constant ( see Methods ) . This procedure fixes the vast majority of edges present in bi-fan arrays but involves rewiring of the regulatory interactions between TFs that could give rise to FFLs . Table 1 and Figure 4 show that the FFL topology remains statistically significant under this null model . Figures 4 and 5 show the frequencies of FFLs and bi-fan motifs as pairs of directed edges are swapped randomly , and demonstrate the sensitivity of the number of FFLs to rewiring of a small number of regulator–regulator interactions . Figure 5 confirms that the number of bi-fan motifs is affected only weakly by randomization of interactions between transcription regulators . The majority of FFL motifs in the yeast TFN result from one or two direct regulatory interactions existing between TFs that form a statistically significant bi-fan array . Although experiments involving randomization of edges between TFs while other parts of the network are fixed suggest that the FFL motif remains overrepresented in natural networks , independently of the presence of bi-fan arrays , it is also possible that the FFL-forming edges could arise from some other nonselective process such as gene duplication . To investigate this question , we used a generalized linear model [31] to fit the probability of a directed regulatory interaction between TF , a , and a second TF , b , as a function of several local network properties ( see Methods for full list ) . This statistical model was used to identify the network variables that are informative in predicting whether such an interaction occurs . The final model indicates that the probability of forming a regulatory interaction increases with the out-degree of node a and the number of targets shared by the pair of TFs ( i . e . , the size of the bi-fan array ) , but that interactions are suppressed if the second TF b directly ( auto- ) regulates its own transcription . Figure 6 shows a measure of the error of optimized linear models involving subsets of these variables , and indicates that the out-degree has the greatest influence on the probability of forming a regulator–regulator interaction . This would be expected under a neutral model; however , the importance of the second term indicates that there is a propensity toward formation of FFLs from bi-fan arrays in the yeast TFN . This supports there being positive selection toward formation of the FFL motif and the signal-processing properties associated with this topology [32] . The previous sections have demonstrated that network motifs are typically organized in larger structures that are likely to have originated from two specific growth models . In this section , we investigate whether network motifs originating from duplication of TFs also contribute to more global properties of the network such as its overall modularity [33] . This feature of the TFN was investigated by using a divisive algorithm for partitioning the network into densely connected groups of nodes , which constitute modules , with sparser connections between groups [34] . The network was partitioned into 18 modules with an overall modularity score Q = 0 . 50 , which suggests significant community structure [33] . The dendrogram in Figure 7 shows a representation of the division path of the algorithm and enriched functional annotations associated with all genes in the extant modules ( see Text S1 ) . The algorithm defines a hierarchy of modular structures , with the more “coarse-grained” solutions also representing relevant network structures [34] . In this case , the five coarsest granularity partitions represent the broad functional classes of small molecule transport , cell cycle/reproduction , protein synthesis , protein degradation , and metabolism . Figure 7 also shows enrichment of structural families within each module , and indicates that members from several structural families of DNA-binding protein are not distributed uniformly . The most recent WGD in Saccharomyces can be used to investigate whether duplicated TFs diverge from the ancestral network module , and whether the duplication has contributed to the overall modularity of the network . This latter property is quantified by calculating the change in the modularity upon deletion of each node , which allows identification of modular ( ΔQ > 0 ) and nonmodular TFs . Of the 15 pairs of TFs where both members bind a significant number of promoters under the conditions assayed by Harbison et al . , 11 are members of the same module ( p < 0 . 01 under permutation of module labels ) . In nine of the pairings , both TFs contribute positively to the modularity of the network , suggesting that gene duplication is involved in the formation of modular networks ( the scores are tabulated in Table S3 ) . There are three further pairs of duplicated TFs in which the sign of ΔQ differs between the duplicates , and in which the membership of bi-fan arrays has diverged asymmetrically . If subfunctionalization , which in this context involves the loss of common bi-fan arrays , is the dominant source of functional divergence [30] , these examples suggest that the TF that retains the majority of the ancestral functions remains a global ( nonmodular ) regulator , and that the mutations lead to specialization of its duplicate . Interactions between TFs that lead to creation of FFL arrays also tend to increase network modularity , since the majority ( 31 out of 43 ) involve intramodule connections ( p < 0 . 01 ) .
We have shown that the overrepresentation of bi-fan motifs in any directed network is associated with bi-fan array structures rather than individual network subgraphs . This property has been observed empirically in the original article describing network motifs in E . coli , which showed that bi-fan motifs are organised in dense overlapping regulons which consist of small numbers of TFs and operons that have particularly dense connectivity , and which also have few connections to the rest of the network [3] . Other work in E . coli has shown that clustering individual bi-fan motifs by overlap of any of their components leads to recovery of the network's largest fully connected component , and that a similar property can be observed for FFLs [16] . Many of the bi-fan arrays and the motifs within them can be attributed to the WGD event that occurred recently in the evolution of Saccharomyces , with the overwhelming majority of these structures arising from duplication of TFs . These represent a subset of the duplicative bi-fan arrays within the network , suggesting that many more of these network structures may also arise from divergent mechanisms of network evolution . It is possible that structural or sequence similarity could be used to detect more complex bi-fan architectures arising from ancient TF gene duplications . However , this is complicated by the rapid sequence divergence of TFs [15 , 17 , 35] and the potential for a particular network topology to be created by several alternative combinations of TF duplication and edge rewiring . It is clear , however , that the TFs arising from WGD have a larger number of shared targets and conserved network motif properties than more ancient duplicates . An outstanding question is whether this property is caused solely by the late occurrence of WGD in Saccharomyces or is also affected by the different effects of gene dosage in single-gene duplication and WGD events [36] . Although many bi-fan arrays originate from TF duplication , there is evidence that this topology also arises from environmental selection via the accumulation of DNA-binding motifs in promoter regions [22] or protein–protein interactions between TFs [8 , 24] . A mixture of these two effects is known to be a feature of mechanisms for combinatorial control of gene expression [26 , 37] . This article has also provided evidence that the cooperative binding of TFs to DNA is also likely to be involved in creating the functional divergence of duplicated TFs , as depicted in Figure 2C–2D . This mechanism may be particularly important for enabling increases in regulatory complexity to occur in unicellular organisms where redundant duplicate proteins cannot persist in the genome as a result of genetic drift [38] , and consequently the fixation rate of single-gene duplications is very low [17] . The analysis of target genes indicates that the conservation of the TFs bound to duplicated promoters is related to the rate of sequence divergence of their associated genes , independently of molecular clock–based assumptions of the age of the duplication event [39 , 40] . This analysis also demonstrates that the cis-conservation is typically low and is restricted either to recent duplicates or the small number of genes that are stabilised by gene conversion [15 , 17] . Target gene duplication does not therefore make a substantial contribution to the formation of network motifs in the yeast TFN , contrary to other studies of Saccharomyces TFN evolution [11] . The rapid divergence in the promoters of duplicate genes is in agreement with other studies showing that gene expression evolves much more rapidly than an organism's gene content [12 , 13] . This result provides an explanation for a recent study of motif evolution [41] , which found that the protein constituents of individual network motifs do not tend to co-occur across several very divergent yeast species . It was thus suggested that the motifs themselves are nonconserved and therefore not critical to the functionality of the network . However , the rapid cis-changes presented in Table 2 and the presence of positive selection toward motif formation suggest that the motif structures may be present in the comparison genomes , although their identity is likely to have changed on these relatively long time-scales . This is supported by the convergent evolution of similar network structures across diverse organisms , such as that observed between the human embryonic stem cell regulators SOX2 , OCT4 , and NANOG [42] . FFL motifs arise from a small number of regulatory interactions between TFs that form statistically significant bi-fan arrays . Our analysis indicates that there is likely to be positive environmental selection for the high/low-pass filtering properties of the FFL motif [3 , 32] independently of the bi-fan array topology . As a result , FFL motifs could act as both a source and a consequence of duplicative bi-fan arrays in the course of network evolution . An outstanding question concerns the chronology of FFL formation , as it is not clear to what extent the existence of an FFL-like topology accelerates the accumulation of target genes or whether FFLs arise from existing bi-fan array structures , as depicted in Figure 3 . The static representation of the yeast TFN , representing a union of DNA-binding interactions across numerous environmental conditions , can be partitioned into modules that represent specific biological functions . Some structural families of DNA-binding proteins are not distributed uniformly across the network modules and are also involved in a larger number of bi-fan arrays with members of their own family . There are two potential causes for this observation . The WGD data indicates that TFs duplicated by WGD tend to occupy the same network module and share far more common targets than more ancient duplicates . It is therefore possible that proteins within a particular family underwent lineage-specific expansions more recently than other families . This appears to be the case for the YAP TFs , of which between two and three TF pairs originate from WGD [15 , 43] . The other possibility is that constraints on the diversity of binding sites available to a particular family of TFs [44 , 45] lead to a slower divergence of promoter binding , as exemplified by the GATA-binding family of Zinc-finger TFs . In summary , the TFN contains many features that reflect the evolutionary history of the organism ( i . e . , divergent evolution ) , suggesting that its structure does not necessarily reflect an optimal “design” [46] , and that evolutionary constraints contribute to both the modularity and network motifs that are present in the network . However , there is also strong evidence for the involvement of natural selection in the formation of network motifs beyond the neutral duplication–divergence model . The motif concept also provides a framework for understanding the mechanisms that have enabled increases in regulatory complexity to occur in a simple eukaryote , and which are also likely to apply to higher organisms .
The TFN was generated using the original gene-mapped ChIP-on-chip data from Harbison et al . [10] . The raw binding profiles were thresholded at a p-value of 10−3 . TFs were classed as bound to an intergenic region if the binding profile was below the threshold in any of the assays carried out under alternative growth conditions . This included around 11 , 000 unique interactions between regulators and promoter regions . Randomization of the networks was carried out using modified versions of the two algorithms used in [3 , 8] . Both these methods ensure that the networks' degree distributions remain unchanged by fixing both kin and kout for each node [47] while randomly rewiring edges . One of the algorithms involves repeatedly swapping nonisomorphic pairs of directed edges until the network is sufficiently randomized . The second algorithm involves specifying a set of in and out stubs for each node . Directed edges are then added from each out stub to a randomly selected in stub while again preserving the networks' in- and out-degree distributions . The two algorithms for generating null networks were found to produce identical results , provided that a sufficient number of iterations were carried out in the edge-swapping algorithm . The number of bi-fan motifs within the TFN , fbi-fan , can be rewritten in an alternative form , which suggests that this particular motif is , in general , associated with array structures such as that shown in Figure 1 where the summations are over the NT TFs , or nodes with nonzero out-degrees , and where k ( xi , xj ) is the number of targets shared by TFs xi and xj . Equation 2 implies that for bi-fan motifs to be overrepresented in the network , there must be pairs of TFs ( xi , xj ) that have a greater number of shared targets than under an equivalent null model of the network . The standard approaches to generating null network models [3 , 8 , 47] involve randomization of directed edges while preserving the in- and out-degree of each node . This null model provides an additional constraint on Equation 2 where kiin is the in-degree of node i and N is the total number of nodes in the network . Intuitively , Equation 3 represents the frequency of “mono-fans” in the network ( i . e . , two TFs binding to the same target ) . The left-hand side of Equation 3 represents the frequency of “mono-fans” in terms of the number of shared targets for each pair of TFs , which may vary in different randomizations of the network . The right-hand side represents this quantity in terms of the ( fixed ) in-degree sequence . The constraint in Equation 3 indicates that a high degree of overlap for a subset of the TFs , required for overrepresentation of bi-fan motifs , implies a lower number of shared targets for other pairs of TFs . This suggests that bi-fan motifs are characteristic of networks with a modular or community structure [3 , 33] . Bi-fan arrays were identified by searching for pairs of TFs with a number of shared targets that exceeded the number found in 9 , 995 of the randomizations of the network . Figure 8 indicates the number of bi-fan arrays identified at the highest significance thresholds . Since there are a total of 176 TFs with kout ≠ 0 in the ChIP-on-chip dataset [10] , there are a total of 1 . 54 × 104 comparisons . A total of 595 arrays were recovered at this threshold , with an expected number of 15 . 4 for a random network . The number of targets shared by pairs of TFs in the randomized networks is well approximated by a Poisson distribution , which was used to estimate p-values for the bi-fan arrays identified to be significant from the bootstrap estimates ( see Text S1 ) . A total of 442 of the bi-fan arrays were significant at the threshold , which is the stringent threshold used in further analyses . A total of 297 bi-fan arrays were found at the p < 0 . 05 threshold after a Bonferroni correction for the multiple hypotheses tested . The Pfam domain assignments were verified using the Saccharomyces Genome Database ( http://www . yeastgenome . org ) , which also provided annotations for three additional TFs ( INO4p , XBP1p , and CUP1p ) that were missed by Pfam . The basic leucine zipper predictions were manually subdivided into the YAP and AP-1 families using definitions from the literature [48] . The two largest families of TFs in yeast , the classic Zinc-finger and the Zn-Cys binuclear cluster domain , are short , ancient domains that typically form one of many contact points between the TF and DNA [49 , 50] . Consequently , the shared presence of these domain types is not necessarily indicative of recent divergence or similar DNA-binding specificity . These families were therefore subdivided using sequence clustering . The BLASTclust program was used with sequence identity set to 25% and the alignment length parameter set to 0 . 25 . This procedure may result in more distant duplicates being missed but increases the statistical significance of any homologous bi-fan arrays identified from analysis of the yeast TFN ( groupings can be found in Text S1 ) . Several generalized linear models [31] were used to fit the probability of a regulatory interaction between a pair of TFs , f ( πi ) , as a function of local network properties . where xi = [x1 , x2 , … , xj] is the vector of network properties , β and α are the parameters of the model , and f ( · ) is the link function . Several link functions , including linear , logistic , and log–log , were compared using the deviance and the Hosmer-Lemshow criterion [31] . The log–log model provided the best fit under both measures and was used to model the full set of network variables . The initial set of variables were the out-degree of node a , kaout , the out-degree of node b , the number of targets shared by the pair of TFs , kabarray , the expected number of shared targets , and binary variables representing a feedback or autoregulatory interaction at node a , autoregulation at node b ( kbauto ) , transcription regulation of node a by node b , homology , and genome duplication . Backward stepwise elimination was then used to remove uninformative variables ( see Text S1 and Figures S3 and S4 for further details ) , and resulted in the following model , indicating that the probability of forming a regulatory interaction between TFs increases with the out-degree of node a and the number of targets shared by TFs a and b . Conversely , interactions are suppressed if the second TF b directly regulates its own transcription . The modularity of the network is defined using the criterion Q , which is defined for undirected networks , but can be applied to the Saccharomyces TFN by considering each edge as undirected [33] , where the sum is over the number of identified modules , Nm , L is the number of edges in the network , ls is the number of intramodule edges , and ds is the sum of the degrees of the nodes in module s . Intuitively , a cluster contributes a large ΔQ to the network's overall modularity if the number of intramodular connections is much larger than the number expected in an equivalent network with edges placed at random ( a null model that corresponds exactly to the randomization procedures used in this article [47] ) . The standard approach to module identification is to seek a partition of the network such that the modularity , ΔQ , is maximised . In this study , a spectral module detection algorithm [34] is used , which involves solving a series of eigenvector problems on a characteristic modularity matrix . The algorithm divides the network recursively into disjoint binary partitions until no further increase in the modularity is recovered . The division of the network can then be used to calculate the sensitivity of Q to the deletion of nodes from the network , ΔQ . | Networks are a simple and general way of representing natural phenomena that range in scale from the social interactions between people to the organization of circuits on a microchip . Many networks have been found to contain repeated patterns of connections between small groups of nodes . These patterns , termed network motifs , are thought to be involved in controlling the flow of information through the network . This article investigates the processes that led to the formation of the two most common types of motif in the network controlling gene expression in baker's yeast . Around 100 million y ago , yeast's ancestor underwent a whole-genome duplication , which resulted in the organism containing four copies of each gene rather than the usual two . The duplicated genes that remain in the yeast genome are used to infer the two mechanisms that give rise to network motifs . These are rewiring of interactions between genes , and the duplication of proteins that control gene expression ( transcription factors ) . These two processes are complementary with the rewiring mechanism enabling duplicated transcription factors to regulate the expression of different genes . It appears likely that these two processes are involved in enabling the increases in complexity that are associated with multicellular life . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"saccharomyces",
"computational",
"biology"
] | 2007 | Evolutionary Models for Formation of Network Motifs and Modularity in the Saccharomyces Transcription Factor Network |
Human papillomavirus type 16 ( HPV16 ) and other oncoviruses have been shown to block innate immune responses and to persist in the host . However , to avoid viral persistence , the immune response attempts to clear the infection . IL-1β is a powerful cytokine produced when viral motifs are sensed by innate receptors that are members of the inflammasome family . Whether oncoviruses such as HPV16 can activate the inflammasome pathway remains unknown . Here , we show that infection of human keratinocytes with HPV16 induced the secretion of IL-1β . Yet , upon expression of the viral early genes , IL-1β transcription was blocked . We went on to show that expression of the viral oncoprotein E6 in human keratinocytes inhibited IRF6 transcription which we revealed regulated IL-1β promoter activity . Preventing E6 expression using siRNA , or using E6 mutants that prevented degradation of p53 , showed that p53 regulated IRF6 transcription . HPV16 abrogation of p53 binding to the IRF6 promoter was shown by ChIP in tissues from patients with cervical cancer . Thus E6 inhibition of IRF6 is an escape strategy used by HPV16 to block the production IL-1β . Our findings reveal a struggle between oncoviral persistence and host immunity; which is centered on IL-1β regulation .
The innate immune system is the first line of defense in response to danger signals from microbial invasion or tissue injury . Viruses are sensed by several immune receptors that activate signaling pathways leading to cytokine production . Many oncogenic viruses can deregulate several immune-related pathways which guarantee a persistent infection . High-Risk Human Papilloma Viruses ( HR HPV ) are the etiological factor of cervical as well as certain head and neck cancers and is responsible for 20% of all human cancers linked to infection [1] . Persistence and progression of the disease are achieved by deregulating both cellular and immune defense mechanisms . Among the HR types , HPV16 is the most prevalent type in premalignant and malignant cervical lesions [2] . HPV16 viral oncoproteins E6 and E7 can target many cellular proteins such as binding and degrading the tumor suppressors’ p53 , and pRb , respectively . In parallel E6 and E7 are able to deregulate several innate immune-related pathways that block cytokine and chemokine production , antigen presentation , and adherence molecules [3] . Recently Lau et al . , showed that E7 from HPV18 suppresses the cGAS pathway by inhibiting the adapter protein STING [4] . Similarly , some antiviral genes induced by interferons such as IFIT1 , MX1 and the innate sensors RIG-I , TLR3 and TLR9 are also inhibited by HPV [5 , 6] . Indeed , Niebler et al . , and Karim et al . , have shown that HPV is capable of blocking IL-1β [7 , 8] . On the flip side , host cells have strategies to thwart viral immune escape . IL-1β is crucial in host-defenses towards infection and injury . Our current understanding is that regulation of IL-1β is controlled by two checkpoints: 1 . The activation and translocation of the nuclear factor-κB ( NF-κB ) which initiates the transcription of the pro-IL-1β gene . 2 . Post-translational regulation of pro-IL-1β into its cleaved form by the inflammasome cytosolic multi-protein complex . The inflammasome complex consists of an innate pathogen recognition receptors such as the nucleotide-binding domain and leucine-rich repeat pyrin domain 3 ( NLRP3 ) or absent in melanoma 2 ( AIM2 ) . Upon viral recognition the inflammasome sensor recruits the apoptosis-associated , speck-like protein containing a carboxy-terminal CARD ( ASC ) . Caspase-1 is activated within the inflammasome multiprotein complex through interaction with ASC that bridges NLRP3 or AIM2 . The activation of caspase-1 is associated with pyroptosis , a form of programmed cell death distinct from apoptosis , as well as the cleavage of the proinflammatory cytokines IL-1β and IL-18 . Once released , mature IL-1β and IL-18 signal to their target cells , thus allowing the expansion of innate and adaptive immune responses . NLRP3 inflammasomes are activated by viruses such as adenovirus [9] , vaccinia virus [10] , and hepatitis C virus ( HCV ) [11] . The AIM2 inflammasome has been shown to detect vaccinia virus [12] and murine CMV [13] . Whether the inflammasome plays a protective role against HPV16 remains to be investigated . Here we demonstrate that HPV16 induces the secretion of IL-1β from human keratinocytes . IL-1β produced from HPV16 infected keratinocytes blocked gene viral transcription . However , inhibition was lost after 8h due to the ability of the viral oncoprotein E6 ( 16E6 ) to inhibit IL-1β transcription . A 16E6 protein binding domain essential for p53 degradation played a crucial role in regulating IL-1β transcription . 16E6 blocked the p53 transcriptional regulation of Interferon Regulatory Factor 6 ( IRF6 ) , which we found was essential for IL-1β promoter activity . The identification of this inhibitory transcriptional loop represents an undiscovered mechanism of oncoviral immune hijacking in the infected host cell .
We first determined whether inflammasome activation could be achieved in normal human keratinocytes , the host of HPV infection . Addition of poly dA:dT ( an AIM2 activator ) or Nigericin ( an NLRP3 agonist ) led to the secretion of IL-1β ( S1 Fig ) . Of note , the induction of pro-IL-1β did not require the first check point signal ( S1A Fig ) . Pro-IL-1β is constitutively expressed in human keratinocytes and has been previously described by Sand et al . , and Zepter et al [14 , 15] . We next tested whether HPV16 induced IL-1β gene expression in human keratinocytes . To do this , we generated HPV16 Quasivirions ( 16QsV ) that closely resemble the natural virus as well control Pseudovirions ( PsV ) . 16QsV are viral particles that contain the full viral genome of HPV16 encaspidated by the viral late proteins L1 and L2 ( L1/L2 ) . PsV are viral particles that contain GFP DNA encaspidated by L1/L2 [6] . Infection in keratinocytes with 16QsV up to 4h led to an increase of IL-1β transcripts ( Fig 1A ) . However , post 8h infection , IL-1β transcription decreased ( Fig 1A ) . The level of IL-1β gene expression inversely correlated to viral gene transcription ( Fig 1B ) . Furthermore , primary keratinocytes infected with 16QsV induced IL-1β or IL-18 secretion at 4h but not at 24h ( Fig 1C ) . 16QsV induction of IL-1β depended on caspase-1 activity ( S1B Fig ) . Pyroptosis was also induced by 16QsV as measured by lactate dehydrogenase activity ( S1C Fig ) . We did not observe IL-1β secretion when PsV or when extracts of the late proteins L1/L2 was added to keratinocytes ( Fig 1C ) . These data suggest that 16QsV can induce caspase -1 dependent IL-1β , IL-18 as well as pyroptosis during the early phases of infection . IL-1β has been shown to block HBV replication in human hepatocytes [16] . Therefore we evaluated whether IL-1β could inhibit HPV16 viral gene transcription . Primary keratinocytes were infected with 16QsV or PsV ± recombinant IL-1β . We observed that IL-1β blocked 16QsV viral expression as measured by E1 transcripts ( Fig 1D ) . This effect was reversed when we blocked the IL-1 receptor using Anakinra ( Fig 1E ) . The viral oncoproteins E6 and E7 inhibit several innate immune pathways such as TLR9 , STING and IRF signaling [4 , 6 , 17] . Based on these reports we hypothesized that E6 and E7 were responsible for the inhibition of IL-1β . To test this , human primary keratinocytes were transduced with recombinant retrovirus expressing HPV16 E6 and E7 ( 16E6E7 ) or with the empty vector control ( pLXSN ) . 16E6E7 blocked both AIM2 and NLRP3-mediated secretion of IL-1β ( Fig 2A ) . Furthermore , knock down of the viral oncoproteins using siRNA targeting16E6E7 restored the ability of cells to produce IL-1β ( Fig 2B ) . In the epidermis , keratinocytes are the first cells to be encountered by external stimuli to induce IL-1β which in turn stimulates IL-8 secretion by human dermal fibroblasts [18] . We established an IL-8 bioassay in which addition of recombinant IL-1β induced IL-8 promoter activity of the luciferase gene in HEK293 cells ( Fig 2C ) . Specificity of the assay was controlled using IL-1R inhibitor ( Anakinra ) ( Fig 2C ) . Supernatants that were derived from AIM2 stimulated primary human keratinocytes induced the expression of the IL-8 luciferase gene . However , supernatants derived from AIM2 stimulated 16E6E7 cells failed to induce IL-8 transcription ( Fig 2D ) . Furthermore , knock down of the viral oncoproteins using siRNA for 16E6E7 restored the ability of a cervical cancer-derived cell line ( SiHa HPV16+ ) to produce IL-1β in response to Nigericin , poly dA:dT and 16QsV ( Fig 2E ) . Thus 16E6E7 oncoproteins block IL-1β secretion . We corroborated our findings using supernatants from cervical cancer cell lines that were stimulated with the NLRP3 ligand . We observed that supernatants from the cervical cell line C33A ( HPV- ) stimulated with nigericin induced IL-8 luciferase activity ( Fig 2F ) . Furthermore , Anakinra blocked IL-8 gene induction from supernatants derived from C33A cells stimulated with the NLRP3 ligand ( Fig 2F ) . In contrast , supernatants taken from SiHa and CaSki cells ( HPV16+ ) that were stimulated with nigericin failed to induce IL-8 promoter activity ( Fig 2F ) . In summary , we have demonstrated the ability of HPV16 E6 and/or E7 to block IL-1β paracrine induction of IL-8 transcription . We hypothesized that the loss of IL-1β production might be due to the ability of 16E6E7 to block NLPR3 and AIM2 transcription . Neither AIM2 nor NLRP3 transcript levels were altered in human primary keratinocytes transduced with 16E6E7 , compared to the pLXSN control ( S2A Fig ) . HPV16 E6 and E7 interact with p53 and retinoblastoma ( pRb ) , respectively , and promote their degradation via the proteasome pathway [19] . Therefore , we next determined whether a similar mechanism affected NLRP3 or AIM2 protein expression in 16E6E7-expressing keratinocytes . Human NLRP3-CFP , AIM2-CFP or p53 constructs were co-transfected with 16E6E7 or pLXSN in human primary keratinocytes and their expression was examined by immunoblotting . We did not observe any alteration in AIM2 or NLRP3 protein levels . As expected we found that p53 was degraded by 16E6E7 ( S2B Fig ) . As we did not detect any change at the receptor level , we next focused our attention on the downstream signaling molecules that are shared between NLRP3 and AIM2 . Inflammasome activation requires ASC dependent caspase-1 maturation of pro-IL-1β [12] . Neither ASC nor caspase-1 transcript levels were altered in 16E6E7 compared to pLXSN transduced cells ( S2C Fig ) . In addition cleavage of pro-caspase-1 was detected in 16E6E7 transduced cells stimulated with NLRP3 or AIM2 ligands ( S2D Fig ) . We observed that levels of the pro-form of IL-1β were already reduced in 16E6E7 compared to LXSN transduced cells . These data indicated that the synthesis of IL-1β was affected by the viral oncoproteins before AIM2 or NLRP3 stimulation ( Fig 3A–3C ) . The same loss of pro-IL-1β was observed in cervical cancer cell lines positive for HPV16 ( Fig 3D ) . All these observations showed that 16E6E7 exerts an inhibitory effect on the synthesis of the pro-form of IL-1β . While Niebler et al . , previously reported the ability of 16E6 to degrade pro-IL-1β via the proteasome [8] , under our experimental conditions the addition of a specific proteasome inhibitor on 16E6E7 expressing keratinocytes did not restore the pro-IL-1β protein ( Fig 3E ) . As expected , p53 levels increased in the presence of 16E6E7 confirming the specificity of the proteasome inhibitor ( Fig 3E ) . Protein levels for 16E6 were controlled by western blot ( Fig 3E ) . Indeed an alternative hypothesis was that 16E6E7 proteins can alter IL-1β mRNA , as shown by Karim et al , and Niebler et al . , [7 , 8] . We observed that 16E6E7 blocked the level of IL-1β transcripts compared to normal cells ( Fig 3F ) . Little or no IL-1β mRNA was detected in CaSki or SiHa compared to C33A cells ( Fig 3G ) . These data indicated that 16E6E7 in human keratinocytes as well as in cervical cancer cells supresses mRNA expression of IL-1β . HPV16 may use E6 and/or E7 to directly inhibit IL-1β transcription . To determine whether HPV16 E6 or E7 proteins influence IL-1β transcription , the IL-1β promoter linked to the luciferase reporter gene was co-transfected ±16E6E7 , 16E6 or E7 into spontaneously immortalized human keratinocytes ( NIKs ) . NIKs already expressed high protein levels of endogenous pro-IL-1β . Indeed high basal luciferase activity was detected in these cells after transient transfection . However , 16E6E7 inhibited IL-1β luciferase activity even with low DNA concentrations ( Fig 4A left ) , indicating that 16E6E7 can block the transcription of the IL-1β . . Furthermore 16E6 , and to a lesser extent 16E7 , inhibited IL-1β promoter activity ( Fig 4A and 4B ) . Knock down of 16E6 restored pro-IL-1β ( Fig 4C ) . We also compared the efficiency of E6 from other high-risk ( HR ) human papillomavirus types and one low risk ( LR ) type in repressing IL-1β transcriptional activity . HR types 18E6 and 31E6 inhibited IL-1β transcription , although less efficiently than 16E6 ( S3A Fig ) . LR HPV6E6 did not affect IL-1β promoter activity ( S3A Fig ) . These data demonstrated that E6 from HPV16 as well as other HR types strongly inhibit IL-1β transcription . We next made deletions in the promoter to determine which region is required by 16E6 to inhibit IL-1β transcription . ( Fig 4D ) . WT and IL-1β deletion constructs were co-transfected with 16E6 . We restored IL-1β promoter activity with deletion 2 in the presence of 16E6 ( Fig 4E ) . The deletion contains an area called LILRE was previously characterized by Unlu and colleagues [20] . The LILRE element has a high degree of inter-species conservation and plays and important role in IL-1β regulation ( Fig 4F ) . Within the LILRE region , Unlu et al . , showed the involvement of three different protein binding sites [20] , an Spi-1 cis site ( ETS ) ; an IRF8-binding site ( ISRE ) and a Stat1 cis site ( GAS ) [20] . We hypothesized that 16E6 requires the regulatory LILRE site to inhibit IL-1β transcription . To test this , primary human keratinocytes were co-transfected ± 16E6 or pLXSN with WT , delLILRE ( deletion of the LILRE site ) and constructs that contained point mutations ( m ) for ISRE , ETS or GAS on the IL-1β promoter . Luciferase activity was restored with the delLILRE promoter indicating that this site contains a region required for IL-1β inhibition by 16E6 ( Fig 4G ) . Luciferase activity remained suppressed in cells transfected with ETS mutant , suggesting that this cis element was not involved in the down-regulation of IL-1β transcription by 16E6 ( Fig 4G ) . Luciferase activity was partially rescued in cells transfected with the mGAS promoter ( Fig 4G ) . However , a complete rescue was observed in cells that were transfected with the mISRE promoter in the presence of 16E6 . These results suggested that IL-1β down regulation by 16E6 principally involves the ISRE site on the IL-1β promoter . The observation that an ISRE site is required for IL-1β suppression by 16E6 prompted us to determine which transcription is involved in this event . IRF8 is required for the development of monocytes , macrophages , dendritic cells ( DCs ) , basophils , and eosinophils , while it inhibits the generation of neutrophils [21] , yet nothing has been described for its role in keratinocytes . We observed no difference in gene or protein expression of IRF8 in primary human keratinocytes vs . 16E6 or E7 transduced cells ( S3B Fig ) . Furthermore , by ChIP we observed in human macrophages IRF8 binding on the ISRE element , however in human keratinocytes we failed to demonstrate binding ( S2C Fig ) . We concluded that IRF8 did not regulate the IL-1β promoter in human keratinocytes . In contrast to most IRFs , IRF6 has no identified function in innate immunity but is essential for normal keratinocyte epidermal development and differentiation [22] . We hypothesized that IRF6 might be involved in IL-1β transcription . To test this we co-transfected the IL-1β promoter with IRF8 , IRF6 or pUNO expression vectors in HEK293 cells . As expected , IRF8 induced a significant increase in IL-1β luciferase activity when compared to pUNO transfected cells ( Fig 5A ) . We also observed for the first time that IRF6 expression also increased IL-1β promoter activity in a dose dependent manner ( Fig 5A ) . Oligo pull-down assays revealed IRF6 as well as IRF8 specific binding to the ISRE site on the IL-1β promoter ( Fig 5B ) . Having established that IRF6 binds to the IL-1β promoter and induces IL-1β transcription , we hypothesized that 16E6 might alter IRF6 expression . Indeed , IRF6 expression in human keratinocytes was decreased in cells expressing 16E6 ( Fig 5C and 5D ) . Furthermore , immunofluorescence detection of IRF6 in primary keratinocytes was localized in the nucleus but shifted into the cytoplasm in 16E6 cells ( Fig 5E ) . ImageJ analysis of IRF6 fluorescence showed that both cytoplasmic and nuclear levels were reduced in keratinocytes expressing 16E6 ( Fig 5E ) . Furthermore , both mRNA and protein levels for IRF6 were lower in CaSki ( HPV16+ ) versus NIKs ( Fig 5F and 5G ) . siRNA targeting of 16E6 reversed the effect , and IRF6 levels were resorted ( Fig 5H ) . We also observed that IRF6 protein levels and mRNA levels were reduced when epithelial cells were treated with increasing amounts of 16QsV ( Fig 5I and 5J ) . The decrease of IRF6 mRNA levels was inversely proportional to viral DNA expression of E7 ( Fig 5J ) . ChIP assays revealed that IRF6 bound less to the ISRE element when cells were infected with 16QsV ( Fig 5K ) . In summary , we confirmed that IRF8 is required to induce IL-1β expression in monocytes , yet in human keratinocytes IRF6 regulates IL-1β transcription . Furthermore , IRF6 binding to the ISRE site on the IL-1β promoter is inhibited by 16E6 expression in primary human keratinocytes . The HPV16 oncoprotein E6 interacts with numerous proteins by hijacking several host cellular networks . To gain further insight into the mechanistic role of 16E6 on IL-1β transcription , we co-transfected the IL-1β promoter with plasmid constructs that contain point mutations that alter E6 binding to cellular host proteins [23 , 24 , 25 , 26 , 27 , 28] ( S4A and S4B Fig and Fig 6A ) . We then co-transfected increasing amounts of 16E6 WT or mutations with the IL-1β promoter ( Fig 6A and 6B ) . IL-1β luciferase activity was restored with the 16E6F47RdelPBM mutant and partial restored with delPBM and 4C/4S K11E . These data indicated that the 16E6F47R mutation , which fully disrupts its ability to degrade p53 [23 , 28] can no longer block IL-1β transcription . These data suggest that p53 also regulates IL-1β transcription ( Fig 6A and 6B ) . We next explored the role of p53 on IL-1β transcription . We suppressed p53 expression in primary human keratinocytes using the CRISPR/CAS9 technology ( Fig 6C ) . Suppression of p53 led to a decrease in IL-1β and IRF6 transcription ( Fig 6C ) . Blocking 16E6 mediated E6AP proteosome degradation of p53 using a siRNA for E6AP restored p53 protein levels as well as IL-1β and IRF6 mRNA expression ( S4C Fig and Fig 6D ) . Over expression of p53 restored IL-1β promoter activity in the presence of 16E6 ( Fig 6E ) . In addition , overexpression of p53 or IRF6 expression in keratinocytes transduced with 16E6 also reconstituted pro-IL-1β protein levels ( Fig 6E ) . Taken together , these data show that 16E6 degradation of p53 is required to inhibit IL-1β transcription . So far we have shown that both IRF6 and/or p53 regulate IL-1β transcription and that both proteins are blocked by 16E6 . Whether both proteins independently or dependently control IL-1β transcription remained to be determined . IRF6 transcription was no longer inhibited when cells transiently expressed 16E6 mutations that altered p53 degradation ( Fig 7A ) . Based on these data we hypothesized that p53 regulates IRF6 transcription . Indeed , using the gene card software , we identified a p53 cis element on the IRF6 promoter . We , therefore , performed ChIP experiments in human primary keratinocytes ±16E6 to determine if p53 was able to bind to the IRF6 promoter ( Fig 7B ) . We observed that p53 bound to the cis element on the IRF6 promoter in human keratinocytes ( Fig 7C and 7D ) . Occupation of this site was reduced in 16E6 expressing cells ( Fig 7C and 7D ) . In summary we demonstrated the existence of a negative feedback loop in which 16E6 degradation of p53 prevented the transcription of IRF6 and the subsequent transcription of IL-1β . Our next approach was to validate our in vitro findings in patients with cervical cancer . ( HPV16 + ) . Cervical cancer and matched normal tissue biopsies were taken from 6 patients and snap frozen . After analysis and HPV typing , sections were stained by immunofluorescence for IL-1β as well as p53 . Basal cells of the normal epidermis showed strong cytoplasmic staining for IL-1β and nuclear staining for p53 ( Fig 8A ) . No staining for IL-1β and p53 was observed in tumour cells ( representative staining in Fig 8A ) . Quantification of the cytoplasmic staining clearly showed that IL-1β expression was strongly down-regulated in cancerous compared to normal tissue ( Fig 8A ) . We next wanted to determine if IL-1β and IRF6 transcripts were down regulated in cervical cancer patients . To do this we used a larger cohort from normal ( 29 patients ) and cervical tumor biopsies ( 29 patients ) and RNA was extracted . RT-qPCR of IRF6 and IL-1β transcripts revealed that both genes were reduced in tumor tissues compared to normal biopsies ( Fig 8B ) . Cervical intraepithelial neoplasia ( CIN ) is the premalignant abnormal growth of squamous cells on the surface of the cervix . Most cases of CIN remain stable , or are eliminated by the host’s immune system without intervention . We next explored if IL-1β and IRF6 transcription were altered in patients during the progression of CIN positive for HPV16 . We obtained Formalin-Fixed Paraffin-Embedded biopsies from normal cervical tissues ( n = 4 ) as well as HPV16-positive CINI ( n = 8 ) , II ( n = 8 ) and III ( n = 5; Fig 8C ) . Immunohistochemical staining of normal cervical tissue revealed high nuclear expression of IRF6 in the basal layers; which decreased as CIN status increased ( Fig 8C and 8D ) . We observed a decrease in both IRF6 and IL-1β mRNA during disease progression , ( Fig 8E ) . ChIP experiments using chromatin extracted from patient tissue revealed that IRF6 binding to the ISRE site on the IL-1β promoter decreased during CIN severity ( Fig 8F ) , indicating that loss of IRF6 inversely correlates with cervical neoplasia progression . Furthermore , p53 binding was observed in normal cervical biopsies , but binding was reduced in patients with cervical tumors ( Fig 9 ) . These data strongly suggest that the p53/IRF6 regulation of IL-1β transcription is lost during CIN disease stages that could lead to cervical cancer .
We showed that human keratinocytes produce IL-1β when exposed to 16QsV . Furthermore , addition of recombinant IL-1β on 16QsV infected keratinocytes led to a block in viral gene transcription . Viral gene transcription was restored in the presence of an antagonist for the IL-1 receptor . More importantly we delineated that IL-1β gene transcription increased when exposed to 16QsV . These data show that HPV16 stimulates IL-1β secretion that has an anti-viral effect on infected cells . IL-1β depends on inflammasome activation; we have data showing that 16QsV was not sensed by NLPR3 or AIM2 ( S5A Fig ) . Bone marrow derived macrophages from NLRP3 and AIM2 knock out mice were still able to produce IL-1β in the presence of 16QsV ( S5A Fig ) . Therefore we still need to elucidate which innate-inflammasome sensor can detect 16QsV . However IL-1β gene expression began to decrease post 8h infection with 16QsV . These data implicate that HPV16 has developed an escape mechanism to block IL-1β production . Our findings are summarised in Fig 10 . Characterizing how HPV blocks immune surveillance is central in understanding the events involved in the establishment of head and neck as well as cervical cancers . In this study we showed the loss of IL-1β transcription was mediated mainly by oncoprotein 16E6 . Our data are in line with Karim et al . , showing that IL-1β mRNA levels were decreased in epithelial cells expressing 16E6E7 [29] . The addition of 16QsV , or expression of E6 alone , blocked IRF6 expression and binding to the ISRE site on the IL-1β promoter . IRF6 has previously been shown to play an important role in the embryonal development of the craniofacial region . Mutations in this gene have been found in two human syndromes: Van der Woude and Popliteal Pterygium Syndrome , which are characterized by the cleft palate , lip pits , skin webbings , syndactyly , genital deformities and oral adhesions . In contrast to most IRFs shown to be essential in IFN gene regulation , IRF6 had no identified function in innate immune gene activation . Other IRF family members have been shown to be hijacked during HPV mediated carcinogenesis , such as IRF1 [30] . We demonstrated that mutation of the ISRE site on the IL-1β promoter prevented 16E6 to inhibit IL-1β promotor activity . Gene silencing of the viral oncoproteins 16E6E7 or 16E6 , restored IRF6 and IL-1β expression in human keratinocytes . This was shown by calculating the percentage of 16E6 inhibition against the cells that are induced with the PLXSN vector alone ( S5B Fig ) . Furthermore we showed that p53 regulated IRF6 transcription . Using 16E6 mutations that cannot , partially or fully degrade p53 allowed us to correlate the degradation of p53 by 16E6 led to the loss of IRF6 transcription ( Fig 10 ) . p53 has also been shown to amplify intracellular IFN responses . IFN-stimulated genes ( ISG ) promoters do not contain p53 consensus binding sites . However Munoz-Fontela et al . , identified IFN regulatory factor 9 ( IRF9 ) , a component of the ISG factor 3 ( ISGF3 ) complex , as a p53 target gene . ISGF3 directly induces the expression of ISRE-containing genes and could represent a mechanistic link between p53 and ISG induction [31] . Several additional IFN-stimulated mediators of ISG expression , including IFN regulatory factor 5 ( IRF5 ) , immune-stimulated gene 15 ( ISG15 ) and the Toll-like receptor 3 ( TLR3 ) , have been identified as direct p53 target genes . Therefore IRFs and p53 play a central role in regulating innate immune responses . To our knowledge , this is the first description of p53-IRF6 axis mediating differential regulation of an immune gene . Our ChIP experiments showed that lack of p53 protein due to 16E6 prevented its recruitment to the IRF6 promoter in cervical cancer patients . Based on our findings we hypothesized that loss of IRF6 and IL-1β expression favours cervical cancer development . These data were corroborated in cervical neoplasia and tumours . In cohorts of cervical neoplastic patients we observed a decrease in both IL-1β and IRF6 mRNA levels . Rotondo et al . , evaluated the gene expression changes involved in neoplastic progression of cervical intraepithelial neoplasia compared to normal keratinocytes [32] . Microarray analysis revealed that IRF6 was one of the 24 genes significantly down regulated during CIN progression [32] . Furthermore two independent studies showed that IRF6 gene mutations were associated to head and neck squamous cell carcinomas [33] [34] . However these scientific findings conflict with two other data sets . Our analysis of the data set by den Boon et al . , showed that IL-1β was not affected during cervical cancer progression [35] . Also neither IRF6 nor IL-1β mRNA levels were suppressed when analysing the data set from the TCGA cervical carcinoma cohort [36] . One should consider that neither studies were hypothesis driven nor were the data sets designed to examine the mechanism of HPV16E6 regulation on p53/IRF6/IL-1β . We validated that IRF6 and IL-1β expression were altered by the viral oncoprotein 16E6 using several read-outs and models . Furthermore , we showed that IL-8 gene transcription depends on IL-1β stimulation . An increase in local cervical IL-8 levels correlates with HPV viral clearance [37] . Experts in HPV incidence have discussed that infection of the cervical epithelium is a prerequisite for the development of cervical cancer and the local immune response is an important determinant of progression and disease outcome [38] . The transiency of most HPV infections and the observed regression of certain cervical intraepithelial neoplasia lesions to normal epithelium suggest a change in local immune responses , which may be caused by differences in host genomics . We observed that loss of IL-1β production in cervical cancer cells led to a loss of paracrine IL-8 transcription . Furthermore , IL-1β down regulation in HPV induced carcinogenesis is underlined by the fact that specific polymorphisms in IL-1β have been demonstrated to be associated with cervical carcinoma risk [38] . The work of Niebler et al . , showed that 16E6 alters IL-1β by proteosome degradation of the pro-form [8] . We did not observe the same findings using our cellular models . This could be due to the fact that the primary keratinocytes used by Niebler et al . , were from neonatal foreskin , whereas our model used keratinocytes from adult female skin ( see Method and materials ) . Yet , Niebler et al . , also showed in Fig 6 of their article a drop in mRNA IL-1β levels in CIN patients [8] . These data fall in line with our findings . We propose that inflammasome activation of IL-1β secretion favors’ HPV viral clearance . Loss of IRF6 and IL-1β function during cervical neoplastic stages reflects a prognostic read out towards cancer development . Thus , interfering with the regulation of IL-1β with synthetic agonists that target p53 and IRF6 levels may provide a novel therapeutic strategy for cervical cancer patients .
Cervical cancer cell lines C33A ( HPV negative cat: HTB-31 ) , SiHa ( HPV16 positive cat: HTB-35 ) , CaSki ( HPV16 positive cat: CRL-1550 ) , HeLa ( HPV18 positive cat: CCL-2 ) and Human embryonic kidney 293 ( HEK293 cat: CRL-1573 ) cells were purchased from American Type Culture Collection ( Manassas , VA ) and cultured in DMEM medium ( Life technologies ) , supplemented with 10% foetal bovine serum ( FBS ) , L-glutamine , pyruvate and 0 . 1% ciprofloxacin ( Euromedex ) . HEK293TT cells were a kind gift from the lab of Dr . Pawlita ( DKFZ , Germany ) . Cells were cultured with hygromycin using the same culture medium as HEK293 . When preparing HEK293TT cells for transfection cells were grown without hygromycin and antibiotics . Cells were cultured at 37°C with 5% CO2 . Immortalized near-diploid human keratinocyte cell line ( NIKS , kind gift from Professor John Doorbar , University of Cambridge , UK ) and Human Primary Keratinocytes produced by the lab of Massimo Tommasino were from Adult female , or femaile skin keraintocytes were purchased from American Type Culture Collection Cat: PCS-200-011 ) . Cells were cultured as previously described [6] . Human Primary Keratinocytes were cultivated at low passages numbers for a period of 3 weeks ( called keratinocytes after 1 passage ) . High-titer retroviral supernatants ( >5 × 106 IU/ml ) were generated as previously described [39] . The 16QsV and PV production , infection , and viral genome expression quantification of HPV16 are described below . NLRP3 ligand Nigericin was used at 1μg/mL ( Sigma ) , AIM2 ligand poly ( dA:dT ) was used at 1μg/well ( Invivogen ) and transfected using lipofectamine 2000 ( Invitrogen ) . ANAKINRA ( Biovitrum ) was used at 200μg/ml . Oligo pulldown was performed as previously described [40] with cellular extracts as stated in the figure legend and oligo probes as listed in Table 1 . IRF8 and IRF6 antibodies were purchased from Cell Signaling . ChIP assays were performed using the Shearing Optimization kit and the OneDay ChIP kit ( Diagenode ) . For C33A cells or primary keratinocytes , cell sonication cycles last 15s with 5s on and 2 s off at 20% of amplitude and were repeated four times . For tissue , immunoprecipitation was performed overnight on a rotating wheel at 4°C . 2 . 5 μl/reaction of DNA solution was used for qPCR . The primers used to amplify IL-1β , or IRF6 binding regions are available on request . ChIP on the tissue was performed according to the protocol from Epigenome Network of Excellence for tissue preparation after the Red ChIP kit from diagenode was used to prepare chromatin and the 1-d ChIP kit for the immunoprecipitation . Immunoprecipitation was performed overnight on a rotating wheel at 4°C . 2 . 5 μl/reaction of DNA solution was used for qPCR . The constructs pLXSN empty , pLXSN-16E6E7 , pLXSN-HPV16E6 , pLXSN-HPV16E7 and pLXSN-HPV18E6E7 were obtained from M . Tommasino ( IARC , Lyon , France ) ( 6 ) . The pGL3 Luc vector was purchased from Promega . The constructs The full-length IL-1β-Luc , LILRE ( IL-1 response element ) and mutants were obtained from Philip E . Auron ( University of Pittsburgh , Pittsburgh , PA 15261 , USA ) . IL-1β deletions were cloned using the primers listed in Table 1 . Nine E6 mutations were obtained from Dr Gilles Trave ( CNRS , Illkirch , France ) ; and previously described . These mutations were cloned into the pX5 plasmid . The retroviral pBabe-puro encoding HPV16 and 6 E6 and or E7 have been previously described [41] . The constructs pLXSN-HPV16 E6 , HPV18 and HPV38 E6 and HPV6 E6 were a gift from D . Galloway ( Fred Hutchinson Cancer Research Center , Seattle , WA ) . The plasmids used for HPV16 structural genes and control PsV production , the target HPV16 genome , and GFP ( for PsV control ) were kindly donated from the laboratories of Martin Muller and Angel Alonso ( DKFZ , Germany ) . pUNO , human IRF6 and IRF8 constructs were purchased from Invivogen . The p53 plasmid was obtained from Addgene . siRNA for 16E6E7 and E6 was purchased from Dharmacon and Sigma respectively . siRNA for E6AP [42]CRISPR for p53 was purchased from Santa Cruz . 16QsV are viral particles that contain the full viral genome of HPV16 encaspidated by the viral late proteins L1 and L2 . PsV contain GFP DNA encaspidated by L1 and L2 . 293TT cells at 75% confluency the day of transfection . The transfection mix consisted of 13μg of the L1-L2 expression vector and ~ the same amount of HPV16DNA or GFP control vector were prepared in a separate tube , a mix 85μl of Lipofectamine with 2ml OptiMEM . Both mixtures were incubated separately at RT for 10´-30´ , then combined and incubated for at least another 20 minutes . The resulting lipid/DNA complexes were directly added to the pre-plated cells . The cells were incubated with the transfection mix for 4–6 h then split 1:2 or 1:3 and left overnight . The next day cells were detached , spun down and the supernatant discarded . Cell lysis and Capsid Maturation: Using a 5ml plastic pipet , cells were suspended in 0 . 5ml in DPBS-Mg and transferred to a siliconized 2ml tube , screw-capped ( Nalgene tubes for freezing cells ) . For 100 million cells 1 ml of lysis buffer was prepared and incubated for 1-2h at 37C then with inversion for a further 16 h at least at 37C . The next day optiprep gradients prepared were diffused for 4 hours . The lysate was then layered on top of the gradient . The tubes were spun for using 13 . 2ml tubes SW40 . 1 Ti 14 h at 16 C . The L1 band is a visible as a slight grey layer a little over a third of the gradient . Using a large needle and a 5ml syringe we removed the 60% cushion layer , then we tool a 1 . 0ml syringe and 26 gauge needle to extract 250μl fractions ( 6–8 fractions ) . Each fraction was placed into a screw cap tube ( not freezing tubes ) . Screen fractions by SDS PAGE: A mini gel of 10% were used to screen fractions for the presence of the L1 protein ( 55kDa ) fractions with significant amounts of L1 were pooled , aliquoted and frozen; the protein yield can be estimated through BSA standards or BCA assay . Analysis of virions- Encapsidated DNA: Fifty μl of fractions were run on a 0 , 8% agarose gel . Supercoiled DNA from the HPV genome , linear human DNA with nucleases and exonuclease treatment captured by L1 and L2 will run at 8Kb . *nuclease should cut up all the human genomic DNA , then any tailed DNA that gets incorporated into the capsid were cut off with the exonucleases . Capsid protein levels: Capsid protein levels ( 20μl fractions ) were measured on 10% SDS-PAGE and silver staining with serially diluted BSA as concentration standard or by western blotting for L1 . Viral genome equivalents were measured by qPCR on the viral DNA of infected HEK293T cells using W-12 cell lysates as a standard ( kind gift from Dr Franck . Stubenrauch , Forschungssektion Experimentelle Virologie , Tubingen , Germany ) . Our cohort of normal , CIN and tumor samples was provided by the hospital in Lyon Sud , Lyon , France . Samples were obtained with written informed consent from each patient with the procedure approved by the local Ethics Committee , Comités de Protection des Personnes . All , normal , CIN or tumor biopsies were from females aged between 30–50 years . Where available the same normal patient-matched samples were provided ( HPV negative genotyped using multiplex PCR with HPV type-specific primers ) . Biopsies were either snap frozen or FPPE . CIN and Tumor samples were genotyped using multiplex PCR with HPV type-specific primers for amplification of viral DNA and array primer extension for typing [41] . NIKs or primary keratinocytes were infected with packaged viruses as stated in the figure legends at 37C . Cells were removed , and RNA extracted for RT-PCR for E1 , E6 and E7 transcripts ( mRNA ) or DNA to measure viral DNA expression for E7 [6] . Keratinocytes transduced with pLXSN or HPV16E6 were fixed as previously described [45] . Sections of 5-μm thickness were cut and either stained for immunofluorescence using the TSA system ( PerkinElmer ) . The p53 antibody was purchased from Cell Signaling and the anti-IL1β 3ZD ( kindly provided by Dr . Trinchieri , NCI ) . The IRF6 antibody ( F12 ) was purchased from Santa Cruz . Cells or tissues were washed , the coverslips were mounted onto slides using a 1/10 dilution of 4′ , 6′-diamidino-2-phenylindole ( nuclear stain; Invitrogen ) in fluoromount ( Southern Biotechnology Associates ) , and protein expression was detected by direct fluorescence microscopy . Photographs were taken at magnification x40 using the Zeiss confocal 710 microscope . Semi-quantitative analysis of IRF6 levels was estimated using the ImageJ software . Immunohistochemistry staining for IRF6 was performed as previously described [6] . NIK , primary keratinocytes , HPV16E6 and E7 induced keratinocytes were seeded into a six-well plate with 2 . 5 x105 cells per well with 4x103 NIH 3T3 feeders . Two days later the feeders were removed , and the medium was replaced . After two hours; keratinocytes were stimulated either with 20μM of Nigericin ( Sigma ) or transfected with 1ug/mL of poly ( dA:dT ) ( Invivogen ) using lipofectamine 2000 ( Invitrogen ) . After the indicated period ( see figure legend ) , the supernatant was harvested and quantified for IL-1β by ELISA ( Bender Med System ) or IL-18 [46] . Twenty-four hours before transfection HEK293 cells were plated at 20% of confluency in 96 well plates with 180μl of complete medium per well . Cells were transfected using GeneJuice Transfection Reagent ( Novagen ) following the manufacturer’s instructions . Cells were transiently co-transfected with HPV constructs as indicated with pGL3-LILRE , mutants or pGL3-XTLuc . A Renilla plasmid with a CMV promoter was used to normalize transfection efficiency . Twenty-four hours after transfection cells were lysed at room temperature in passive lysis buffer ( Promega ) for 20 minutes . Luciferase buffer was composed of MgSO4 ( 2 , 67mM ) , EDTA pH8 ( 0 . 1 mM ) , DTT ( 33 . 3 mM ) , ATP ( 0 . 53 mM ) , acetyl-CoA ( 207 μg/ml ) , luciferin ( 0 . 13 mg/ml ) , Magnesium carbonate hydroxide ( 0 , 265 mM ) and tricine ( 20 mM ) . Renilla buffer was made by diluting coelenterazine . Luciferase and renilla activity from transfected cells were measured using a luminoskan Ascent ( Thermo ) . A single read program with an integration time of 1000 ms was used . Firefly luciferase ( Photinuspyralis ) activity of individual cell lysates was normalized against renilla ( Renillareniformis ) activity to correct for transfection efficiency in each reaction . Supernatants from stimulated cells were added onto HEK 293 cells transfected with IL-8 luciferase promoter , and a Renilla plasmid with a CMV promoter was used to normalise transfection efficiency [47] . Twenty-four post stimulation cells were processed as listed above . Cells were preserved in RP1 lysis buffer complemented with β-mercaptoethanol ( 1% ) until RNA and total proteins extraction using the NucleoSpin RNA/protein extraction kit ( Macherey-Nagel ) . Supernatants from stimulated cells where concentrated using MeOH/chloroform . All RNA samples were treated with DNAse before reverse transcription was performed . Eighteen μg of total cellular protein were incubated during 5 minutes at 95°C . The protein samples were separated by electrophoresis using Novex 4–20% Tris-Glycine gels ( Life Technologies ) for 1 hour at 100V . Proteins then were transferred on a PVDF membrane ( PerkinElmer ) during 1 hour at 100V . After blocking with PBS 0 . 1% tween and 5% milk for 1 hour , membranes were probed with the following primary antibodies: anti-caspase 1 P10 ( SantaCruz Biotechnology ) , anti-IL1β 3ZD ( kindly provided by Dr Trinchieri , NCI ) , anti-ASC ( Santa Cruz Biotechnology ) , 16E6 ( provided by the lab of Dr Trave ( GBMC , France ) and 16E7 ( Santa Cruz , France ) over night at 4°C . β-actin ( Sigma ) primary antibodies were added for 2h at RT . After three PBS 0 . 1% tween washes , secondary antibodies are added for two hours at RT . Anti-Rabbit and anti-mouse HRP conjugate secondary antibodies were provided by Promega . Proteins were revealed with Lumiglo chemiluminescent substrate system ( Kpl ) . Western blots were developed using the intelligent dark box ( Fuji film ) . We retro transcribed ( RT ) 1–1 . 5 μg of RNA extracted from cells using first strand RT-PCR kit with oligodT primers ( Fermentas ) . The RT reaction was diluted according to detection sensitivity . One μl of the diluted samples was added to a 20 μl PCR mixture containing 0 . 4 μl of primers forward and reverse ( 10 μM ) and 10 μl of Master Mix . Mx300P real-time PCR system ( Stratagene , La Jolla , CA ) were used to performed qPCR with Mesa Green qPCR Master Mix Plus ( Eurogentec ) on CaSki , C33A and SiHa cells . Primer sequences designed to detect gene expression of AIM2 , NLRP3 , ASC , IL-1β , house-keeping β2-microglubulin and GADPDH are listed as previously described [46] . As relative levels of house-keeping genes between samples did not alter , data were plotted against GAPDH . Primers for IRF6 , IRF8 , and p53 are listed in Table 1 . Where appropriate , anova , unpaired or paired T test were performed using prism software version 6 ( Graph Pad ) Statistical studies were validated by Omran Allatif ( Statistician CIRI , Lyon , France[46 , 48] ) . | Oncoviruses block innate immune responses to persist in the host . However , to avoid viral persistence , the immune response attempts to clear the infection . IL-1β is a pro-inflammatory cytokine produced by the inflammasome pathway . Whether oncoviruses such as human papillomavirus ( HPV ) can activate the inflammasome remains to be explored . We demonstrated that keratinocytes , the host cell type for papillomaviruses , when infected with HPV16 induced IL-1β transcription and secretion . Yet , upon expression of the viral oncoprotein E6 , IL-1β transcription was blocked . E6 expression inhibited IRF6 transcriptional regulation of the IL-1β promoter . Preventing E6 expression , or its ability to degrade p53 , restored the ability of IRF6 to bind to the IL-1β promoter . HPV16 abrogation of p53 , IRF6 and IL-1β expression was fully confirmed in cervical cancer cells and tissues from patients . These data highlight the equilibrium between the host innate immune rheostat and viral immune escape . | [
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"organisms"
] | 2018 | Human papillomavirus type 16 antagonizes IRF6 regulation of IL-1β |
A challenge for hepatitis C virus ( HCV ) vaccine development is to define epitopes that are able to elicit protective antibodies against this highly diverse virus . The E2 glycoprotein region located at residues 412–423 is conserved and antibodies to 412–423 have broadly neutralizing activities . However , an adaptive mutation , N417S , is associated with a glycan shift in a variant that cannot be neutralized by a murine but by human monoclonal antibodies ( HMAbs ) against 412–423 . To determine whether HCV escapes from these antibodies , we analyzed variants that emerged when cell culture infectious HCV virions ( HCVcc ) were passaged under increasing concentrations of a specific HMAb , HC33 . 1 . Multiple nonrandom escape pathways were identified . Two pathways occurred in the context of an N-glycan shift mutation at N417T . At low antibody concentrations , substitutions of two residues outside of the epitope , N434D and K610R , led to variants having improved in vitro viral fitness and reduced sensitivity to HC33 . 1 binding and neutralization . At moderate concentrations , a S419N mutation occurred within 412–423 in escape variants that have greatly reduced sensitivity to HC33 . 1 but compromised viral fitness . Importantly , the variants generated from these pathways differed in their stability . N434D and K610R-associated variants were stable and became dominant as the virions were passaged . The S419N mutation reverted back to N419S when immune pressure was reduced by removing HC33 . 1 . At high antibody concentrations , a mutation at L413I was observed in variants that were resistant to HC33 . 1 neutralization . Collectively , the combination of multiple escape pathways enabled the virus to persist under a wide range of antibody concentrations . Moreover , these findings pose a different challenge to vaccine development beyond the identification of highly conserved epitopes . It will be necessary for a vaccine to induce high potency antibodies that prevent the formation of escape variants , which can co-exist with lower potency or levels of neutralizing activities .
Infection with hepatitis C virus ( HCV ) is a leading cause of chronic hepatitis , cirrhosis and hepatocellular carcinoma . The World Health Organization estimates an annual increase in the global burden by 3–4 million new infections [1] . Encouragingly for patients , advances in in vitro and in vivo HCV infection systems and increased understanding of HCV virology have led to the development of many promising HCV-specific direct acting antivirals ( DAA ) [2]–[6] . However , the high costs of DAA will limit their access to the large majority of HCV infected patients living in countries with limited resources . There is clearly a need for a preventive HCV vaccine . Humoral immunity is the primary correlate of protection for most preventive vaccines , as shown for smallpox and other DNA viruses . For HCV , cumulative evidence supports the importance of virus neutralizing antibodies to facilitate clearance . Chimpanzee studies showed that protection from an infectious HCV inoculum is correlated with HCV-specific antibody titers blocking infection of target cells with pseudotyped retroviral particles expressing HCV E1E2 glycoproteins ( HCVpp ) [7] . Neutralizing antibody response measured via HCVpp has been associated with control of infection in single source outbreaks of acute HCV infections [8] , [9] , and in a study of active injection drug users ( IDUs ) [10] . While only 25% of IDUs in this study cleared primary HCV infection , 83% cleared subsequent re-infection episodes , and clearance was associated with cross-reactive neutralizing antibodies . In addition , antibodies to HCV E2 prevent infection in a human liver-mouse chimeric model [11] , [12] . Finally , an immunocompetent humanized mouse model for HCV exhibited a robust antibody response to a recombinant vaccinia virus expressing HCV proteins that protected against an infectious HCV challenge in some animals that correlated with the serum level of E2 antibodies [13] . A key challenge for vaccine design is to overcome the genetic diversity of the virus . This will require information on conserved epitopes mediating virus neutralization and on the mechanisms of HCV escape from the humoral immune response . HCV is a positive-strand RNA virus encoding a polyprotein that undergoes proteolytic cleavage to 10 polypeptides , each with distinct functions . The two envelope glycoproteins , E1 and E2 , form a heterodimer that mediates viral entry [14]–[16] through interactions with cellular receptors ( reviewed in [17] ) , and are the natural targets for neutralizing antibodies . Both proteins are highly glycosylated that partly shields the virus from neutralizing antibodies [18]–[21] . The genes encoding E1 and E2 are the most variable in the HCV genome . The hypervariable region one ( HVR1 ) in E2 is immunodominant and infected individuals develop isolate-specific neutralizing antibodies against this region throughout the course of their infections [22] , [23] . These antibodies provide little protection since the HVR1 sequence continuously evolves in response to pressure exerted by HVR1-specific neutralizing antibodies leading to viral escape [23] , [24] . An effective HCV vaccine will need to include conserved epitopes that are able to elicit broadly neutralizing antibodies . Much effort has been devoted to the identification of conserved regions mediating virus neutralization through the isolation and characterization of human monoclonal antibodies ( HMAbs ) from the B cells of HCV-infected individuals and of murine monoclonal antibodies from recombinant E2 glycoprotein immunized mice . The focus has been primarily on E2 since this viral structure interacts with HCV co-receptors and is more immunogenic than E1 . Studies with HMAbs to E2 have led to the delineation of at least six distinct clusters of overlapping linear and nonlinear epitopes , designated as antigenic domains A-E [25]–[28] . Many of these HMAbs from different laboratories are to overlapping epitopes , which can be grouped in one cluster , antigenic domain B . Of concern , some domain B antibodies do not neutralize all HCV genotypes , which is indicative of escape [29] . Single amino acid substitutions also can lead to viral escape with other domain B antibodies [30] , [31] , similar to escape from antibodies against the HVR1 [24] . There are three patterns of viral escape that are observed when infectious cell culture virions ( HCVcc ) are grown in the presence of neutralizing domain B antibodies [32] . Of the three tested domain B HMAbs , one led to escape mutant viruses without affecting in vitro viral fitness; a second led to escape but with compromised viral fitness; and a third led to complete virus elimination at a critical antibody concentration without escape mutants . Sequence analysis of escape mutants revealed a conserved region , amino acid ( aa ) 529–535 , and a region , aa 425–443 , on E2 that appears to be associated with escape mutations [32] . Immediately downstream of HVR1 is a cluster of overlapping linear epitopes that are highly conserved across all HCV genotypes and subtypes , encompassing aa 412–423 , but are of low immunogenicity in population studies [33] , [34] . A number of broadly neutralizing monoclonal antibodies targeting this region have been isolated from experimentally immunized mice [16] , [35]–[37] and a human monoclonal antibody , designated as HCV1 , in a transgenic mouse [38] . Their precise contact residues have been resolved by direct crystal structure of E2 peptides in complex with two of these antibodies , AP33 and HCV1 [39]–[41] . Other studies have also established that this region is involved in virus binding to the HCV co-receptor , CD81 [37] , [42] , which explains why this region is highly conserved in order to preserve essential viral functions . Thus , antibodies to this region have held great promise for immunotherapy and vaccine development . However , the Asn at 417 is an N-linked glycosylation site that shields this conserved region from being fully exposed to neutralizing antibodies by reducing epitope access [18]–[21] . An adaptive mutation N417S that leads to a glycan shift upstream to N415 blocks virus neutralization by AP33 and HCV1 [43]–[45] . The N-glycan shift at N417 occurs frequently in passaged HCVcc . The shift occurs in the absence of selection by neutralizing antibodies targeting this region , in the presence of neutralizing antibodies targeting different regions or in the presence of a non-HCV HMAb [28] , [32] . We recently isolated a panel of HMAbs to aa 412–423 [25] . Surprisingly , cell culture adapted 2a JFH1 HCVcc , containing mostly glycan shifted HCVcc at N417S and a minor population of wild-type ( wt ) HCVcc , displayed an increased sensitivity to neutralization by these HMAbs , in contrast to the lack of neutralization by a murine monoclonal antibody . This raised questions whether and how HCV can escape from human antibodies directed against aa 412–423 , particularly because the mutation leading to an N-glycan shift from 417 to 415 does not lead to viral escape , but to an increase in sensitivity to these antibodies . This report addresses these questions by assessing viral evolution in the presence of a HMAb against aa 412–423 , designated as HC33 . 1 . Sequence analyses of variants obtained at different time points when 2a HCVcc was co-cultured with HC33 . 1 , from low to high antibody concentrations , revealed multiple patterns of mutations . At low antibody concentrations , mutations occurred outside of aa 412–423 in combination with an N-glycan shift mutation at N417T . These variants exhibited improved viral fitness and reduced sensitivity to HC33 . 1 binding and neutralization . At moderate antibody concentrations , a mutation was observed within the conserved aa 412–423 region at residue 419 in escape variants having compromised fitness and greater reduction in sensitivity to HC33 . 1 . Interestingly , when HC33 . 1 was removed , the 419 mutation-associated variants rapidly disappeared and the variants that emerged contained the wild-type residue at this position . At high antibody concentrations , a mutation at 413 was observed in variants that were completely resistant to HC33 . 1 neutralization . Taken together , multiple pathways are involved in viral escape from a single antibody that appear to be concentration dependent , and associated with and without compromised in vitro viral fitness in escape variants .
Employing AP33 as the prototype antibody to this region [16] , [35]–[37] , [43] , epitope mapping of this and three HMAbs to aa 412–423 , HC33 . 1 , HC33 . 4 and HC33 . 8 ( designated as antigenic domain E ) , revealed shared contact residues at L413 , G418 and W420 , as determined by <20% binding to a panel of alanine substitution H77C E1E2 mutants ( Fig . 1A ) [25] . No contact residues were identified between aa 425–443 with the HC33 HMAbs ( data not shown ) . They differed at residue 415 , in which a N415A mutation led to AP33 binding reduction of 73% and the HC33 HMAbs having no binding reduction . To define the different neutralization profiles of AP33 and HC33 HMAbs against glycan shifted HCVcc variants , JFH1 E1E2 plasmids were constructed to contain N417S or N417T . The N417S mutation has been shown to be an adaptive mutation [45] and the N417T change was observed in the HC33 . 1 selection studies ( see below ) . Both substitutions resulted in an N-glycan shift from residue 417 to N415 . Wild type and variant HCVcc bearing N417S or N417T were produced , and dose-dependent neutralization was measured with AP33 and the three antigenic domain E HMAbs ( Fig . 1B–1D ) . AP33 and HC33 . 1 neutralized wt HCVcc , which was poorly neutralized by HC33 . 4 and HC33 . 8 ( Fig . 1B ) . AP33 had a higher potency ( IC50 at 3 . 5 µg/ml ) than HC33 . 1 ( IC50 at 12 . 5 µg/ml ) ( Fig . 1F ) . The data is consistent with previous findings of AP33 having high neutralizing potencies against different HCV genotypes [37] . In contrast , AP33 ( up to 50 µg/ml ) failed to neutralize the N417S and N417T HCVcc variants ( Fig . 1C , 1D and 1F ) ; whereas these variants remained sensitive to HC33 . 1 , HC33 . 4 and HC33 . 8 . The neutralization potencies of the three domain E antibodies significantly improved and their IC50 values ranged 0 . 9 to 21 . 2 µg/ml . HC33 . 1 IC50 improved by over tenfold against both N417S/T variants compared to wt HCVcc . Of note is that the contact residues for the HCV1 HMAb , isolated from a transgenic mouse that was challenged with recombinant E2 proteins , are similar to the HC33 antibodies , involving 413 and 420 but with a 20 percent reduction at 418 [38] . Yet escape variants for HCV1 have been documented to include N417T/S mutations [44] , [46] . These results demonstrate the difference between previously isolated antibodies to aa 412–423 and the HC33 HMAbs that are elicited in response to viral infection undergoing an N-glycan shift from 417 to 415 . Moreover , the increased potencies of the antigenic domain E HMAbs to glycan shifted virions confirm the importance of the N-glycan at 417 in shielding aa 412–423 from neutralizing human antibodies [18]–[21] . The relative in vitro viral fitness of N417S and N417T HCVcc variants was compared to wt by determining the virus yield at a low multiplicity of infection ( MOI = 0 . 1 ) after 96 hours post infection . Both N417S ( 4 . 1 ) and N417T ( 3 . 7 ) had approximately four fold higher viral yields than wt HCVcc ( Fig . 1E ) . Statistical analysis found both N417S ( P = <0 . 040 ) and N417T ( P = <0 . 009 ) to be significantly higher than wt HCVcc . The increased fitness is in agreement with previous findings that the glycan shift associated with N417S is a spontaneous adaptive mutation that confers greater viral fitness [45] . However , the previous study found the increase to be statistically not significant ( P = <0 . 063; [45] ) . The P values between the two sets are marginally different and within experimental fluctuations . The findings also show that the residue at 417 is polymorphic , N417 , S417 or T417 , with the variants having advantages of greater in vitro viral fitness and resistant to neutralization to some antibodies to this region , e . g . , AP33 and HCV1 [44]–[46] . But this glycan shift leads to greater susceptibility to other human antibodies to aa 412–423 , and to antigenic domain B [45] . Escape from antibody-mediated virus neutralization occurs by mutations at contact residues within the cognate epitope of the virus neutralizing antibody [28] , [32] . However , alanine substitution at each of the three contact residues of HC33 . 1 at L413 , G418 or W420 completely abolished HCVpp infection [42] , suggesting that mutations at these contact residues probably will not be an escape mechanism from human antibodies to aa 412–423 on E2 . Either the virus cannot escape from antigenic domain E antibodies or that escape under immune selection pressure is by a different pathway . This was studied by an in vitro antibody-virus co-culture protocol that mimics the evolution of viral antigenic determinants under immune pressure in humans . The antibody-virus co-culture system with a 2a HCVcc isolate identified the same escape mutation for an antigenic domain B antibody as observed in an genotype 1a infected individual [28] , [30]–[32] . Similar findings have been reported with other escape mutations that are the same in co-culture studies with a different 2a HCVcc isolate and observed in clinical studies with HCV genotype 1a infected individuals [43] , [44] . Thus , we believe that antibody-virus co-culture systems identify escape variants that are broadly applicable to other genotypes/isolates . Extracellular JFH1 HCVcc was passaged in the presence of HC33 . 1 in increasing antibody concentrations . CBH-2 , an antigenic domain B HMAb , was used as a positive ( escape ) control and R04 , an isotype-matched HMAb to CMV was used as negative control . The expectation was that mutations at contact residues within the CBH-2 epitope would appear in escape variants from CBH-2 co-culture passaged virions . Any mutations that appeared in the R04 passaged virions would be considered as spontaneous mutations and would be ignored if they appeared in the variants from HC33 . 1 co-culture passages . At each passage of extracellular virus , infected cells were monitored for virus escape by screening with a two-color indirect immunofluorescence assay ( IFA ) that used both the test antibody , and a second antibody that recognized virus replication regardless of a change in envelope antigenicity ( Fig . 2A ) [28] , [32] . In this case , cells infected with an escape variant were detected by a decrease or a loss of specific binding by the test antibody , HC33 . 1 , but with retained binding by an anti-NS3 antibody . When escape was detected , RNA from escape variants was extracted from either cells or culture supernatants , reverse-transcribed , PCR amplified , and subcloned . Genomic residues 1491–2579 spanning the entire E2 coding region were sequenced from selected individual clones . The number of clones that were sequenced and analyzed ranged from 20 to 40 per sample . To ensure that newly released variants were transferred successfully to the next higher antibody concentration , repetitive passages of extracellular virions in the supernatant occurred at the lower antibody concentration until the percent of infected cells reached >80% . When passaged virions in supernatant resulted in >80% infected cells , the virus titers were usually >104 FFU/ml ( data not shown ) [28] , [32] . HCV genetic evolution under HC33 . 1 selection was analyzed and displayed after elimination of spontaneous mutations observed with R04 passaged virus ( Fig . 2B and 2C ) . The passage numbers shown in Fig . 2 represent the evolving viral population and those passages having similar distribution of variants were not shown . New variants were observed and can be roughly separated into four phases under increasing concentrations of HC33 . 1 . Because R04 has no effect on HCV , the concentration was raised rapidly and only 1–2 passages at each antibody concentration were needed to reach >80% infected cells . Spontaneous mutations located at V402A , N415D , N417S and F650Y were identified ( Table S1 ) , as previously reported , but with the addition of another mutation at 650 [28] . CBH-2 escape variants were isolated that contained the same mutations at two contact residues at 431 and 439 , as previously reported ( data not shown ) [28] , [32] . To prepare sufficient virus stock , 2a JFH1 HCVcc was passaged multiple times in Huh7 . 5 cells . The final virus stock ( P0 ) contained a mixture of wt ( 20% ) and the glycan shifted N417S variant ( 80% ) . Nearly 100% of Huh7 . 5 cells infected with this stock was stained strong positive ( +++ ) by both HC33 . 1 and anti-NS3 by IFA ( upper panels in Fig . 2A and 2B , P0 ) . Similar staining was observed with a control antigenic domain B antibody , CBH-5 [27] , [47] ( lower panels in Fig . 2A and 2B ) . Approximately 104 FFU/ml of this stock was co-cultured initially with 0 . 25 µg/ml HC33 . 1 and designated as P1 . After several passages of extracellular virions were collected from the supernatant , the percentage of infected cells was checked and found to be >80% . The antibody concentration was increased to 0 . 5 µg/ml and after three passages , at P6 , the percent infected cell was again >80% and stained +++ with both HC33 . 1 and anti-NS3 . Sequence analysis of extracellular virions revealed that the viral population shifted completely back to wt HCVcc with the glycan located at N417 ( Fig . 2B ) . The viral population remained essentially wt for the next three passages , P6–9 , as the antibody concentration increased to 1 . 0 µg/ml . The N-glycan shift from 415 back to 417 was a specific response to HC33 . 1 immune selection in that this change was not observed with the positive selection control , CBH-2 , nor with the isotype-matched negative control , HMAb R04 ( data not shown ) . Moreover , this is consistent with the greater sensitivity of the N417S variant to be neutralized by HC33 . 1 ( Fig . 1B and 1C ) that resulted in the re-emergence of wt HCVcc . When the antibody concentration increased from 1 . 5 to 4 . 5 µg/ml HC33 . 1 during P10–P19 , a modest decrease in HC33 . 1 binding from +++ to ++ was observed by IFA ( as shown for P18 , Fig . 2A and 2B ) . CBH-5 staining by IFA remained unchanged at +++ . Sequence analysis of extracellular virions at P10 ( Fig . 2B ) showed wt HCVcc decreasing to 30% and the appearance of four new variants , with each containing single or double mutations: N417T ( 40% ) , K610R ( 10% ) , N417S+K610R ( 10% ) or N417T+N434D ( 10% ) . Although an N-glycan shift at N417S or N417T increased viral sensitivity to HC33 . 1 ( Fig . 1B–D ) , the observed variants contained predominantly N417T-associated mutations as single , double or triple combinations with N434D and K610R . The following two passages , P12 and P13 ( Fig . 2B ) , showed that wt HCVcc declined further to 10% , while the variantN417T fluctuated between 20–40% . The most notable viral population change was the appearance of two new variants containing double or triple mutations , N417T+K610R or N417T+N434D+K610R , that replaced variantN417S+K610R and variantK610R . The triple mutation containing variantN417T+N434D+K610R emerged as the dominant strain from P14 to P19 . At P18 and P19 ( not shown ) , this variant accounted for 90% of the viral population ( Fig . 2B ) . Taken together , it is possible that the N434D and K610R mutations provided some degree of survival benefit to the virus in combination with N417T and not with N417S . The N434D and K610R mutations are outside of the HC33 . 1 epitope that is located at aa 412–423 on E2 . The increasing dominance of the triple mutation variantN417T+N434D+K610R indicates that a variant having a N417T change requires additional mutations to provide some degree of protection from the neutralizing antibody , since N417T alone leads to a variant that is more sensitive to neutralization by HC33 . 1 . During P20–P27 with concentrations of HC33 . 1 increasing from 5 to 6 . 0 µg/ml , the IFA intensity for HC33 . 1 binding decreased further from ++ to + , while CBH-5 staining remained +++ ( as shown for P27 , Fig . 2A and 2C ) . Sequence analysis showed two distinct changes . First , the triple mutation variantN417T+N434D+K610R declined from 90% at P20 to 20% at P25 and eliminated at P27 ( Fig . 2C ) . When HC33 . 1 increased from 5 µg/ml at P20 to 5 . 5 µg/ml at P21 , the infected cell percentage rapidly decreased from 90% to 10% . Over the next four passages , this antibody concentration was maintained and the infected cell percentage gradually increased from 10 to 90% at P25 . From P26 to P27 , the infected cells remained high at 90% , even though HC33 . 1 was increased to 6 . 0 µg/ml . Second , a new mutation developed at S419N in mainly a quadruple mutation variantN417T+S419N+N434D+K610R . This variant increased from 10% at P20 to 70% at P27 ( Fig . 2C ) . A second variantN417T+S419N was also detected at a lower percentage of 10% at P27 . The S419N mutation is within the HC33 . 1 epitope , although the residue at 419 is not a contact residue for the antibody ( Fig . 1A ) . The findings suggest that the antibody concentration at P20 has risen to a level where the triple mutation variantN417T+N434D+K610R can no longer survive . Increasing HC33 . 1 antibody concentrations led to greater selection pressure that resulted in the emergence of an S419N mutation . The location of the S419N mutation is between two contact residues for HC33 . 1 located at G418 and W420 . Since W420 is also a contact residue for virus binding to CD81 [42] , the S419N could lead to variants with diminished binding by HC33 . 1 and diminished binding by these variants to the HCV co-receptor . From P27 to P29 , an increase of HC33 . 1 from 6 . 0 to 6 . 5 µg/ml led to the appearance of two new variants with double , L413I+N417T ( 20% ) , and triple S395P+L413I+N417T ( 10% ) mutations ( Fig . 2C ) . For the first time , IFA analysis showed some infected cells staining positive by anti-NS3 but negative by HC33 . 1 . Increasing HC33 . 1 concentrations more rapidly at 2 . 5 µg/ml increments from P29 to P30 ( 9 . 0 µg/ml ) to P31 ( 11 . 5 µg/ml ) led to rapid elimination of variants with the S419N mutation from 70% of combined variantN417T+S419N+N434D+K610R and variantN417T+S419N+N434D at P29 to 10% at P30 , and their elimination at P31 . During these passages of extracellular virions , infected cells remained at nearly 80% positive by anti-NS3 IFA staining but were completely negative by HC33 . 1 ( as shown for P31 , Fig . 2A ) . CBH-5 remained +++ . Between P30 and P31 , HC33 . 1 reached a critical concentration that eliminated S419N associated variants . It is probable that there are two contributing factors . First , repeated passages at concentrations ≥10 µg/ml reduced the proportion of S419N variants in the extracellular viral pool . Second , the L413I associated variants are able to enter Huh7 . 5 cells more efficiently leading to their rapid expansion . To confirm this possibility , extracellular virus from P31 was passaged once more at 11 . 5 µg/ml to increase virus stock and then placed in two high concentrations of HC33 . 1 at 20 ( P33 ) and 50 µg/ml ( P34 ) ( Fig . 2C ) . As expected , virus infectivity remained high with nearly 90% of cells stained positive by anti-NS3 and negative by HC33 . 1 . Sequence analyses of P33 and P34 were identical with 90% variantS395P+L413I+N417T and 10% variantL413I+N417T . The sensitivity of escape variants isolated at different passages compared to the initial virus stock ( consisting mainly of variantN417S at P0 ) was tested in dose-dependent studies with HC33 . 1 ( Fig . 3A ) . At P18 ( phase II ) , when the dominant variant contained triple mutations , N417T/N434D/K610R , a modest reduction of 40% in neutralization sensitivity was apparent only at 1 µg/ml and not at the higher antibody concentrations . At P27 ( phase III ) , when the dominant variant contained quadruple mutations , N417T/S419N/N434D/K610R , a more significant reduction of 50–75% in sensitivity to HC33 . 1 was observed at concentrations between 1–10 µg/ml . From P31–P34 ( phase IV ) , when cells infected with passaged virions no longer showed HC33 . 1 binding by IFA and the dominant variant contained S395P/L413I/N417T mutations , essentially no neutralization was observed against passaged virus ( P34 ) at all antibody concentrations . To verify these findings , and because wt HCVcc declined rapidly in the beginning of phase II and new variants appeared in combination with N417T , the variantN417T was employed as the reference virus to determine the role of mutations observed in phase II ( N434D and K610R ) , in phase III ( S419N ) , and in phase IV ( L413I ) . The N434D and K610R mutations were engineered with N417T in double and triple mutation bearing variants . The S419N mutation was engineered in single and quadruple mutation variants . For the two variants observed at P31–P34 having mutations at L413I , with or without S395P , both were constructed in the context of N417T . HCVcc plasmid DNA constructs were made and their corresponding viruses were harvested following electroporation of the viral RNA into Huh7 cells . The neutralization sensitivities of these recombinant HCVcc variants were then measured ( Fig . 3B ) . Recombinant variantN417T/N434D ( IC50 2 . 1 µg/ml ) , variantN417T/K610R ( IC50 1 . 7 µg/ml ) and variantN417T/N434D/K610R ( IC50 1 . 6 µg/ml ) had nearly two times the IC50 values as variantN417T ( IC50 1 . 0 µg/ml ) . This indicated that N434D and K610R mutations contributed to modest decrease in neutralization sensitivity to HC33 . 1 , although combining both mutations had no additive effect . For the S419N mutation observed in phase III , the variantN417T/S419N/N434D/K610R showed a more substantial decrease in neutralization sensitivity with IC50 values of 6 . 9 µg/ml . The variants bearing mutation at L413I with or without the S395P mutation , observed in phase IV , were completely resistant to HC33 . 1 neutralization ( >50 µg/ml ) . The findings with constructed HCVcc variants collectively confirmed the results observed with passaged virions obtained in phase II , III and IV . To assess that the drop in HC33 . 1 neutralization potency is due to decrease in antibody binding to these escape variants , binding studies against recombinant variant E1E2 cell lysates were performed ( Fig . 3C ) . Binding by HC33 . 1 to the N417T variant was greater than to wt JFH1 , which is consistent with greater neutralization potency against the N417T HCVcc variant ( Fig . 1B and 1D ) . As expected , progressive decrease in binding was observed in the following order of variants: N417T>N417T/N434D/K610R>N417T/S419N/N434D/K610R . No binding was observed with either L413I/N417T or S395P/L413I/N417T associated variants , which is consistent with complete viral escape associated with the L413I mutation . To confirm that the S395P mutation had no effect on HC33 . 1 , a variant having just S395P was tested and no reduction in HC33 . 1 or AP33 binding was observed ( Fig . S1 ) . The aa 412–423 region is known to be highly conserved and involved in virus binding to CD81 [42] . This implies that the region is under functional constraints and that viral escape from neutralizing antibodies to this region will be at least associated with compromised in vitro viral fitness . However , escape from AP33 occurs when there is an N-glycan shift from 417 to 415 [45] ( Fig . 1B–ID ) . More importantly , the escape variants bearing either N417S or N417T mutation exhibited improved viral fitness ( Fig . 1E ) . A similar viral escape pattern from HCV1 has been also documented in experimental animals and HCV infected patients [44] , [46] . Since the viral escape pattern from HC33 . 1 is different from AP33 , viral fitness of the dominant variants identified in phase II , III and IV were measured . To avoid possible contribution of non-E1E2 mutations contributing to fitness in passaged virus , the constructed recombinant HCVcc variants were employed for this study . Huh7 cells were infected with each variant HCVcc at a 0 . 1 MOI and the infectious virus yield at 96 hours was determined ( Fig . 3D ) . From phase II , the two mutations , N434D and K610R in the context of N417T , variantN434D+N417T+K610R had a higher virus yield compared to wt HCVcc ( P = <0 . 003 ) . The S419N mutation observed in phase III in the context of N417T , variantN417T+S419N , had nearly three-fold decrease in virus yield compared to wt HCVcc ( P = <0 . 017 ) . The L413I mutation in variantL413I+N417T and variantS395P+413I+N417T had modest reductions in virus yield compared to N417T , but they were not significantly higher than wt HCVcc ( respective P values = <0 . 177 and = <0 . 106 ) . All escape variants essentially had higher or normal in vitro viral fitness except for the variants with the S419N mutation having a compromised viral fitness . The S419N mutation emerged at a critical inflection point of 5 µg/ml HC33 . 1 ( P20 ) and not at 4 . 5 µg/ml ( P18 ) ( Fig . 2C ) . This raised a question whether the S419N substitution is a truly concentration-dependent mutation . To address this possibility , the extracellular virus pool at P18 , which did not contain S419N associated variants , was passaged 14 more times with the HC33 . 1 concentration remaining constant at 4 . 5 µg/ml ( Fig . 4A ) . Sequence analysis showed that the triple mutation variantN417T/N434D/K610R persisted as the dominate isolate with other N417T variants , variantN417T/N434D and variantN417T , at lower percentages in the viral pools and eventually not detected ( as shown for P18-3 to P18-14 , Fig . 4A ) . The fact that the S419N mutation did not emerge indicated that the variant containing triple mutations , N417T+N434D+K610R , sufficiently altered HC33 . 1 binding and neutralization such that the virus can persist under continuous immune selection at this antibody concentration . When the virus was first exposed to 5 µg/ml HC33 . 1 at P20 , the first indication of an S419N mutation was observed and the variantN417T/S419N/N434D/K610R rapidly expanded over subsequent passages ( Fig . 2C ) . To further prove that the S419N mutation is concentration dependent , HC33 . 1 was withdrawn from and repeatedly passaged to determine whether the S419N mutation reverted back to the wt residue at this position . The P27 viral pool comprising 70% of variantN417T/S419N/N434D/K610R was passaged 15 more times in the absence of HC33 . 1 ( Fig . 4B ) . Sequence analysis showed that the variantN417T/S419N/N434D/K610R reduced from 70% to 10% in the first 4 rounds and completely disappeared in the following rounds . The dominant isolates at P27-8 to P27-15 were triple mutation variantN417T/N434D/K610R . At P27-15 , an N417S associated variantN417S/N434D/K610R appeared . The pattern shows that the induction of the S419N mutation is HC33 . 1 antibody concentration dependent and occurred in the context of the triple mutation variantN417T/N434D/K610R . It is possible that these mutations influenced the emergence of the S419N mutation . To determine whether the triple mutation variantN417T/N434D/K610R is stable , the viral pool at P18 , containing 70% variantN417T/N434D/K610R , was passaged repeatedly without HC33 . 1 ( Fig . 4C ) . Sequence analysis showed that this variant persisted . It should be noted that when HC33 . 1 was withdrawn from P18 and P27 ( Fig . 4B and 4C ) , the adaptive mutation at N417S eventually returned and co-existed with N417T . This provides additional proof that the N417T mutation is a specific response to HC33 . 1 immune selection . The L413I mutation is associated with stable variants ( Fig . 4D ) . When the P34 viral pool was passaged eight times without HC33 . 1 , sequence analyses remained the same throughout these passages , consisting of 90% variantS395P/L413I/N417T and 10% variantL413I/N417T . Overall , stable and unstable mutations were induced under antibody pressure . The mutations at 417 and 434 are a direct response to low antibody pressure without a cost in viral fitness . Consequently , when antibody pressure is withdrawn , variants containing these mutations will persist . The mutation at 419 leads to more resistant variants having compromised fitness . When antibody pressure is withdrawn , the virus reverts back to a wt residue at this position that restores an improved fitness .
These studies defined the pathways of viral escape and the formation of quasispecies from a single neutralizing antibody directed against a conserved region encompassing aa 412–423 on the E2 glycoprotein that underscore the difficulty in vaccine design for this highly variable virus . Neutralization escape occurred in a nonrandom stepwise progression in response to the antibody concentration and was mediated by multiple mechanisms with relatively few amino acid changes . The mutations were at residues within and outside of the region encompassing the epitope , and some were associated with a N-glycan shift . Multiple variants appeared when infectious virions were co-cultured with low antibody concentrations that have two mutations , N434D and/or K610R , located outside of the epitope . These variants were stable and not associated with reduced in vitro viral fitness . Their development exemplifies the formation of variants or quasispecies from one antibody that contributes to viral persistence in the presence of neutralizing antibodies . In contrast , mutations within the region encompassing the epitope , aa 412–423 , had different effects . The N-glycan shift associated mutation at S419N reverted to wt residue at this position when antibody selection pressure was lowered or withdrawn . The S419N associated variants , having compromised in vitro viral fitness , highlight the constraints on molecular evolution within the epitope because of the essential role of this region in HCV entry . A third mutation at a contact residue , L413I , occurred at higher HC33 . 1 selection pressure that resulted in variants completely escaping virus neutralization by this antibody . These variants were stable and had in vitro viral fitness similar to wt HCVcc . Although the L413I mutation was elicited in these studies , the Leu in this position is highly conserved in patient sequences [45] . Only 11 of 2108 curated E2 sequences of >100 bases length in the LANL Hepatitis C Virus Database , varied from Leu at this position [48] , [49] . All of these variants are L413P , except for a genotype 5a sequence from South Africa which is L413F . Additionally , only 18 of 25629 uncurated E2 sequences deposited in GenBank since 2009 varied from Leu at 413 . Again all of these variants were L413P , except for one each of L413Q , L413F , L413H and L413V . The elicited L413I mutation is therefore considered not to be found thus far in nature . Similarly , in a subset of the 2108 LANL HCV Database sequences consisting of 1311 longer high-quality E2 sequences , Gly at 418 is highly conserved and only two out of these 1311 sequences varied from Gly . The Trp at 420 is absolutely conserved . Only one of the 1311 sequences contained Trp to Arg change at 420 and this is more likely due to PCR error since the W420R mutation is not tolerated in JFH1 HCVcc ( unpublished data ) . The observed conservation of Leu at 413 raises a question why the L413I mutation has not been documented more frequently in light of our studies and because the L413I associated variants are stable , and without compromised fitness . One possible explanation is that HC33-like antibodies are of low frequency [33] , [34] and when present are of low titers . The low immunogenicity of aa 413–423 is possibly due to the masking effect of HVR1 [50] . Consequently , the L413I mutation is not necessary for HCV infection to persist in the majority of HCV infected individuals . Another possibility is that this mutation is strictly an in vitro virus-antibody co-culture phenomenon . Overall , the combination of multiple escape pathways enables the virus to persist under a wide range of antibody concentrations . In previous studies with antigenic domain B antibodies , epitope mapping by alanine scanning revealed that their cognate epitopes were located in two discontinuous segments on E2 , encompassing aa 425–443 and aa 529–535 [32] , [51] . The region at 529–535 is highly conserved and under functional constraints , because these residues participate in E2 interaction with CD81 [42] . The 425–443 region located immediately downstream of the 412–423 region is a more variable region and five of these residues at positions 431 , 434 , 435 , 438 and 439 are sites of escape mutations from domain B antibody-mediated neutralization [28] , [31] , [32] . Among the five residues , substitutions at 431 and 439 have no negative impact on in vitro viral fitness [28] , [32] . But the other three at 434 , 435 and 438 adversely affect fitness by reducing virus binding to CD81 [32] . In the current studies , partial escape from HC33 . 1 at low antibody concentrations also involved the 434 residue , although this antibody is against a linear epitope upstream of this location . A mutation at 434 reduced antibody binding and neutralization . These observations taken together outline a functional sequence organization at the N-terminal end of E2 . It consists of a conserved region at aa 412–423 that is flanked by two variable regions , the HVR1 located at aa 383–411 and a second variable region located at 425–443 . While mutations within HVR1 are mostly in response to antibodies directed at linear epitopes within HVR1 , the 425–443 variable region is responsible for escape from antigenic domain B antibodies and now , antigenic domain E antibodies ( as represented by HC33 . 1 ) . It is possible that the K610R mutation is indicative of a different variable region on E2 . In other studies , we found that the C-terminal end of this 425–443 variable region , encompassing 441–443 , is actually quite conserved . These three residues form a critical binding pocket of a cluster of overlapping epitopes , designated as antigenic domain D [28] , [52] . HMAbs directed at domain D are not likely to be associated with viral escape . Taking this into consideration , the variable region is more restricted to the region encompassing aa 425–440 . The second pathway of escape involves mutations associated with a glycan shift . Asparagine ( N- ) linked protein glycosylation plays crucial roles in viral protein folding and in regulation of protein functions that include epitope accessibility . The most commonly used glycosylation sequon was first defined as Asn-X aa-Ser/Thr ( Xaa Pro ) [53] , and since this first observation , more variable sequons have been reported ( review in [54] ) . In the aa 412–423 sequence on E2 , there are three residues , N415 , N417 and S419 , perfectly placed for a “glycosylation sequon” that allows a glycan shift either forward ( +2 ) or backward ( −2 ) [55]–[57] with the N417 as the key residue . Through the studies of HCV evolution in the presence of HC33 . 1 , at least four escape strategies are linked to these three residues that impact antibody access to its epitope and affecting the neutralization potency of the antibody . However , some of these escape mechanisms are associated with a cost in fitness . First , Asn at the 417 position , designated as the first N-glycan among twelve in the highly glycosylated HCV E2 glycoprotein , is highly conserved among HCV genotype and subtype isolates [18]–[21] . The position of this N1 glycan appears to have a greater negative modulating effect on HC33 . 1 than AP33 , with both directed at aa 412–423 ( Fig . 1B–1D ) . This is supported by the observed shift in viral population from predominantly N417S in the virus stock ( P0 ) back to a more uniform wt population , as soon as the virus was exposed to HC33 . 1 , albeit at a low concentration . The reappearance of wt JFH1 HCVcc was the first step in viral escape because wt virus is more resistant to HC33 . 1 neutralization than the N417S variant ( Fig . 1B and 1C ) . Second , the glycan shift associated with the N417S mutation occurs spontaneously , as observed in natural infection [44] , [46] and in passaged cell culture HCVcc [45] . The N417S change is an adaptive mutation that leads to a variant with greater in vitro viral fitness ( Fig . 2E ) and is able to completely escape from AP33 , but not the HC33 antibodies to aa 412–423 ( Fig . 1C ) . The implication is that AP33 and the HMAb HCV1 [44]–[46] targeting the same region as HC33 . 1 are more glycan-dependent . Third , both Ser and Thr are believed to be equal alternative amino acids in glycosylation sequon ( Asn-Xaa-Ser/Thr ) . However , the selection of Thr substitution ( Asn-Xaa-Thr ) is associated with HC33 . 1 immune pressure and not Ser substitution ( Asn-Xaa-Ser ) ( Fig . 2B and 2C ) . The finding that N417S associated variants began to be detected after withdrawal of HC33 . 1 from passaged virus supports our analysis of a Thr substitution specifically induced by this antibody ( Fig . 4B and 4C ) . The reason why Asn-Xaa-Thr was preferentially selected in the presence of antibody is not entirely clear because N417T HCVcc and N417S HCVcc have similar fitness and sensitivity to HC33 . 1 ( Fig . 1 ) . Some studies noted that glycosylation of Asn-Xaa-Thr sequons is approximately 40 times more efficient than that of Asn-Xaa-Ser sequons [58] , [59] . In addition , the selection of Asn-Xaa-Thr over Asn-Xaa-Ser occurred in response to an antibody directed at the aa 412–423 region but not by neutralizing antibodies directed at other antigenic regions . When escape studies were performed with antigenic domain B antibodies , the N417T mutation has not been observed [28] , [32] . Importantly , during viral evolution in the presence of HC33 . 1 , the N434D , K610R and S419N escape mutations occurred in the context of N417T and not N417S . Taken together , the N417T change is a specific response to HC33 . 1 and not an adaptive mutation . The identification of the N417T mutation provides additional support that the virus-antibody co-culture studies with 2a HCVcc is applicable to escape studies with other HCV genotypes/isolates . Clinical studies with HMAb HCV1 in liver transplant recipients infected with genotype 1a led to escape variants having the N417T or N417S mutations [44] . Fourth , it is possible that the S419N mutation generated a new glycan at 419 using −2 glycosylation sequon ( Thr-Xaa-Asn ) [55]–[57] . A shared element between N1 and S419N-associated glycans is that the middle residue in both sequons is G418 , a contact residue for HC33 . 1 . Antibody access to this residue will be blocked by either glycans . The S419N glycan is more efficient than the N1 glycan in shielding the HC33 . 1 and resulting in a significant drop in antibody binding and neutralization ( Fig . 3A–3C ) . However , the formation of the S419N glycan is associated with compromised in vitro viral fitness , which can be attributed to this glycan being in closer proximity to W420 , a contact residue for virus binding to CD81 [42] . The effect of S419N glycan shift in reducing HC33 . 1 binding explains the persistence of variants with compromised fitness over the course of multiple passages ( P20–P29 ) under continuous immune selection . Furthermore , the cost in viral fitness associated with S419N explains why the N434D mutation occurred first in the context of N417T because the fitness of these variants was not significantly compromised . But the ability of this mutation to reduce HC33 . 1 binding was not as significant as S419N . The transition from nearly uniform wt virions ( P6–P9 ) to variants that were more able to co-exist with low levels of HC33 . 1 in phase II ( P18 ) ( Fig . 2B ) appears to be a non-random process during viral evolution . There were a restricted number of mutations at a limited number of sites during sequence space expansion ( P10 ) and contraction ( P13–P14 ) . All four variants had a combination of N417T , N434D and K610R mutations at P13–14 that were the same mutations in the dominant variantN417T/N434D/K610R at P18 . In this phase of viral escape , a mutation occurred in a region that is more variable , e . g . , 425–440 , and not under functional constraints . Mutations in this variable region are more likely to be in stable variants that persist regardless of continuous presence of neutralizing antibody ( Fig . 4A ) or absence of antibody ( Fig . 4C ) . The development of stable variants or quasispecies that are more resistant to virus neutralization partly explains why HCV co-exists with neutralizing antibodies during chronic infection . While this balance between variants having robust fitness and antibody can be maintained in repeated passages ( Fig . 4A ) , it can be disrupted by a slight increase in antibody concentration . When HC33 . 1 reached 5 µg/ml at P20 ( Fig . 2C ) , a quadruple mutation emerged precisely by the addition of the S419N mutation onto the existed triple mutation variant , without undergoing a sequence space expansion . The quadruple mutation variant preferentially replicated over the triple mutation variant ( from P20 to P27 ) . Although the quadruple mutation variantN417T/S419N/N434D/K610R can co-exist at higher levels of HC33 . 1 ( 5 . 0–6 . 0 µg/ml ) , viral escape is still incomplete since the virus can be neutralized at a higher percentage at higher antibody concentrations ( Fig . 3A and 3B ) . This suggests that incomplete escape is sufficient for the virus to co-exist with HC33 . 1 . The antibody concentration-dependent stepwise escape pattern is suggestive of low affinity or low antibody concentration facilitating the formation of escape variants or quasispecies . This could be the scenario during acute HCV infection when a wide range of lower affinity neutralizing antibodies is more likely to be elicited . As acute infection progresses to persistent infection , a more robust neutralizing antibody response provides immune pressure that leads to the selection of escape variants with compromised fitness . This in turn will contribute to a transient reduction in viral load resulting in a reduced B cell response . The lowering of a neutralizing antibody response leads to the release of virions with greater fitness but potentially greater sensitivity to virus neutralization , as observed when the S419N mutation changed back to wt when the neutralizing antibody was removed . This cycle may explain in part persistent viremia during chronic HCV infection in the presence of serum neutralizing antibodies . At the same time , our findings pose a different challenge to vaccine development beyond the identification of highly conserved epitopes mediating virus neutralization . It will be necessary to induce high potency neutralizing antibodies to multiple epitopes within 412–423 that prevent the formation of escape variants , which can co-exist with lower potency or levels of neutralizing activities . The fact that the aa 412–423 segment on E2 is the target of both AP33-like and HC33 . 1-like antibodies increases the importance of this region in an effective HCV vaccine . It will be more difficult for the virus to escape simultaneously from both sets of these antibodies . The isolation and characterization of neutralizing human monoclonal antibodies to HCV will further our understanding of viral neutralization escape mechanisms that will be necessary for vaccine design .
Ethical approval was obtained from the Administrative Panel on Human Subjects in Medical Research ( protocol number 13860 ) , Stanford University , Stanford , California , USA . Written informed consent was obtained from the participant . HEK-293T cells were obtained from the ATCC . Huh7 [60] and Huh7 . 5 cells , generously provided by Dr . Charles Rice ( Rockefeller University ) , were cultured at 37°C , 5% CO2 in DMEM ( Invitrogen , Carlsbad , CA ) supplemented with 10% fetal calf serum ( FCS ) and 2 mM glutamine ( Sigma-Aldrich Co . , St . Louis , MO ) . The secreted alkaline phosphatase ( SEAP ) reporter cell line Huh7J-20 was described previously [61] . HMAbs HC33 . 1 , CBH-5 , CBH-17 and HC-11 against HCV E2 have been described previously [25] , [47] , [51] . A MAb against HCV NS3 protein was generously provided by Dr . George Luo ( University of Kentucky ) . JFH-1 2a virus was generously provided by Dr . Takaji Wakita ( National Institute of Infectious Diseases , Japan ) . Virus stocks were produced as described in [51] , [62] and virus titers were determined by a focus-forming unit assay , FFU , as described [32] . JFH-1 2a HCVcc was employed in this study to determine viral evolution under HMAb HC33 . 1 and performed essentially as described [28] , [32] . Briefly , Huh7 . 5 cells ( 3 . 2×104/ml ) seeded 24 hrs previously in a 24-well plate were inoculated with a mixture of HCVcc ( 1×104 FFU ) and HMAb HC33 . 1 . The initial concentration of the neutralizing antibody was adjusted to the 25% inhibitory concentration ( 0 . 25 µg/ml ) of the antibody against the 2a HCVcc . HMAb anti-CMV R04 was used as mock human IgG selection . The cells were collected for analysis by indirect immunofluorescent assay ( IFA ) and the extracellular virus was harvested for virus titration , the next passage of selection , and for viral sequence analysis . The entire process constituted one passage of infectious virus . To ensure that minority variants have a high probability to be passed to the next round selection , extracellular virions were repeatedly passaged until the virus titer reached 1×104 FFU/ml , which correlated to ≥80% infected cells . Growth of extracellular virus was measured by FFU assay and the emergence of escape variants was monitored weekly by two-color confocal immunofluorescence microscopy and by staining with HC33 . 1 and an anti-NS3 antibody . To assess the relationship between emerging specific mutations and the antibody concentration , selected viral supernatants were passaged in the growth medium containing antibody at a fixed concentration or no antibody ( antibody was withdrawn from the medium ) for a number of rounds as indicated . Total RNA or viral RNA from virus-containing culture supernatant was extracted using commercial kits ( Qiagen , Valencia , CA ) and reverse transcribed to cDNA SuperScript III reverse transcriptase ( Invitrogen , Carlsbad , CA ) using primer p7rev ( CCCGACCCCTGATGTGCCAAGC ) . The envelope genes ( E1E2 ) were amplified using the Expend High Fidelity PCR system ( Roche Applied Sciences , Indianapolis , IN ) and primers E1F ( GGAACCTTCCTGGTTGCTCTTTCTCTATCTTCC ) and E2R ( TGCTTCGGCCTGGCCCAACAAGAT ) . The PCR products were ligated into the Topo cloning vector ( Invitrogen , Carlsbad , CA ) , and individual clones containing an insert of the expected size were sequenced in both sense and antisense strands ( Elim Biopharm , Hayward , CA ) . Selected PCR products were cloned into pCDNA 3 . 1 expression vector for protein production in binding assay . Neutralization against extracellular virus in cultured supernatant from different passages was measured by FFU-reduction neutralization assay as previously described [28] . The antibody concentration causing 50% reductions in FFU was determined by linear regression analysis . The percent neutralization was calculated as the percent reduction in FFU compared with virus incubated with an irrelevant control antibody . Neutralization against recombinant virus variants were performed using Huh7J-20 cells , and virus infectivity levels were determined by SEAP reporter assay , as described previously [61] . Briefly , Huh7J-20 cells were plated out 24 hrs prior to infection at a density of 3×103 per well in a 96-well plate . Virus was pre-incubated at 37 C for 1 h with the appropriate antibody prior to infecting the cells at an MOI of 0 . 1 . At 3 h post-infection , the inoculum was replaced with fresh medium and incubated for 72 hrs . The virus infectivity levels were determined by measurement of the SEAP activity released into the medium . ELISA was performed to measure antibody binding to the wt or mutant E2 glycoproteins , as described [28] . Briefly , microtiter plates were prepared by coating each well with 500 ng of Galanthus nivalis agglutinin ( GNA ) and blocking with 2 . 5% nonfat dry milk and 2 . 5% normal goat serum . Lysates of cells expressing wt HCV , mutant E1E2 , or pelleted virus were captured by GNA on the plate and later bound by a range of 0 to 150 µg/ml of HMAb . The bound HMAb was detected by incubation with alkaline phosphatase-conjugated goat anti-human IgG ( Promega; Madison , WI ) , followed by incubation with p-nitrophenyl phosphate for color development . Absorbance was measured at 405 nm and 570 nm . Epitope mapping was performed using alanine substitution mutants of a defined E2 region: aa 411–424 . Alanine substitution mutants were constructed in plasmids carrying the 1a H77C E1E2 coding sequence ( GenBank accession number AF009606 ) as previously described [28] . All the mutations were confirmed by DNA sequence analysis ( Sequetech , Mountain View , CA ) for the desired mutation and for exclusion of unexpected residue changes in the full-length E1E2 encoding sequence . The resulting plasmids were transfected into HEK293T cells for transient protein expression using the calcium-phosphate method . The mutated constructs were designated X#Y , where # is the residue location in H77C , X denotes the single-letter code for the H77C amino acid , and Y denotes the altered amino acid . Virus-containing supernatants were inoculated onto Huh7 cells at a multiplicity of infection ( MOI ) of 0 . 1 . The cells were seeded 24 h previously in a 24-well plate . After 3 h of incubation at 37°C and 5% CO2 , the inoculum was replaced with fresh complete medium and incubated for an additional 96 hrs . The supernatant fluids were then collected , and the titer of infectious virus was assessed by the SEAP reporter assay , as described previously [61] . To evaluate contribution of mutated individual amino acid observed during viral evolution , introduction of amino acid change was conducted using a QuikChange II site-directed mutagenesis kit as described previously [28] , [32] . All the mutations were confirmed by DNA sequence analysis ( Sequetech , Mountain View , CA ) for the desired mutation and for exclusion of unexpected residue changes in the full-length E1E2-encoding sequence . The mutated constructs were designated X#Y , where # is the residue location in H77C , X denotes the single-letter code for the H77c amino acid , and Y denotes the altered amino acid . The exception is for the K610 , where # ( 610 ) is the residue location in JFH1 that corresponds to # ( 606 ) residue location in H77C . Statistical analyses were performed using unpaired Student t test ( GraphPad software ) , with p values<0 . 05 considered statistically significant . Sequences were downloaded from the Los Alamos National Laboratory Hepatitis C Database ( http://hcv . lanl . gov/content/index , [48] , [49] ) , which contains a set of curated sequences deposited prior to 2009 . E2 sequences deposited in GenBank ( http://www . ncbi . nlm . nih . gov ) from 2009 onwards were also retrieved . Alignments were made and viewed in MEGA6 ( www . megasoftware . net [48] , [49] . | An effective hepatitis C virus ( HCV ) vaccine will require information on epitopes that are responsible for protective antibodies against this highly diverse virus . A region known to be highly conserved and responsible for broadly neutralizing antibodies is located on the E2 glycoprotein at 412–423 . To test whether HCV can escape from human antibodies against this region , infectious virus was passaged in culture in increasing concentrations of a human monoclonal antibody to 412–423 . Multiple pathways of viral escape were identified at different levels of antibody concentrations . Some of the escape virions were stable and were more robust than wild-type virus . Other escape virions were unstable and had compromised in vitro viral fitness . Collectively , these findings underscore the difficulties in HCV vaccine development and the need to induce high potency antibodies not associated with viral escape . | [
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] | 2014 | Non-random Escape Pathways from a Broadly Neutralizing Human Monoclonal Antibody Map to a Highly Conserved Region on the Hepatitis C Virus E2 Glycoprotein Encompassing Amino Acids 412–423 |
Schistosomiasis is a parasitic zoonosis caused by small trematode worms called schistosomes , amongst which Schistosoma japonicum ( S . japonicum ) is endemic in Asia . In order to understand the schistosome-induced changes in the host metabolism so as to facilitate early diagnosis of schistosomiasis , we systematically investigated the dynamic metabolic responses of mice biofluids and liver tissues to S . japonicum infection for five weeks using 1H NMR spectroscopy in conjunction with multivariate data analysis . We were able to detect schistosomiasis at the third week post-infection , which was one week earlier than “gold standard” methods . We found that S . japonicum infection caused significant elevation of urinary 3-ureidopropionate , a uracil catabolic product , and disturbance of lipid metabolism , stimulation of glycolysis , depression of tricarboxylic acid cycle and disruption of gut microbiota regulations . We further found that the changes of 3-ureidopropionate and overall metabolic changes in both urinary and plasma samples were closely correlated with the time-course of disease progression . Furthermore , such changes together with liver tissue metabonome were clearly associated with the worm-burdens . These findings provided more insightful understandings of host biological responses to the infection and demonstrated that metabonomic analysis is potentially useful for early detection of schistosomiasis and comprehension of the mechanistic aspects of disease progression .
Schistosomiasis is a chronic parasitic disease caused by infection with schistosomes . As one of the most infectious species , Schistosoma japonicum is mainly endemic in Asia with over 1 million infected individuals and about 46 million people at risk in China , the Philippines and Indonesia [1]–[3] . During schistosomiasis progression , schistosomes mature to adults in the hepatic circulation and then in pairs migrate to inhabit in the mesenteric veins , where they mate and lay a large number of eggs in the vessels of the intestinal wall . Consequently , schistosomiasis causes diarrhea , fatigue , anemia at the early stage of infection , and portal vein hypertension syndrome , ascites and liver fibrosis at the later stages [1] . Currently , schistosomiasis is diagnosed using the Kato-Katz technique by detecting eggs in feces under microscope [4] , or with immunological approaches by detecting soluble antigens secreted from the hatching-eggs via the antigen-antibody reaction [5]–[6] . However , such methods are not suitable for early diagnosis and the adverse effects associated with the deposition of schistosome eggs would have already occurred when diagnosis were made . Therefore , development of early diagnostic methods is in urgent need so as to treat patients timely to prevent clinical complications . Understanding the dynamic responses of the hosts with schistosomiasis in the systems level is important to provide insights into the mechanisms underlying disease progression and thus could be potentially useful for early diagnosis of schistosomiasis . Previous work has examined the schistosomiasis-caused alterations in the transcription and protein levels . Reductions in biologically active albumin mRNA and increased type I procollagen mRNA were observed in the liver of S . mansoni infected mice 6 weeks post-infection [7] . However , no such changes were noted at the earlier stages of infection [7] . The expressions of proteins associated with structural components ( procollagen VI , keratin and actin ) , the stress responses ( heat shock proteins , chaperones ) were significantly promoted [8] , which may be relevant to the infection-caused liver fibrosis and schistosomes' uptake of host proteins onto their tegument during development [9] . Furthermore , S . mansoni infection caused significant increases in the activities of pyruvate kinase and phosphofructokinase but marked reductions in the activities of citrate synthase , glycogen phosphorylase , glucose-6-phosphate dehydrogenase , carbamoyl phosphate synthetase and ornithine carbamoyltrasferase [10]–[11] . Such observations were consistent with recent proteomic results that S . mansoni infection ( for 8 weeks ) caused remarkable decreases in the expression of host liver enzymes associated with the Krebs cycle , fatty acid cycle , urea cycle , amino acid metabolism and catabolism , amongst which the expression of malic enzyme was decreased 15-folds by infection [8] . However , it is not clear thus far whether such systems responses are generic for infections by other schistosome species and what are the host systems responses at the early stage of infections . The analysis of host metabolite composition ( i . e . , metabonome ) is a well suited approach to understand the holistic metabolic responses to infections since metabonomics is a branch of science concerned with the metabolite composition of biological systems and its dynamic responses to both endogenous and exogenous stimuli [12]–[14] . As a powerful holistic analytical approach , metabonomics has already been widely applied in studies of disease pathogenesis [15]–[17] , drug toxicity [18]–[19] and in the environmental [20]–[21] and nutritional sciences [22]–[23] . This approach has also been successfully applied in parasitological studies with comprehensive characterizations of the host metabolic responses to infections by several parasites , such as Trypanosoma brucei brucei [24] , Plasmodium berghei [25] and Echinostoma caproni [26]–[27] . The results also showed that schistosomal infections led to suppression of the hosts' Krebs cycles , disruption of amino acid metabolism , liver injuries and disturbances of the gut microbiota [28]–[29] . A recent study revealed that S . mansoni infection resulted in significant metabolic alterations in a range of mouse tissues [30] . Metabolic alterations were also comprehensively studied for hamster models co-infected with S . japonicum and Necator americanus [31] . However , the previous investigations were all based on a well-established late-stage schistosomal infection model . The dynamic metabolic responses associated with progression of infection remained to be elucidated . In this work , we systematically investigated the time-course metabonomic changes in urine and blood plasma of the S . japonicum infected mice over 5 weeks and liver tissues at the fifth week post-infection using 1H NMR spectroscopy and multivariate data analysis . The main objectives are to define the host metabonomic responses to infection at the early stages and their dynamic changes during the disease progression , which are of potential importance for early diagnosis and prognostic understandings of schistosomiasis .
A total of 60 female pathogen free BALB/c mice , about 8 weeks old weighing 20±2 g , were purchased from the animal laboratory center of Wuhan university ( China ) , and housed in groups of 5 in plastic cages under environmentally-controlled conditions ( temperature: 18∼22°C; humidity: 40∼70%; light-dark cycle: 12–12 h ) . Mice had free access to rodent food and water . After 3 weeks of acclimatization , half of the mice ( n = 30 ) were infected with 80±2 S . japonicum cercariae , each via shaved abdominal skin . The cercariae were obtained from infected O . hupensis ( Anhui ) after exposure to artificial light . The rest of the mice served as controls . All experimental procedures were performed according to the National Guidelines for Experimental Animal Welfare ( MOST of People's Republic of China , 2006 ) and were approved by the Animal Welfare Committee of Wuhan University ( Permission No . SYXK ( E ) 2008–0013 ) . Plasma and urine samples were collected one day before infection and after infection for five weeks on a weekly basis . Sample collection was carried out between 08:30–11:30 in order to avoid potential metabolic variations due to diurnal cycle . Blood samples ( 70∼80 µl ) were collected from the orbital venous plexus and transferred to Eppendorf tubes containing 5 µl sodium heparin , followed by centrifugation at 3000 g for 10 mins . The supernatant ( ∼30 µl ) was transferred into 0 . 5 ml Eppendorf tubes , immediately immersed in liquid nitrogen , and stored at −80°C . Urine samples ( 50∼400 µl ) were collected in empty plastic boxes by gently massaging the abdomen of mice and transferred into Eppendorf tubes , stored at −80°C . Half of the mice ( 15 control and 15 infected mice ) were sacrificed at 5 weeks post-infection by cervical dislocation and the remaining mice were kept for a separate experiment . Plasma at sacrifice was divided into two portions with one portion kept for NMR analysis and the other for clinical biochemistry analysis . The adult schistosomes were isolated by perfusion via the heart with saline solution containing heparin . The worms in the portal vein and the mesenteric veins were pushed out gently with a dissecting needle . All harvested S . japonicum worms were sexed and counted for worm burden assessments . The middle lobe of liver was excised and immediately snap-frozen in liquid nitrogen and stored at −80°C for 1H High Resolution Magic Angel Spinning ( HR MAS ) NMR analysis . Another small portion of the liver was stored in 10% formalin solution for histological assessments where tissue samples were sectioned into 5 µm slices and stained with H&E and examined under a light microscope ( BRX-51 , Leica , Germany ) . Urine samples were prepared by adding D2O into urine ( 50∼400 µl ) to make a final volume of 500 µl . Then the liquid was mixed with 50 µl Na+/K+ buffer ( K2HPO4/NaH2PO4 in D2O , 1 . 5M , pD 7 . 4 ) [32] , containing 0 . 01% sodium 3-trimethylsilyl ( 2 , 2 , 3 , 3-2H4 ) propionate ( TSP ) for chemical shift reference . After being vortexed and centrifuged at 10000 g , 4°C , supernatant of 500 µl was transferred into 5 mm NMR tubes . The urinary 1H NMR spectra were acquired at 298 K from a Bruker AVIII 600 MHz NMR spectrometer ( Bruker Biospin , Germany ) equipped with a cryogenic probe , operating at 600 . 13 MHz proton frequency . The plasma samples were prepared by mixing 30 µl plasma with 30 µl saline solution containing 95% D2O , and 30 mM phosphate buffer ( pD 7 . 4 ) . The mixed liquid was transferred into 1 . 7 mm micro NMR tubes . 1H NMR spectra of plasma were recorded at 298 K on a Bruker AV∏ 500 NMR spectrometer , operating at 500 . 13 MHz proton frequency with a broad band inverse detection probe . Liver samples ( about 15∼20 mg ) were rinsed with 0 . 9% saline ( D2O ) and placed in a 4 mm zirconia rotor with a spin rate of 2200 Hz . HR MAS 1H NMR spectra of liver tissues were acquired at 283 K on a Varian INOVA-600 spectrometer equipped with a Varian nanoprobe , operating at 599 . 81 MHz proton frequency . A standard water suppressed one dimensional NMR experiment using sequence [recycle delay −90°−t1−90°−tm−90°-acquisition] was employed for urine [28] . A spin relaxation edited-water saturated 1H NMR experiment using Carr-Purcell-Meiboom-Gill ( CPMG ) pulse sequence was performed for both plasma and liver tissues . A total spin-spin relaxation delay of 70 ms and 400 ms was used for plasma and liver tissues respectively . The 90° pulse length was adjusted to 10 µs . A total of 256 scans were accumulated into 32 k data points , with a spectral width of 20 ppm for plasma and liver samples , and 32 scans were recorded for urine samples . For spectral assignment purposes , two dimensional ( 2D ) NMR spectra ( 1H-1H COSY and TOCSY , 1H-13C HSQC and HMBC ) were acquired on selected samples utilizing standard acquisition parameters [18] , [33]–[34] . 1H NMR spectra were corrected for phase and baseline distortion , and referenced manually using TOPSPIN package ( V2 . 0 , Bruker Biospin , Germany ) . Spectra were segmented into integral regions of 0 . 002 ppm for urine and 0 . 004 ppm for plasma and liver using the AMIX package ( V3 . 8 , Bruker Biospin , Germany ) . The distorted water regions were removed to eliminate the effects of water suppression prior to normalization of the data to the total sum intensity of the spectrum . SIMCA-P+ software package ( V . 12 , Umetrics , Sweden ) was employed for multivariate data analysis . Principal component analysis ( PCA ) was performed by using a mean-centered NMR data to identify general trends and outliers . A supervised multivariate data analysis tool , orthogonal-projection to latent structure discriminant analysis ( O-PLS-DA ) [35]–[36] , was employed with the Pareto scaling method [37] . All models were cross validated using a 7-fold method [38] . In supervised pattern recognition method , validation of model is crucial for interpretation of data and hence all models here have been rigorously evaluated with permutation tests ( permutation numbers = 200 ) [39]–[40] . In order to facilitate interpretation of the results , back-transformation of the loadings was performed as described previously [41] and plotted with color-coded coefficients for each variable using in-house developed MATLAB scripts . The clinical biochemistry of serum was measured using an automatic biochemistry analyzer . Independent t-tests were conducted using SPSS 12 . 0 software and expressed as mean ± SD .
On average , 42 live S . japonicum worms were found ( with standard deviation of 12 ) in the infected mice but with no significant bodyweight differences between the control and infected animals . Histopathological examinations of liver from the infected mice ( 5 weeks post-infection ) showed grayish irregular nodules and marked schistosomal hepatic lesions ( Fig . S1 ) . Clinical serum chemistry results ( Table 1 ) indicated that S . japonicum infection led to significant increases in the activities of alanine aminotransferase ( ALT ) ( ca . 5 folds ) , aspartate aminotransferase ( AST ) ( >1 fold ) , and their ratio ( ALT/AST ) . Infection also caused significant increases in the levels of globulin and decreases in the levels of albumin , alkaline phosphatase , triglyceride and the albumin-to-globulin ratio . 1H NMR spectra of mice plasma , liver tissues ( Fig . 1 ) and urine ( Fig . 2 ) samples contained rich metabolite information with all NMR resonances assigned according to literature data [34] , [42]–[43] and further confirmed with a catalogue of 2D NMR spectra . Glucose , lipoproteins , citrate , creatine and a range of amino acids were detected in the plasma and intact liver tissues from both control and infected BALB/c mice ( Fig . 1 ) . Visual inspection of the plasma spectra revealed that the infected samples ( Fig . 1B ) contained higher levels of N-acetyl-glycoproteins together with lower levels of lipids , citrate and alanine than controls ( Fig . 1A ) . The metabolic profiles of liver tissues of the infected mice ( Fig . 1D ) had lower levels of glucose and glycogen accompanied with higher levels of choline metabolites , such as phosphorylcholine ( PC ) and glyceryl phosphorylcholine ( GPC ) , and alanine than controls ( Fig . 1C ) . 1H NMR spectra of urine from infected mice ( Fig . 2B ) showed obvious elevated levels of 2-keto-isocaproate , 2-keto-3-methyl-valerate , 2-keto-isovalerate , pyruvate , 4-cresol glucuronide , 3-ureidopropionate ( 3-UP ) , dimethylamine ( DMA ) , trimethylamine ( TMA ) , phenylacetylglycine ( PAG ) and alleviated levels of adipate , taurine and hippurate compared with the controls ( Fig . 2A ) . To further obtain the detailed metabonomic differences , we employed multivariate data analysis approaches . Initial PCA of the mean-centered NMR spectral data from plasma of the S . japonicum infected mice and corresponding controls showed that one control sample containing markedly low levels of lipoproteins appeared to cluster closely with the infected group ( data not shown ) . One sample from the infected group was associated with the control group at all time points probably because it had significantly low worm burden with worm count of only 18 . We therefore removed these two animals from subsequent data analysis in order to avoid possible confusions . PCA trajectory ( Fig . S2 ) demonstrated that the metabolic profiles of both mice plasma and urine samples had an association with the time course of S . japonicum infection and disease progression . The metabolic profiles obtained from the infected mice deviated from the corresponding controls from the third week post-infection onwards and such separations became more obvious as disease progression . In order to identify the metabolites associated with such separations , we further compared the metabolic profiles obtained from the infected mice and corresponding controls for all matched time points , including the pre-infection day , week 1 , 2 , 3 , 4 and 5 post-infection , using O-PLS-DA strategy . The same strategy was utilized to analyze spectral data of liver tissues obtained from mice at week 5 post-infection . These O-PLS-DA models were validated using a 7-fold cross-validation strategy and rigorous permutation tests [39]–[40] . Judged from the values of R2X ( goodness of fit ) and Q2 ( robustness of the models ) ( Tables 2 and 3 ) and permutation tests ( Fig . S3; Fig S4 ) , valid O-PLS-DA models were obtained for plasma and urine samples collected at week 3 , 4 and 5 post-infection ( Fig . 3A–C and Fig . 4A–C ) , and liver tissues at week 5 post-infection ( Fig . 5 ) . As noted , plasma ( Fig . 3C ) and urine ( Fig . 4C ) samples collected at week 5 post-infection were further separated into two subgroups . These subgroups were associated with the numbers of worm burden , including a group with a light-infection ( average worms: 36 . 3±11 . 1 ) and the other a heavy-infection ( average worms: 51±8 . 4 , p = 0 . 02 ) . Additional O-PLS-DA comparisons between the control group and the lightly-infected , the control and the heavily-infected groups were performed to assess the variation of metabolites at different infection levels in plasma and urine ( Fig . 3 D , E and Fig . 4 D , E ) . Color-coded coefficient plots ( Fig . 3a–e and Fig . 4a–e ) from O-PLS-DA revealed detailed mice metabolic changes induced by S . japonicum infection with coefficients summarized in Tables 2 and 3 . The discrimination significance at the level of p<0 . 05 was determined for specific metabolites according to the test for the significance based on the Pearson product-moment correlation coefficients , where the absolute coefficient cutoff values ( |r| ) were 0 . 361 for models following 3 , 4 and 5 weeks infection ( Fig . 3a–c and 4a–c ) whereas such values were 0 . 514 and 0 . 497 for light ( Fig . 3d and 4d ) and heavy infection ( Fig . 3e and 4e ) at week 5 post-infection , respectively . The upwards and downwards peaks respectively denote the elevated and alleviated metabolites in the infected mice with hot colored ( e . g . red ) metabolites contributing more significantly to the class discrimination than cold colored ones . Blood plasma samples showed significant elevation of glucose and a range of amino acids together with depletion of lipoproteins and keto-bodies , including D-3-hydroxybutyrate and acetone after infection for 3 and 4 weeks ( Fig . 3a–b ) . Compared to the controls , the metabolic changes of plasma obtained from the lightly infected mice ( Fig . 3d ) at week 5 post-infection were similar to those obtained from the mice at week 4 post-infection ( Fig . 3c ) whereas additional metabolite changes were observed for the heavily infected mice at week 5 post-infection ( Fig . 3e ) . Such changes included elevated levels of N-acetyl-glycoproteins and reduced levels of glucose , citrate ( i . e . , Krebs cycle intermediate ) and choline metabolites ( Fig . 3e ) such as PC and GPC . Compared with controls , the infected mice showed obvious urinary metabolic changes at week 3 post-infection with significant elevation of 2-keto-3-methyl-valerate , 2-keto-isovalerate , 3-UP and some gut-microbiota related metabolites , including TMA , trimethylamine-N-oxide ( TMAO ) and PAG together with alleviation of adipate and Krebs cycle intermediates ( such as succinate , 2-oxoglutarate and citrate ) . As the disease progressing , elevated levels of 4-cresol glucuronide , pyruvate , dimethylamine , malonate , glycine , indoxysulfate , and decreased levels of α-hydroxyisobutyrate , acetate , taurine and hippurate were observed in the urine of infected mice . The urinary metabolic profiles obtained from the lightly infected mice at week 5 post-infection were characterized by the increased pyruvate , glycine , 3-UP and microbiota related metabolites , such as PAG , 4-cresol glucuronide and TMA ( Fig . 4d ) . For the heavily infected group , additional elevation of 2-keto-3-methyl-valerate , 2-keto-isovalerate and creatine together with alleviation of hippurate , 2- ( 4-hydroxyphenyl ) propanoic acid and citrate were noted ( Fig . 4e ) . The cross-validated O-PLS-DA was further conducted for the metabolic profiles of liver tissue obtained at week 5 post-infection . The color-coded coefficient plot ( Fig . 5 ) indicated that compared to controls , the infected mice showed higher levels of hepatic lactate , choline , PC , GPC , TMAO , taurine , creatine and a range of amino acids together with lower levels of glucose and glycogen ( Table 2 ) . Projection to latent structures ( PLS ) models were constructed using Pareto-scaled NMR data of plasma , liver and urine obtained at week 5 post-infection as corresponding X matrices and worm burden as Y matrix ( Fig . 6 ) . Significant correlations were found between the worm burden and metabolic changes in plasma ( Fig . 6A ) , liver tissues ( Fig . 6B ) and urine samples ( Fig . 6C ) . In plasma , reduced levels of glucose , pyruvate and increased levels of lysine and N-acetyl glycoprotein were closely associated with the worm burden ( Fig . 6A ) whilst , in the liver , reduced levels of glucose , glycogen and increased level of glutamate , glutamine were related to worm burden ( Fig . 6B ) . In urine samples , the worm burden was associated with the elevated levels of PAG , 3-UP , creatine , 4-cresol glucuronide , TMAO and DMA together with alleviated levels of hippurate , 2- ( 4-hydroxyphenyl ) propanoic acid and adipate ( Fig . 6C ) . Fig . 7 shows the alterations of relative concentrations of typical metabolites as a function of infection duration and worm burden . It is apparent that infection causes steady increases in the concentrations of 3-UP , PAG and pyruvate together with decrease in the concentration of citrate . The elevation of 3-UP starts from week 3 post-infection and is positively correlated with infection duration and worm burden . Marked changes occurred at the fourth week post-infection for 3-UP , gut microbiota related metabolites ( PAG , hippurate , DMA and TMA ) , pyruvate and citrate .
Previous investigations of metabolic response of schistosomal infections have been focused on the end point of one schistosome life cycle [28]–[30] when eggs have been produced . The metabolic responses of the same host to schistosome infection over time , starting from an early stage of infection have not been previously studied . Our investigation clearly showed that the schistosomal infection-induced metabolic changes were detectable from the third week post-infection in both plasma and urine samples ( Fig . 3A and 4A ) . Such detection of infection is achieved one week earlier than the current “gold standard” method . S . japonicum worms reach maturity and begin to lay eggs around 4 weeks post-infection [44]–[45] . In the current study , the variations in metabolic profiles induced by the infection occurred before sexual maturation of S . japonicum worms in the mammalian host and thus prior to liver injuries by deposition of schistosomal eggs . Infection severity was also distinguished based on the metabolic profiles of both urine and plasma ( Fig . 3C and 4C ) . Furthermore , metabolic profiles of plasma , urine and liver tissues are highly correlated with the intensities of worm burden ( Fig . 6 and Fig . 7 ) . These findings imply that metabonomic investigations of blood plasma and urine are potentially useful in the development of an early diagnostic tool for S . japonicum infection and assessment of infection severity . Liver injury is one of the most important manifestations of S . japonicum infection in humans . Our clinical chemistry data ( Table 1 ) and histological results ( Fig . S1 ) confirmed the occurrence of liver injuries at week 5 post-infection , being consistent with a previous human investigation [46] . One of the metabolic consequences of liver injury is the disturbance of amino acid metabolism , resulting in accumulation of amino acids in the liver and their depletion in plasma . In fact , such disturbed amino acid metabolism was previously noted with high levels of alanine , asparagine , creatine , glutamine and glycine in the S . mansoni infected mice liver [30] . These changes are also broadly similar to the increased concentrations of glutamine and glutamate relative to the lipids resulting from liver injuries caused by chronic hepatitis [47] . Our metabonomic results are clearly consistent with these observations , indicating that there might be some commonality for the metabolic responses to liver injuries caused by different schistosome species . The accumulation of taurine observed here in the liver of schistosomal infected mice is probably due to the liver injury caused deficiency in the formation of taurine-conjugated bile acids and thus subsequent malabsorption that has been reported in human infected with schistosomes [1] . Since taurine is also a cell membrane stabilizer to maintain osmosis [48] , its over-representation in liver may also reflect the liver cell membrane abnormalities following infection . Such view is further supported by the infection-induced accumulation of the cell membrane components ( GPC and PC ) in the host liver observed in current S . japonicum and previous S . mansoni infections [30] . Another important consequence of liver injury is stimulated glycolysis , which is manifested by marked reduction in levels of plasma glucose , liver glucose and glycogen , and the accumulation of liver lactate and urinary pyruvate following 5 weeks infection . Such stimulated glycolysis has also been observed for mice with S . mansoni infection for 49 days [28] . However , we further observed significant elevation of the plasma glucose for the infected mice at week 3 and 4 post-infection ( Fig . 3a–b ) and the light-infection group at week 5 post-infection ( Fig . 3d ) . Such observation is broadly agreeable with the results of a previous study [49] on S . mansoni infection that hyperglycemia was observed for mice at the early stage . This is probably due to active manipulation and adaptation of parasites to the host rather than consequences of host injuries . S . japonicum infection further led to the TCA cycle suppression with alleviation of plasma citrate and urinary citrate , 2-oxoglutarate and succinate which was similar to previous observations for S . mansoni infection [28]–[29] . Such changes were also consistent with the previous findings that the expression of TCA cycle associated enzymes decreased about 5 folds after S . mansoni infection for 8 weeks [8] . Furthermore , the urinary 2-keto-isocaproate , 2-keto-3-methyl-valerate and 2-keto-isovalerate were degradation products of leucine , isoleucine and valine respectively . The elevations of these keto acids observed here indicated that S . japonicum infection promoted ketogenesis resulting from the degradations of the branched-chain amino acids . Such effects appeared to be similar to the infection by another schistosome species S . mansoni [28] . The marked reduction of lipoproteins observed in the plasma of S . japonicum infected mice here is broadly consistent with the results from a proteomic study [9] , which has shown that S . japonicum absorbs up to fifty host proteins . The reduction of lipoproteins can further be explained by the ability of adult schistosomes to take up the host phospholipids and triacylglycerols [50] to form a lipid tegument , which accounts for about one-third of the adult schistosomes and plays an important role in evading the host immune systems [51] . Therefore , the observed reduction of lipoproteins in the plasma of infected mice is probably a common consequence of worm developments for both S . japonicum and S . mansoni species [52] in both rodents and human [53] as well . Moreover , the infection-induced changes of in gut microbiota related metabolites such as PAG , hippurate , TMA and DMA ( Table 3 ) indicated that schistosome infection also disturbed the gut microbial ecology . This was broadly similar to the effects of infection by S . mansoni [28]–[29] , suggesting such effects as a universal consequence of schistosomiasis . Amongst the microbial related metabolites , elevations of 4-cresol glucuronide and PAG and depressed levels of hippurate appeared to be common for the hosts infected with helminths [28]–[29] and intestinal nematodes [54] . Further research is required to determine the fine-grained alterations in the microbial community associated with infection , which will enhance our understanding of three-way host-parasite-microbiota interactions . In this study , elevation of urinary 3-UP was found in mice infected with S . japonicum . Such metabolite has also been found recently in the urine samples of mice 53 days after infection by S . mansoni with the combination of NMR and capillary electrophoresis methods [55] . However , our detection of urinary 3-UP in mice at the third week of S . japonicum infection was four weeks earlier than that in the previous investigation . In addition , the levels of 3-UP was positively correlated with disease progression and worm burden ( Fig . 7 ) . Therefore , urinary 3-UP could be a potential biomarker for early diagnosis of schistosome infection . Elevated urinary 3-UP has previously been found in a case of inborn error of β-ureidopropionase deficiency [56] and reported to be a neuro-toxin [57] . The elevated urinary 3-UP in this study suggested that the schistosomal infection caused reduction of β-ureidopropionase activity thus disturbed uracil metabolism . Such alterations are also reflected with the elevation of another uracil metabolite , malonate , after infection for five weeks . The presence and specificity of 3-UP is warranted for further verification as an early diagnostic biomarker in the schistosome infected humans and other animals . In conclusion , metabonomic analyses of urinary and plasma samples were effective , with little or no invasiveness , in detecting S . japonicum infection to mice one week prior to the “gold standard” method and in distinguishing the severity of such infections in terms of worm-burdens . A good correlation of elevation of the urinary 3-UP is clearly evident with worm burden and progression . The overall metabonomic changes in plasma , urine and liver of infected animals were also associated with the time-course of S . japonicum infection . Most of the metabolic responses to S . japonicum infection were broadly similar to what previously observed to S . mansoni infection indicating the generic metabolic consequences of schistosomiasis . We further discovered the alterations of pyrimidine and lipid metabolisms induced by schistosome infection . The changed metabolites in the plasma and liver coincided with the schistosome development and were consistent with the metabolic signature of the early stage of liver damage . Our findings on mechanisms of host-parasite interaction in the disease process over time provide a new basis for development of an early diagnosis tool . Further investigation of metabolic alterations due to parasitic infections in humans is necessary to evaluate the specificity of the altered metabolites in human populations . | Schistosomiasis is an infectious disease resulting from the infection of parasitic trematode worms called schistosomes . About 600 million people are currently exposed to schistosomiasis and 200 million people are infected in about 76 countries . Current diagnostic methods are unable to detect schistosomiasis at its early stages and thus are incapable of preventing disease causing further complications . In order to understand the effects of schistosome infection on hosts' biochemistry associated with disease progression in a holistic fashion and detect the infection at the early stage , we systematically investigated the metabolite composition ( metabonome ) changes in mice biofluids and liver tissues induced by Schistosoma japonicum using NMR spectroscopy . We detected infection-induced mice metabonomic alterations at three weeks post-infection , a week earlier than traditional methods . We found that the infection-caused elevation of urinary 3-ureidopropionate was not only associated with disease progression but also worm burden . We further found that overall metabonomic changes were also closely associated with disease progression , and our methods were capable of distinguishing different levels of worm burden at week five post-infection . Our findings provided further understandings in host responses to the infection and demonstrated metabonomics as a potentially useful tool for early diagnosis of S . japonicum infections . | [
"Abstract",
"Introduction",
"Materials",
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] | [
"infectious",
"diseases/helminth",
"infections"
] | 2010 | Metabolic Changes Reveal the Development of Schistosomiasis in Mice |
Turner syndrome is caused by complete or partial loss of the second sex chromosome , occurring in ~1 in 2 , 000 female births . There is a greatly increased incidence of aortopathy of unknown etiology , including bicuspid aortic valve ( BAV ) , thoracic aortic aneurysms , aortic dissection and rupture . We performed whole exome sequencing on 188 Turner syndrome participants from the National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Related Conditions ( GenTAC ) . A gene-based burden test , the optimal sequence kernel association test ( SKAT-O ) , was used to evaluate the data with BAV and aortic dimension z-scores as covariates . Genes on chromosome Xp were analyzed for the potential to contribute to aortopathy when hemizygous . Exome analysis revealed that TIMP3 was associated with indices of aortopathy at exome-wide significance ( p = 2 . 27 x 10−7 ) , which was replicated in a separate cohort . The analysis of Xp genes revealed that TIMP1 , which is a functionally redundant paralogue of TIMP3 , was hemizygous in >50% of our discovery cohort and that having only one copy of TIMP1 increased the odds of having aortopathy ( OR = 9 . 76 , 95% CI = 1 . 91–178 . 80 , p = 0 . 029 ) . The combinatorial effect of a single copy of TIMP1 and TIMP3 risk alleles further increased the risk for aortopathy ( OR = 12 . 86 , 95% CI = 2 . 57–99 . 39 , p = 0 . 004 ) . The products of genes encoding tissue inhibitors of matrix metalloproteinases ( TIMPs ) are involved in development of the aortic valve and protect tissue integrity of the aorta . We propose that the combination of X chromosome TIMP1 hemizygosity and variants of its autosomal paralogue TIMP3 , significantly increases the risk of aortopathy in Turner syndrome .
Turner syndrome is the most common sex chromosome aneuploidy , where ~50% have a complete monosomy X and ~48% have either a partial loss , rearrangement , or mosaicism of a second X chromosome . [1] The remaining ~2% have a partial or mosaic Y chromosome . Although Turner syndrome can be compatible with life , less than 1% of Turner syndrome fetuses survive . [2] The majority of prenatal deaths are due to cardiovascular defects . [3] Live born females with Turner syndrome share a constellation of phenotypes including primary ovarian insufficiency , short stature , lymphedema , webbed neck , skeletal deformities , neurocognitive disability , and a high incidence of congenital cardiovascular malformations . In particular , they are at a greatly increased risk for having left heart obstructions including hypoplastic left heart syndrome , BAV , coarctation of the aorta , and TAA . [4] Heart defects are the major cause of premature death . The degree to which a second sex chromosome is retained is the primary determinant of the morbidity and mortality in Turner syndrome , an observation that strongly implicates X chromosomal genetics in the pathology of acquired and congenital cardiovascular disease . [5 , 6] In depth studies have shown that BAV , coarctation of the aorta , and risk for aneurysm are linked to the short arm of the X chromosome ( Xp ) . [7 , 8] BAV is a congenital malformation where the aortic valve is comprised of two leaflets as opposed to the normal three leaflet configuration . BAV is associated with lifelong heart disease including valve calcification , stenosis , aortic endocarditis , and thoracic aortic dilation ( TAD ) that has a high risk of progression to aneurysm , dissection and rupture , and premature death . It is the most common congenital heart malformation occurring in about 2% of the general population where it is predominantly found in males , which comprise about 70% of all BAV cases . [9] However , despite the prevalence in the population , little is known about the etiology of BAV . There is clearly a genetic component as 10–40% of BAV is familial . [10] BAV and aortic aneurysm are thought to have a common genetic etiology . [11] Mutations in NOTCH1[12] , GATA5[13] , and NKX2 . 5[14] have been identified as the causative factor in some families with inherited BAV , but the majority of cases remain unexplained . The sex bias in euploid BAV indicates that having two X chromosomes may be protective . In Turner syndrome the incidence of BAV is increased by at least 50-fold over that seen in the euploid population . [15] This suggests that the lack of a second X chromosome predisposes both males and Turner syndrome females to have BAV and TAA , a condition known as BAV aortopathy . Although there is a paucity of information about the etiology for BAV , a great deal is known about the pathogenic events underlying TAA and dissections associated with BAV . Numerous studies have shown significantly increased expression of matrix metalloproteinases ( MMPs ) and decreased expression of TIMPs in aneurysmal tissue . [16] This is significant because the role of MMPs is to degrade extracellular matrix ( ECM ) ; an activity that is inhibited by TIMPs . It is thought that in aneurysms the ECM in the aortic wall becomes degraded by MMPs , which weakens the aorta allowing it to succumb to hemodynamic stress thereby enlarging the diameter and thinning the aortic wall . In particular , increased expression of MMP2 and MMP9 , which degrade the collagen and elastin components of the aortic wall , and a decrease in TIMP1 , which inhibits MMP2 and MMP9 activity , have been implicated in the pathogenesis of aortic aneurysms . [16] In addition , an increased MMP9/TIMP1 ratio has been shown to be elevated in chronic aortic dissection , demonstrating a persistent role for ECM degradation . [17] Deficiency of the second sex chromosome contributes to aortopathy in Turner syndrome , but its loss is not sufficient to cause disease since ~50% of women with Turner syndrome have a normal aortic valve and aortic dimensions . We hypothesized that autosomal genetic variation sensitized by sex chromosome deficiency causes aortopathy in Turner syndrome . To address this hypothesis we used whole exome sequencing to identify autosomal genetic variation associated with BAV and TAD in Turner syndrome . We used TAD as an indicator of aneurysm formation . This study of a discovery cohort of 188 and a replication cohort of 53 individuals with Turner syndrome identified an exome-wide significant association between TIMP3 ( MIM: 188826 ) and BAV/TAD . Furthermore , investigation of the TIMP3 paralog , TIMP1 ( MIM: 305370 ) , revealed that having more than one copy of the Xp chromosome gene TIMP1 was protective against BAV/TAD . Combinatorial analysis shows a synergistic effect between having a single copy of TIMP1 plus the TIMP3 risk allele and the occurrence of BAV/TAD . Knowledge of a direct link between TIMP family-gene expression and aortopathy points the way to the development of novel biomarkers for disease progression and therapies to combat catastrophic aortic dissection and rupture in Turner syndrome .
The presence of BAV was associated with a higher aortic root ( AR ) z-score ( mean AR z-score in BAV 1 . 29 ±1 . 59 , versus no BAV 0 . 31 ± 1 . 08 , p = 0 . 0002 , mean difference = 0 . 98; Fig 1A ) . BAV was also associated with a significantly higher ascending aorta ( AAO ) z-score ( mean AAO z-score in BAV 2 . 04 ± 1 . 99 , versus no BAV 0 . 61 ± 1 . 18 , p<0 . 0001 , mean difference = 1 . 44; Fig 1B ) . SKAT-O analysis revealed that variants in TIMP3 on chromosome 22 achieved exome-wide significance for association with BAV and TAD . TIMP3 was associated with the occurrence of BAV when it was used as the sole dichotomous phenotype ( p = 1 . 58x10-6; Fig 2A ) , with the significance level increasing by an order of magnitude when BAV and AR z-scores were evaluated as covariates ( p = 2 . 27x10-7; Fig 2B ) . This demonstrates a TIMP3-driven association between BAV and aortic enlargement in Turner syndrome . The quantile-quantile plots showed that there was no departure from observed vs . expected p-values ( S1 Fig ) . Targeted exome sequencing of TIMP3 in a replication cohort also showed a significant association of TIMP3 variants with BAV and AR z-scores using SKAT-O ( p = 0 . 038; Table 1 ) . There were a total of four variants identified in TIMP3 in the discovery cohort ( Table 2 ) . Of the four variants , rs11547635 was determined to be the SNP predominantly driving the association based on the increased allele frequency in cases compared to controls ( p = 0 . 001 , chi-squared ) and evidence that the variant is deleterious based on the CADD score of 16 . 67 . This is above the recommended deleterious significance cutoff of 15 , which indicates that is in the top 5% of all damaging variants in the human genome . On the gene level , TIMP3 has a GDI PHRED score of 0 . 449 , placing in the top 10% of genes intolerant of mutations . The lead driving SNP encodes a synonymous C>T transition at p . Ser87 in exon 3 . Another SNP , rs9862 , which is a synonymous variant at p . His83 is always present along with the p . Ser87 variant in the BAV cases in this study . Importantly , these variants , which have been studied in various types of cancer are associated with reduced TIMP3 plasma levels . [18–20] In combination the two variants disrupt two core ETS1 binding consensus sequences and prevent ETS1 binding , which is thought to be the basis of the reduction in expression . [20] Our discovery that known deleterious variants in TIMP3 are significantly associated with BAV and TAD of the aortic root in Turner syndrome fits well with the known role for TIMPs in protection against aortopathy . Nearly 25% of our Turner syndrome cohort carry these SNPs , making them a significant risk genotype . The two additional TIMP3 variants , rs149161075 and rs369072080 , are rare and occur only in cases in this study . Analysis of all of the genes on Xp identified TIMP1 as the top gene meeting our aortopathy criteria , which includes the potential for escape from X-inactivation , no Y chromosome or autosome homologues , and expression in the aorta . The list of all of the genes that met the criteria is shown in Table 3 , ranked according to the likelihood that they could contribute to aortopathy . The list of all Xp genes and their characteristics can be found in S1 Table . TIMP1 polymorphically escapes X inactivation , [21] has partial functional redundancy with TIMP3[22] , and is highly expressed in the aorta with nearly 10-fold higher expression than any of the other genes ( GTExPortal ) . In addition , it is the only Xp gene that meets these criteria and has a known role in aortic valve development . [23] TIMP1 is also the only gene on Xp with a known association with aortic aneurysms in both humans and mouse models . Timp1 mouse models are susceptible to the development of aortic aneurysms[24 , 25] and TIMP1 is known to be reduced in TAA in humans . [16 , 26] Additionally , overexpression of Timp1 prevents aneurysm degradation and rupture in a rat model . [27] We therefore hypothesized that reduced copy number of TIMP1 in Turner syndrome increases the risk for BAV/TAD . Using BAV as the only variable the analysis revealed that subjects with only one copy of TIMP1 have a 4 . 50 increased odds of having a BAV than those who have greater than one copy ( p = 0 . 0009 , 95% CI = 1 . 9–11 . 8 , Fig 3A ) . When BAV with TAD was studied as the outcome , having only one copy of TIMP1 increased these odds substantially ( OR = 9 . 76 , p = 0 . 029 , CI = 1 . 91–178 . 80 , Fig 3B ) . To determine the specificity of the association between TIMP3 rs11547635 and TIMP1 copy number for having BAV/TAD or other phenotypic features , we compared cases with or without rs11547635 . Height , weight , blood pressure , body surface area , the presence of webbed neck , broad chest , primary ovarian insufficiency , hypertension , or lymphedema occurred with equal frequency in subjects with or without the rs11547635 SNP ( Table 4 ) . On the other hand BAV , BAV with TAD , coarctation of the aorta , and any aortic disease occurred with significantly higher frequency in the group with rs11547635 , indicating that it is specifically associated with aortopathy . TIMP1 copy number associations were similar but also included systolic blood pressure , lymphedema and webbed neck ( Table 5 ) . We investigated the combinatorial effect of TIMP1 and TIMP3 variation on the outcome of BAV alone , and BAV with TAD . This analysis shows that the combination of having only one copy of TIMP1 and being a carrier of TIMP3 rs11547635 specifically increases the odds for having a BAV by nearly twenty-fold ( OR = 18 . 00 , 95% CI = 5 . 19–74 . 89 , p<0 . 001 ) and also for having a BAV with TAD ( OR = 12 . 86 , 95% CI = 2 . 57–99 . 39 , p = 0 . 004 ) compared to the group with no rs11547635 and >1 TIMP1 ( Table 6 ) .
Turner syndrome , like all genetic syndromes , is characterized by a primary inherent defect that sensitizes downstream modifier genes to breach a pathologic threshold . Thus , a single triggering event is capable of unleashing a myriad of phenotypic variations . Consistent with this disease model , we found that in Turner syndrome hemizygosity of TIMP1 due to lack of a complete second X chromosome is associated with genetic variation of its paralogue , TIMP3 on chromosome 22 , synergistically heightening the risk for BAV and TAD , which is the first sign of aneurysm formation . Given the detailed understanding of the fundamental role of MMPs in thoracic aortic disease , the results of this study have clear biological relevance . In the euploid population there is a significant reduction in TIMP1 and TIMP3 expression in BAV-associated TAA and a highly significant increase in MMP2 and MMP9 , which are both regulated by TIMP1 and TIMP3 . [16] This results in a considerable MMP/TIMP imbalance in aneurysms compared to control aortas . We propose that hemizygosity for TIMP1 is the X chromosome basis for increased susceptibility for BAV and aortopathy in Turner syndrome . This coupled with a SNP-driven decrease in TIMP3 expression synergistically increases risk for both BAV and BAV with TAD . This is consistent with our hypothesis that a gene or genes on Xp interact with autosomal variants that are benign unless expressed on a genetically sensitized background such as that in Turner syndrome . The inherent decrease in TIMP1 in Turner syndrome subjects missing a complete second copy of the X chromosome sensitizes those individuals to decreased TIMP3 expression . In addition , a global methylation profile for Turner syndrome found that the Turner syndrome X chromosome has a unique methylation pattern when compared to the X chromosome of euploid males . [11] Notably , TIMP1 tends to be hypermethylated in Turner syndrome , [28] which suggests that the expression level may be decreased even beyond the reduction in copy number . Importantly , TIMP1 and TIMP3 have functional redundancy in the aorta . Both exercise inhibitory control over MMP2 and MMP9 , which are the two MMPs associated with degradation of the aortic wall . We propose that decreased TIMP1 expression due to a reduction in copy number sensitizes the aorta to MMP-induced damage , but protection is conferred by the expression of TIMP3 . Decreased expression of both negates that protection making the aortic wall vulnerable to degradation which can lead to TAD and aneurysm . In addition , TIMPs 1 and 3 are expressed in the aortic valve , where they play a role in valve remodeling , [23] which is a critical activity in the development of the tricuspid aortic valve . This fundamental link between BAV pathogenesis and downstream TAD provides a previously unrecognized mechanism for the heightened risk for aortopathy in Turner syndrome . In a study of 18 women with TS and aortic dissection , 6 cases were available for biochemical analysis , and that study showed a skewed ratio of collagen I to collagen III ( normally 30:70% ) with 60% collagen I and only 30% collagen III , [29] which could well be the end result of an altered MMP/TIMP activity . As with all studies of this nature there are some limitations and caveats . The exome sequencing was done on DNA isolated from peripheral blood , so the molecular karyotypes reflect the chromosome composition in that tissue . It is possible that the karyotype in other tissues such as the developing heart may differ , particularly with respect to mosaicism . In addition , our analyses did not include potential effects of the autosomal rearrangements found in some of the study subjects . These were genetically heterogeneous and often in single individuals , so it is unlikely that they would significantly affect the results of this study . Another limitation is that this study did not assess any potential influence of maternal genetic effects , nor did we assess the parent-of-origin of the retained X chromosome . There is no clear explanation for the strikingly higher prevalence of aortopathy in euploid men compared to women . And , the larger questions regarding the role of the sex chromosome genes in the differential susceptibility to common diseases has received little attention . Bellott and colleagues proposed that dosage differences between X chromosome genes and homologous ancestral genes retained on the Y chromosome may account for phenotypic differences between men and women . [30] Our data supports another model where expressed genes that escape inactivation on the second X chromosome and that are also absent from the Y chromosome ( like TIMP1 ) play a role in the frequently observed sex bias in disease . In conclusion , we propose that aortopathy in Turner syndrome results from an inherent dysregulation of the TIMP/MMP ratio . This imbalance increases risk for both congenital cardiovascular defects and later onset aortic disease . Beyond Turner syndrome , the lack of a second copy of TIMP1 in euploid males may also explain the increased risk for BAV/TAD compared to euploid females . The findings of this study represent a significant advance in the understanding of the mechanisms underlying aortopathy in Turner syndrome .
The Turner syndrome cohort was accessed from the National Registry of Genetically-Triggered Thoracic Aortic Aneurysms and Related Conditions ( GenTAC ) . [31] GenTAC study subject recruitment was approved by the institutional review board for each member of the GenTAC investigative team , and informed consent for participation in associated research studies was obtained for each study subject . The project was approved by the Oregon Health & Science University institutional review board . The Danish cohort was approved by the Central Denmark Region Ethical Scientific Committee ( #2012-500-12 ) and registered at ClinicalTrials . gov ( #NCT01678274 ) . GenTAC spent a decade recruiting study subjects with conditions related to thoracic aortic aneurysms , including collection of biospecimens , rigorous evaluation and documentation of clinical data , and collection of follow-up data for longitudinal studies . The majority of subjects enrolled in GenTAC had aorta imaging studies that provide information on aortic dimensions and evaluation of aortic valve status . All images , such as echocardiograms , CT and MRT studies were collected clinically , but transferred to the GenTAC imaging core ( ICORE ) for re-evaluation by a single cardiac imaging expert for consistency of measurements and interpretation . [32] The discovery cohort for this study was composed of Turner syndrome study subjects of Northern European ( non-Finnish ) descent . Inclusion criteria included a diagnosis of Turner syndrome , self-reported race as white , ethnicity as non-Hispanic , evaluation for a diagnosis of BAV , and availability of aortic dimension measurements and body morphometrics . The diagnosis of BAV was based on clinical images and interpretations . An additional 53 study subjects from a prospective study in Denmark were used as an independent replication cohort . [33 , 34] For the purposes of this study we defined aortopathy ( cases ) as those having a BAV with or without TAD . In keeping with clinical norms for Turner syndrome , a thoracic aortic dimension z-score ≥ 1 . 9 was used as the definition of TAD as an indicator of aneurysm formation . All study subjects were confirmed for a diagnosis of Turner syndrome based on either clinical karyotype or exome sequence-based karyotyping . Subjects were phenotyped for presence of a BAV or a normal aortic valve . Our final Turner syndrome discovery cohort was composed of 88 cases ( Turner syndrome with BAV ) and 100 controls ( Turner syndrome with no BAV ) . Within this cohort , 113 subjects had aortic root ( AR ) dimensions and 106 subjects had ascending aorta ( AAO ) dimensions . For the replication cohort 14 had a BAV and 39 had a normal aortic valve . For all subjects AAO and AR diameters were converted into z-scores using methodology that was specifically developed for children and adults with Turner syndrome to correct for the altered longitudinal growth in Turner syndrome . [35] Briefly , the regression equations and coefficients were used to calculate expected aortic dimensions based on body surface area ( BSA , Haycock formula ) for each individual in the study with a measurement ( Eqs 1&2 ) . The z-scores were calculated by comparing expected aortic dimensions to actual aortic dimensions and incorporating the mean squared error ( MSE; Eq 3 ) . [35] Expected aortic dimension data points and lines were generated for each z-score . Equations: AorticRootequation: ( expected ) 2= ( 1 . 035+ ( 0 . 589*BSA ) + ( −0 . 129*BSA2 ) ) 2 ( 1 ) AscendingAortaequation: ( expected ) 2= ( 0 . 942+ ( 0 . 593*BSA ) + ( −0 . 122*BSA2 ) ) 2 ( 2 ) Z-scoreequation:= ( √ ( actualdimension ( cm ) −√ ( expecteddimension ( cm ) ) / ( √ ( MSE ) ) ( 3 ) The BSA ( m2 ) vs . AR or AAO ( cm ) for BAV cases ( triangle ) and BAV controls ( square ) were plotted . Overlaid on the same plot are the polynomial trend lines for z = 0 , z = 1 , z = -1 , z = 2 , z = -2 , z = 3 , z = -3 ( S2 Fig ) . In total , 215 genomic DNA samples isolated from peripheral blood were submitted for exome sequencing and the exome capture kit Roche Nimblegen SeqCap EZ was used to prepare the sequencing libraries . Whole exome sequencing ( WES ) was performed by the NHLBI Resequencing & Genotyping Service at the University of Washington ( D . Nickerson , US Federal Government contract number HHSN268201100037C ) . In summary , 16 samples failed post-sequencing QC and 199 samples passed post-sequencing QC . The average read depth for the targeted exome was 71X , with 86% of the target regions covered at greater than 20X . Reads were mapped to the hg19 UCSC genome build using the Burrows-Wheeler aligner , version 0 . 7 . 10 . Variants were called using the GATK best practices pipeline , where in the 199 samples , 195 , 034 variants were called . BAM files and VCF files were transferred to the Maslen lab for evaluation . Data cleaning and filtering was performed using PLINK v1 . 90b3g[36] , which 1 ) removed any variants with less than 99% genotyping rate , where 6 , 815 variants were removed; 2 ) removed individuals with more than 5% missing genotypes , where no individuals were removed; 3 ) excluded markers that fail the Hardy-Weinberg equilibrium test using a threshold of 1 . 0x10-6 , where 2 , 334 variants were removed . A principal components analysis ( PCA ) was performed using the R package SNPRelate to calculate the eigenvectors ( EVs ) for each subject . [37] Data were prepared for PCA analysis by taking common SNPs ( MAF >5% ) and pruning out SNPs in linkage disequilibrium with an r2 > 0 . 2 , stepping along five SNPs at a time within 50kb windows . We plotted EV1 vs EV2 to look for population outliers ( S3A Fig ) . Population outliers were removed and the analysis was repeated a total of four times until no more outliers remained ( S3B Fig ) . In total , 11 subjects were detected at EV1 < -0 . 3 and EV2 > 0 . 3 and were removed from the dataset . Additionally , we use the first three eigenvectors as covariates in most downstream analysis . The final dataset contained 185 , 885 variants across 188 subjects , providing a total genotyping rate of 0 . 998084 . To enhance the probability of identifying an exome-wide significant signal a gene-based burden test , the optimal sequence kernel association test ( SKAT-O ) , was used to evaluate the data . [38] This analysis clusters variants into genes for a gene by phenotype analysis , which improves signal strength for exome data from smaller cohorts as it reduces the multiple testing burden . This state-of-the-art approach is particularly useful for studies of rare disorders such as Turner syndrome . The 185 , 885 variants which passed QC from the WES pipeline were assigned to their respective genes using hg19_refGene . Variants were allowed to be in more than one gene since the test compares gene burden in the same gene , not between different genes . All analyses included the first three principal component eigenvalues as covariates to adjust for any underlying population structure . First , SKAT-O was used to test for an association with the dichotomous BAV status . Second , SKAT-O was used to test for an association with BAV and aortic diameter z-scores as a proxy for TAD evaluated as a continuous variable . For each analysis , a quantile-quantile ( Q-Q ) plot was generated to look for departure of the observed p-values from the expected p-values . Combined Annotation Dependent Depletion ( CADD ) scores were used as a tool for scoring the deleteriousness of the genetic variants identified in exome sequencing data . PHRED-scaled CADD scores integrate multiple annotations into a single metric that outperforms other commonly used algorithms of this type . A CADD score ≥20 indicates that a variant is among the top 1% most deleterious variants in the human genome . We used the recommended cutoff score of ≥15 as our threshold for considering a variant to be likely deleterious . The allele frequency of each variant was queried in the Exome Aggregation Consortium ( ExAC ) database of exome data from over 60 , 000 unrelated individuals , from which we used the European non-Finnish population . [39] All variants with alleles that were overrepresented in cases were validated by Sanger sequencing . For the replication cohort , we performed targeted Sanger sequencing of all TIMP3 exons and followed the same SKAT-O association test as described above . X and Y chromosome information from the WES data was used to assess the presence of any second sex chromosome . X and Y SNP plots were generated for each study subject and compared to control reference plots to define the second sex chromosome status for each individual . [40] Alternate allele frequencies from the exome variant calls were used to create SNP plots . Briefly , the alternate allele frequencies were calculated for all variants on the X chromosome and sorted by position for each subject . In R , scatter plots were generated and evaluated for the presence of a second X chromosome . This was repeated for the Y chromosome and the Integrative Genome Viewer ( IGV ) was used to confirm the presence of Y chromosome reads . [40] Reference plots of a control female with 46 , XX karyotype , a control female with 45 , X karyotype , and a control male with 46 , XY karyotype were generated ( S4A Fig ) . We then generated X and Y chromosome plots for each subject in this study . In these plots , the X-axis is sorted by position on the X chromosome and the Y-axis is the alternate ( ALT ) allele frequency . As expected for a 46 , XX karyotype , some SNPs are homozygous for the ALT allele ( 1 . 0 ) , homozygous for the reference ( REF ) allele ( 0 . 0 ) , or heterozygous for the ALT/REF allele ( 0 . 5 ) . In contrast , a 45 , X karyotype only has SNPs that are homozygous for the ALT allele , or homozygous for the REF allele because only one copy is present . The 46 , XY karyotype looks similar to the 45 , X plot , but has SNPs heterozygous for the ALT/REF allele clustered in the captured pseudoautosomal ( PAR ) region . The presence of any Y chromosome material was confirmed using IGV . Available clinical karyotypes were compared to molecular karyotypes generated from the SNP data and basic second sex chromosome status groups were created to categorize the study subjects . While the majority of subjects were true monosomy 45 , X , examples of other karyotypes included Xp deletions , Xq deletions , Xq isochromosomes , and X chromosome rings for their second X chromosome ( S4B Fig ) ; mosaicism for the second X chromosome , either 45 , X/46 , XX or 45 , X/47 , XXX , or mosaicism for Y chromosome material ( S4C Fig ) , although we were unable to quantify the Y mosaicism level based on the plots . While most plots were straight forward in their interpretation , some were more complicated . In those cases , the clinical karyotype was relied upon . To assess the mosaicism observed in a large number of subjects , a model was created to predict the percent 45 , X mosaicism based on alternate allele frequencies ( S5 Fig ) . The equations from each model were used , where y is the percent 45 , X mosaicism and x is the alternate allele frequency . The average of the upper and lower predicted values was used as the final estimate of 45 , X mosaicism . The molecular karyotypes and estimated TIMP1 copy number based on the percentage of cells with a second X chromosome are shown in Table 7 . Genes on Xp were evaluated to identify candidates likely to contribute to aortopathy . We hypothesized that an aortopathy gene would be found on Xp , would escape X inactivation in euploid females , [41–43] would be expressed in the aortic wall , and would not be a pseudogene , or have a Y homologue . To calculate the magnitude of the association between BAV status and aortic z-score , a linear regression model was fit where BAV was the predictor and aortic z-score was the response variable . This was performed separately for both AR z-score and AAO z-score . The mean differences and 95% confidence intervals were generated to accompany p-values . Boxplots for each AR and AAO z-scores were plotted against BAV status . To investigate if the TIMP3 paralog TIMP1 was associated with BAV , a general logistic regression model was performed where TIMP1 copy number was the categorical predictor , 1 copy and >1 copy of TIMP1 were the variables , and BAV status or BAV with TAD was the response variable with no BAV serving as the reference . Odds ratios and 95% confidence intervals were generated to accompany p-values . To investigate the combination of the TIMP3 variant rs11547635 and TIMP1 as risk factors for the presence of a BAV or BAV with TAD , four groups were formed: 1 ) no TIMP3 rs11547635 and >1 copy of TIMP1 , 2 ) with TIMP3 rs11547635 and >1 copy of TIMP1 , 3 ) no TIMP3 rs11547635 and only 1 copy of TIMP1 , and 4 ) with TIMP3 rs11547635 and only 1 copy of TIMP1 . Separate general logistic regression models were created to compare these four groups in order to determine their associations with BAV , or the combination of BAV and TAD . Odds ratios and 95% confidence intervals were generated to accompany p-values . Other physical attributes of Turner syndrome were studied to determine if any were also associated with the TIMP3 rs11547635 risk allele . Continuous variables ( height , weight , body surface area , systolic blood pressure , and diastolic blood pressure ) were analyzed using a Student’s two-sample t-test , where the means of those with or without TIMP3 rs11547635 were compared . Categorical variables ( lymphedema , broad chest , webbed neck , primary ovarian insufficiency , hypertension , coarctation of the aorta , bicuspid aortic valve , and any aortic risk factor ) were analyzed using a Chi-squared test with Yate’s correction or Fisher’s exact test as appropriate . The same analysis was done using TIMP1 copy number as the variable . | BAV is the most frequent congenital heart defect , occurring in about 1–2% of the population with 70% of cases occurring in males . BAV increases risk for thoracic aortic aneurysm ( TAA ) and early death . Approximately 30% of individuals with Turner syndrome have BAV/TAA , making this an important population for the study of this disease . Given that individuals with Turner syndrome are missing a complete or partial second sex chromosome , it is presumed that X chromosome genes are involved in causing the defect . This is consistent with the bias towards occurrence in euploid males . However , not everyone with Turner syndrome has a BAV , so we hypothesized that autosomal genes may also play a role . Using whole exome sequencing we have shown that deleterious variation in TIMP3 is associated with BAV and indices of TAA . We further found that there is a synergistic interaction between loss of the X chromosome gene , TIMP1 , and deleterious variation in TIMP3 that significantly increases that risk . TIMP1 and TIMP3 play roles in aortic valve morphogenesis and in stabilizing the aortic wall , loss of which leads to TAA . Hence our findings have implications for understanding the cause of BAV/TAA in all populations and as a potential therapeutic target . | [
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] | 2018 | TIMP3 and TIMP1 are risk genes for bicuspid aortic valve and aortopathy in Turner syndrome |
Knowledge of biological relatedness between samples is important for many genetic studies . In large-scale human genetic association studies , the estimated kinship is used to remove cryptic relatedness , control for family structure , and estimate trait heritability . However , estimation of kinship is challenging for sparse sequencing data , such as those from off-target regions in target sequencing studies , where genotypes are largely uncertain or missing . Existing methods often assume accurate genotypes at a large number of markers across the genome . We show that these methods , without accounting for the genotype uncertainty in sparse sequencing data , can yield a strong downward bias in kinship estimation . We develop a computationally efficient method called SEEKIN to estimate kinship for both homogeneous samples and heterogeneous samples with population structure and admixture . Our method models genotype uncertainty and leverages linkage disequilibrium through imputation . We test SEEKIN on a whole exome sequencing dataset ( WES ) of Singapore Chinese and Malays , which involves substantial population structure and admixture . We show that SEEKIN can accurately estimate kinship coefficient and classify genetic relatedness using off-target sequencing data down sampled to ~0 . 15X depth . In application to the full WES dataset without down sampling , SEEKIN also outperforms existing methods by properly analyzing shallow off-target data ( ~0 . 75X ) . Using both simulated and real phenotypes , we further illustrate how our method improves estimation of trait heritability for WES studies .
Understanding biological relatedness plays a central role in quantitative genetic studies of heritable traits and diseases . For example , complete pedigree information is required for linkage analysis and family-based association studies . In population-based association studies , inference of genetic relatedness is a routine practice in quality control because cryptic relatedness is a major confounding factor that can lead to spurious association signals . The estimated pairwise relatedness matrix is often used to model phenotype covariance through mixed models for both quantitative traits [1–3] and case-control studies [4] . Such mixed model approaches have been widely used to control for population and family structure in association tests [1–4] and to estimate heritability for traits of interests [5 , 6] . Genetic relatedness between samples can also be leveraged to improve imputation of missing phenotypes and thus boost the statistical power of multiple-phenotype association studies [7 , 8] . In addition to quantitative genetics , inference of genetic relatedness has broad applications in many other areas , including forensics , agriculture , evolution , and ecology [9] . Kinship coefficient , defined as the probability that two homologous alleles drawn from each of two individuals are identical by descent ( IBD ) , is a classic measurement of relatedness [10 , 11] . While kinship coefficients can be derived from pedigree , many estimators based on the maximum likelihood method or the method of moments have been developed to estimate kinship coefficients from genotype data , especially in population-based studies in which pedigree information is not available or inaccurate . While likelihood estimators [12–14] are powerful to test the hypothesized relationships , moment estimators [15–17] are widely used due to their computational efficiencies in large datasets . Two popular moment estimators that assume random mating in a homogeneous sample have been implemented in the KING [18] and GCTA [5] programs . These homogeneous estimators , however , can produce biased estimation in the presence of population structure [13 , 18 , 19] . Such bias might be corrected by modeling the drift of allele frequencies in the subpopulation where both individuals come from [13 , 19] . While KING has a robust estimator ( KING-rob ) for samples with population structure , it does not perform well in analyzing admixed samples , in which two related individuals might have different ancestry background [20 , 21] . Two moment estimators , REAP [20] and PC-Relate [21] , and a likelihood estimator , RelateAdmix [22] , have been proposed for kinship estimation in admixed samples . These methods account for different ancestry background of admixed individuals using individual-specific allele frequencies derived from either model-based methods for population structure analysis , such as ADMIXTURE [23 , 24] , or principal components analysis ( PCA ) [25] . These existing kinship estimators require accurate genotype data across genome-wide SNPs , which may not be available in next-generation sequencing studies . The shallow whole-genome sequencing design is widely used in large population-based studies , in which individual genotypes might be inaccurate but the statistical power for association tests is optimized as the sample size increases [26–28] . Additionally , due to sample quality , shallow sequencing data are typical from studies of wild animals , forensics , and ancient human DNA [29–31] . Target sequencing is another widely used design in human genetic studies by focusing on candidate loci of interests or the whole exome [32–37] . More than 60 , 000 exomes from over 20 studies have been contributed to the Exome Aggregation Consortium ( ExAC ) Browser [36] . In target sequencing studies , accurate genotypes are only available for the deeply-sequenced target regions , which often do not have enough SNPs to infer either individual ancestry or pairwise genetic relatedness , posting a limitation to control for major confounding factors of population structure and family relatedness . The vast off-target regions are typically covered by ~0 . 1-1X sequence reads , which are byproducts of target sequencing due to imperfect capture technologies . We have developed a method called LASER that can utilize the off-target reads to accurately infer an individual’s genetic ancestry background [38 , 39] . Estimation of pairwise relatedness remains challenging because the analysis requires both individuals to have data across a common set of SNPs , which are very few because off-target reads are sparse . For example , if each individual have ~10% of their off-target SNPs covered by some reads , there will be only ~1% ( = 0 . 12 ) of SNPs sequenced in both individuals . Furthermore , there is huge genotype uncertainty at these SNPs due to extremely low sequencing depth . Recently , a likelihood method called lcMLkin has been proposed to estimate kinship from shallow sequencing data by explicitly modeling the uncertainty [40] . However , lcMLkin assumes Hardy-Weinberg equilibrium ( HWE ) and thus cannot be applied to samples with population structure and admixture . In this paper , we develop a new method called SEEKIN ( SEquence-based Estimation of KINship ) to estimate kinship using sparse sequence reads . The key rationale is that even though the number of SNPs sequenced in both of a pair of individuals is small , neighboring SNPs in the genome are often correlated due to linkage disequilibrium ( LD ) . With large amounts of existing whole genome sequencing ( WGS ) data , such as the 1000 Genomes Project [28] , we can leverage LD to call genotypes with probabilities across majority of the SNPs in each individual , including SNPs that are not even sequenced [41] . Such an approach has been implemented in many phasing and imputation programs , which are widely used in genome-wide association studies ( GWAS ) [42–45] . Through imputation , we can substantially increase the number of SNPs shared by any two individuals , thereby making it possible to estimate pairwise relatedness . We model the genotype uncertainty [46] and propose two moment estimators of kinship; one for homogeneous samples and the other for heterogeneous samples with population structure and admixture . We evaluate our method using whole-exome sequencing ( WES ) and array genotyping data for 762 related individuals from the Singapore Living Biobank Project , which include Chinese and Malays with substantial amount of admixture . We show that our method can accurately estimate kinship coefficient for both homogeneous and heterogeneous samples even when the sequencing depth is as low as ~0 . 15X , while existing methods show strong downward bias . Compared to results based on high-coverage target regions in WES , which are ~1 . 5% of the genome , our method also improves kinship estimation and the subsequent heritability estimation by properly utilizing data from off-target regions . While SEEKIN is developed for sparse sequencing data , it is also applicable to high-quality genotyping data , for which our estimators reduce to the PC-Relate estimators [21] . We have implemented SEEKIN in an efficient multithreading program , which is publically available at https://github . com/chaolongwang/SEEKIN/ .
A typical genotype calling pipeline involves SNP discovery and genotype inference . In this study , we skipped the SNP discovery step by focusing on biallelic autosomal SNPs that have MAF>0 . 05 in the 1000 Genomes Project Phase 3 ( 1KG3 ) dataset [28] . Given BAM files of N individuals , we computed genotype likelihoods across the 1KG3 SNPs using the mpileup option in samtools , after filtering reads with mapping quality <30 and base quality <20 [47] . Based on genotype likelihoods , we used three different strategies to generate genotype call sets for downstream analyses . In the first strategy , we used the default settings of bcftools to call genotypes without using any LD information [48] . We set to missing at genotype entries with no read support and filtered SNPs with quality score QUAL<30 or MAF<0 . 05 . In the second strategy , we used BEAGLE ( v4 . 1 ) to call genotypes by taking genotype likelihoods as the inputs ( using the gl option ) [45] . This strategy leverages the LD information shared among N study individuals to improve calling accuracy . In the third strategy , we included 5 , 008 haplotypes from 1KG3 as the external reference for BEAGLE to improve phasing and genotyping accuracy . We chose BEAGLE because most other imputation programs take genotypes as the input without accounting for genotype uncertainty associated with shallow sequencing data . We set niterations = 0 in BEAGLE to use its v4 . 0 phasing algorithm because we found that the genotype probabilities produced by the new algorithm in BEAGLE v4 . 1 were not well calibrated for shallow sequencing data . For the BEAGLE call sets , we filtered SNPs with dosage r2<0 . 5 or MAF<0 . 05 . We propose kinship estimators for shallow sequencing data based on the imputed dosage ( i . e . , expected genotypic value given the posterior genotype probabilities ) and the estimated dosage r2 at each SNP , both of which are obtained from BEAGLE . We first describe the relationship between imputed dosages and true genotypes , and then derive kinship estimators for homogeneous samples and for samples with population structure and admixture . Suppose N individuals from a population are genotyped at M biallelic SNPs . Let Gim = 0 , 1 or 2 denote the copies of the alternative allele at the mth SNP of the ith individual . The expected value for Gim is E ( Gim ) = 2pm for all i = 1 , 2 , … , N where pm is the population allele frequency at the mth SNP . For commonly used genotype imputation programs , Hu et al . [46] derived the expectation of the imputed dosage G˜im given true genotype Gim and the mean genotype G¯Rm in the imputation reference panel as E ( G˜im|Gim , G¯Rm ) = ( 1−rm2 ) G¯Rm+rm2Gim , ( 1 ) where rm2 is the squared correlation between the true genotypes and the imputed dosages at the mth SNP . Under iterated expectations for Eq ( 1 ) , the mean of imputed dosage is 2p˜m=E ( G˜im|G¯Rm ) = ( 1−rm2 ) G¯Rm+2rm2pm . ( 2 ) Note that rm2 can be estimated without knowing the true genotypes and is widely used to measure imputation accuracy [42 , 43] . We let rm2^ denote the estimate of rm2 throughout the rest of the paper . To estimate kinship coefficient ϕij between individuals i and j using genotypes , Yang et al . [5] proposed the genetic relationship estimator: 2ϕ^ij=1|Sij|∑m∈Sij2ϕ^ijm=1|Sij|∑m∈Sij ( Gim−2pm ) ( Gjm−2pm ) 2pm ( 1−pm ) , ( 3 ) where Sij is the set of SNPs in the sample with genotypic information for both individuals , and |Sij| is the number of SNPs in this set . Assuming independence across loci , ϕ^ij is a consistent estimator of ϕij with |Sij|→∞ [18] . The precision of ϕ^ij given in Eq ( 3 ) can be improved by averaging over more loci when high quality genotypes are available . For shallow sequencing data , however , a direct substitution of the imputed values ( G˜im , G˜jm ) for ( Gim , Gjm ) in Eq ( 3 ) could lead to bias in kinship estimation when ignoring the genotype uncertainty . Given Eqs ( 1 ) and ( 2 ) , we propose the following kinship estimator at the mth SNP: 2ϕ˜ijm= ( G˜im−2p˜m ) ( G˜jm−2p˜m ) 2p˜m ( 1−p˜m ) ( rm2^ ) 2 , i≠j , ( 4 ) where p˜m is defined by the first equity of Eq ( 2 ) and can be estimated as 12N∑i=1NG˜im . Based on Eq ( 2 ) , we further have pm=p˜m− ( G¯Rm−2p˜m ) ( 1−rm2^ ) /rm2^ . Because ( G¯Rm−2p˜m ) ( 1−rm2^ ) /rm2^ is small when the reference panel has similar allele frequency as the imputed samples or when rm2^ is close to 1 , we assume pm=p˜m unless otherwise noted . Therefore , the main difference between ϕ˜ijm and ϕ^ijm in Eq ( 3 ) is a scaling factor of ( rm2^ ) 2 in the denominator , reflecting the observation that the imputed dosages have smaller variance than the true genotypes [46] . When rm2^ goes to 0 for a poorly imputed SNP , the numerator of ϕ˜ijm also goes to 0 because all individuals are imputed as G¯Rm based on Eq ( 1 ) , but the expectation of ϕ˜ijm remains the same . We show in S1 Text that ϕ˜ijm share the same expectation with ϕ^ijm under the assumption that the residuals of Eq ( 1 ) for two different individuals i and j are independent . When the true genotypes are observed , we have ( G˜im , G˜jm ) = ( Gim , Gjm ) and rm2^ = 1 so that ϕ˜ijm reduces to ϕ^ijm . We also propose the following estimator of self-kinship coefficient at the mth SNP: 2ϕ˜iim= ( G˜im−2p˜m ) 22p˜m ( 1−p˜m ) rm2^ . ( 5 ) We show in the S1 Text that ϕ˜iim has the same expectation as ϕ^iim and is an unbiased estimator for ( 1+fi ) /2 , where fi is the inbreeding coefficient of the ith individual . In practice , to obtain a genome-wide relationship between individuals i and j , we combine ϕ˜ijm across SNPs using a weighted average: ϕ˜ij=∑mwmϕ˜ijm∑mwm . ( 6 ) Specific choices of weights wm generally affect the precision of the estimator but not its expectation . A typical choice is the inverse-variance weighting scheme , which minimizes the sampling variability . We show in S1 Text that the variance of ϕ˜ijm is inversely proportional to ( rm2^ ) 2 when individuals i and j are unrelated . Furthermore , it has been suggested that down-weighting low-frequency variants can lead to more stable estimation when aggregating information across SNPs [21 , 49] . Therefore , we propose wm=2p˜m ( 1−p˜m ) ( rm2^ ) 2 , which intuitively down weighs SNPs of poor imputation quality or of low MAF . Under this weighting scheme , our genome-wide kinship estimator for homogenous samples is 2ϕ˜ij={∑m ( G˜im−2p˜m ) ( G˜jm−2p˜m ) ∑m2p˜m ( 1−p˜m ) ( rm2^ ) 2 , i≠j∑m ( G˜im−2p˜m ) 2rm2^∑m2p˜m ( 1−p˜m ) ( rm2^ ) 2 , i=j . ( 7 ) We denote ϕ˜ij in Eq ( 7 ) as the SEEKIN-hom estimator . In the presence of population structure and admixture , the population allele frequency pm is no longer able to reflect distinct ancestry backgrounds of the individuals . Several existing methods replace population allele frequency pm with individual-specific allele frequency pim , which is the expected allele frequency given the ancestry of individual i [20–22] . For example , the PC-Relate method uses the following estimator: 2ϕ^ij=∑m ( Gim−2pim ) ( Gjm−2pjm ) ∑m2pim ( 1−pim ) pjm ( 1−pjm ) , ( 8 ) where the individual-specific allele frequencies pim and pjm are estimated using linear predictors of top PCs [21 , 25] . Other methods , including REAP [20] and RelateAdmix [22] , derive individual-specific allele frequencies from model-based ancestry estimation programs such as ADMIXTURE [23] . However , neither PCA nor ADMIXTURE can be applied directly to sparse sequencing data . We propose using LASER [38 , 39] , a method that we previously developed for both shallow sequencing and genotyping data , to estimate the top PCs of each study individual in a reference ancestry space . The estimated PCs can be used to predict individual-specific allele frequencies . Briefly , we first apply PCA on genotyping data of a set of reference individuals to construct an ancestry space using the top K PCs , recorded as V = [V1 , … , VK] . Let Gm be a column vector of genotypes at the mth SNP for the reference individuals . We obtain the least squares solution β^m= ( β^m0 , … , β^mK ) of the linear model E ( Gm|V ) = [1 , V]βm for each SNP . For each sequenced individual i , we use LASER to estimate the PC coordinates in the reference ancestry space , denoted as v^i= ( v^i1 , … , v^iK ) , in which v^ik is the coordinate of the kth PC [39] . Similar to PC-Relate [21] , we can estimate the allele frequency for individual i at the mth SNP as p^im=12 ( β^m0+∑k=1Kβ^mkv^ik ) . To avoid out of boundary values , we force p^im to be 0 . 001 or 0 . 999 when p^im<0 . 001 or p^im>0 . 999 , respectively . With the estimated individual-specific allele frequencies , we propose the following kinship estimator at the mth SNP for samples with population structure and admixture: 2ϕ˜ijm= ( G˜im−2u˜im ) ( G˜jm−2u˜jm ) 2p^im ( 1−p^im ) p^jm ( 1−p^jm ) ( rm2^ ) 2 , i≠j , ( 9 ) where u˜im=p˜m+rm2^ ( p^im−p^m ) and p^m=1N∑ip^im . Analogous to Eq ( 5 ) , the self-kinship coefficient at the mth SNP can be estimated as: 2ϕ˜iim= ( G˜im−2u˜im* ) 22p^im ( 1−p^im ) rm2^ , ( 10 ) where u˜im*=p˜m+rm2^ ( p^im−p^m ) . The terms u˜im and u˜im* can be interpreted as the adjusted individual-specific allele frequencies that account for the imputation accuracy and the shift of allele frequency from the sample average p˜m due to individual ancestry background . Intuitively , the shift should be proportional to ( p^im−p^m ) , reflecting the deviation in allele frequency of an individual from the sample mean . The scaling factors of rm2^ in u˜im and rm2^ in u˜im* are chosen such that our proposed estimators in Eqs ( 9 ) and ( 10 ) have the same expectations as the PC-Relate estimator in Eq ( 8 ) when individual-specific allele frequencies are accurately estimated ( S1 Text ) . To combine information across genome-wide SNPs , we use the same weighting scheme as the case for the homogeneous samples ( Eq 7 ) but replace population allele frequencies with individual-specific allele frequencies , i . e . wm=2p^im ( 1−p^im ) p^jm ( 1−p^jm ) ( rm2^ ) 2 . Therefore , our proposed kinship estimator for samples with population structure and admixture is 2ϕ˜ij={∑m ( G˜im−2u˜im ) ( G˜jm−2u˜jm ) ∑m2p^im ( 1−p^im ) p^jm ( 1−p^jm ) ( rm2^ ) 2 , i≠j∑m ( G˜im−2u˜im* ) 2rm2^∑m2p^im ( 1−p^im ) ( rm2^ ) 2 , i=j ( 11 ) When all variants are genotyped or well imputed ( rm2^→1 ) , we have p˜m≈p^m and u˜im≈u˜im*≈p^im for m = 1 , 2 , … , M . Our estimator ϕ˜ij reduces to the PC-Relate estimator ϕ^ij ( Eq 8 ) except that our individual-specific allele frequencies are estimated based on coordinates derived from LASER instead of the PCAiR method [25] . We denote ϕ˜ij in Eq ( 11 ) as the SEEKIN-het estimator . We implemented our SEEKIN estimators into a multithreaded C++ program . The program accepts input files in a standard compressed VCF format . The genotype VCF file can be obtained from BEAGLE , which include genotypes , imputed dosages , and rm2^ for all SNPs . For the SEEKIN-het estimator , SEEKIN requires an additional VCF file that stores the individual-specific allele frequencies . Our program includes a data preparation module to generate the individual-specific allele frequency file and a main module to compute kinship coefficients . To balance computational speed and memory usage , the main module adopts a “single producer/consumer” design pattern ( S1 Fig ) . Briefly , a single-threading “producer” job scans the input files , extracts required information for each SNP , and packs into a data block for every L SNPs . Concurrently , a “consumer” job takes the data blocks one by one and performs computation . We simultaneously compute all elements in a kinship matrix of N individuals by adopting matrix representations of the estimators in Eqs ( 7 ) and ( 11 ) . Our implementation uses the Armadillo C++ library [50] , which provides multithreading and highly efficient matrix computation . The required memory of SEEKIN scales as O ( N2L ) . The block size L can be specified by users according to the available computational resource , making our software scalable to large datasets . The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals , for the purpose of phenotype recall study of high-impact variant carriers . These individuals are sampled from two studies: Multi-Ethnic Cohort ( MEC ) , and the Singapore Health 2012 ( SH2012 ) . The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups ( Chinese , Malay , and Indian ) . The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013 , with over-sampling of Malays and Indians [51] . Participants in MEC and SH2012 completed a similar set of questionnaire components , health examination , and biochemisty panels . Description of the MEC and SH2012 studies can be found at http://blog . nus . edu . sg/sphs/ . The National University of Singapore Institutional Review Board approved the Living Biobank Project ( Approval No . : NUS 2585 ) . All participants provided written informed consent . In total , 1 , 299 self-reported Chinese and 1 , 229 self-reported Malays were whole-exome sequenced on the Illumina HiSeq2000 platform ( 125bp paired end ) . The exonic regions were captured using the Nimblegen SeqCap EZ Exome v3 kits . We aligned sequence reads to the human reference genome ( GRCh37 ) using BWA-MEM [52] , followed by base quality score recalibration and removal of duplicated reads [53] . The mean depth of raw reads aligned to the target regions was ~32X . After excluding reads with mapping quality score <30 and base quality score <20 , the mean sequencing depths across target and off-target regions were ~20X and ~0 . 75X , respectively . We focused on off-target data in our evaluation of low-coverage settings . In addition , we used samtools [47] to down sample 20% of the off-target data , which was ~0 . 15X , to mimic a typical off-target coverage in studies that sequence small target regions rather than the whole exome [33 , 38] . Among the sequenced individuals , we have array genotyping data for 2 , 452 individuals ( Illumina OmniExpress-24 ) . After excluding SNPs with call rate <0 . 95 , HWE P<10−5 in either Chinese or Malay , or minor allele frequency ( MAF ) <0 . 01 , we retained 595 , 668 autosomal SNPs . We jointly analyzed the array genotyping data of 2 , 452 individuals from the Singapore Living Biobank Project with 268 individuals from the Singapore Genome Variation Project ( SGVP ) [54] . The SGVP includes 96 Chinese , 89 Malays , and 83 Indians , who were genotyped on Affymetrix 6 . 0 and Illumina Human1M arrays , totaling 1 , 141 , 519 autosomal SNPs with MAF>0 . 05 . Based on 435 , 314 overlapping SNPs , we estimated the genetic ancestry background of the Living Biobank samples using ADMIXTURE and LASER [23 , 39] , both including the SGVP dataset as reference . For the ADMIXTURE analysis , we used the supervised mode and set the number of clusters K = 3 because Singapore has three major ethnicity groups . We plotted results from ADMIXTURE using CLUMPAK [55] . The LASER method can analyze either genotypes or sequence reads to infer an individual’s ancestry in a reference ancestry space [39] . We used the default settings of the trace program in LASER to place the Living Biobank samples in the ancestry space generated by the first two principal components ( PCs ) of the SGVP individuals . We applied PC-Relate [21] to the array genotyping data to estimate both kinship coefficients and the probability of zero IBD sharing . Using the criteria in [18] , we identified 736 pairs of close relatedness ( ≤3rd degree ) , involving 263 Chinese and 499 Malay individuals . In this paper , we focused on these 762 individuals to evaluate different kinship estimators on low-coverage sequencing data . Because pedigree information was not collected , we used the kinship coefficients estimated by PC-Relate on the array genotyping data as the gold standard for comparison . We evaluated the impacts of kinship estimation on downstream analysis of trait heritability based on 762 related individuals from the Singapore Living Biobank Project . We first simulated quantitative traits using a linear mixed model y ∼ N ( 0 , 2Φ + I ) , where Φ is the kinship matrix estimated by PC-Relate on the GWAS array data and I is the identity matrix . The simulated traits have heritability h2 = 0 . 5 under this model . We then estimated heritability using different kinship matrices derived from sequencing data within WES target regions or across both target and off-target regions using either SEEKIN or PC-Relate . For the off-target regions , we experimented with both the original data ( ~0 . 75X ) and the down sampled data ( ~0 . 15X ) . Heritability estimation was performed using the restricted maximum likelihood ( REML ) method in the GEMMA software [2] . We also compared heritability estimation for 10 metabolic traits using GWAS array data , WES target data , or WES target and off-target data . These traits include body-mass index ( BMI ) , waist-to-hip ratio ( WHR ) , systolic blood pressure ( SBP ) , diastolic blood pressure ( DBP ) , total cholesterol ( TC ) , low-density lipoprotein ( LDL ) , high-density lipoprotein ( HDL ) , triglycerides ( TG ) , fasting blood glucose ( FBG ) and hemoglobin A1C ( HbA1C ) . We log-transformed TG to reduce the skewness of its distribution . For each trait , we removed outliers that are more than 5 standard deviations from the mean . We used the REML method in GEMMA to estimate heritability for each trait , adjusting for age , age2 , sex , and the first two ancestry PCs . The ancestry PCs were derived from LASER using array genotypes and the SGVP reference panel [39] .
Three major ethnic groups , Chinese , Malay and Indian , contribute to ~97% of the population in Singapore . Using genotypes across 435 , 314 SNPs , we compared the ancestry backgrounds of 2 , 452 individuals in the Singapore Living Biobank with 268 individuals previously reported by the Singapore Genome Variation Project ( SGVP ) [54] . The SGVP samples were selected on the basis that all four grandparents belong to the same ethnic group and thus were less likely to be admixed [54] . Based on the first two PCs derived from the LASER analysis ( Fig 1A and 1B ) , self-reported Chinese from the Living Biobank Project tightly cluster with each other and with the SGVP Chinese , expect for a few outliers . In contrast , self-reported Malays appear to be more heterogeneous , with many individuals spreading between different ethnicity groups in the SGVP , indicating a high level of admixture among self-reported Malays from the Living Biobank Project . Such observations were confirmed by the ADMIXTURE analysis [23] . Self-reported Malays had ~25% Chinese ancestry component and ~13% Indian ancestry component , and the variation of admixture proportions is large across individuals ( Fig 1C ) . Compared to Malays , self-reported Chinese are more homogeneous with ~3% Indian component and ~19% Malay component . The moderate level of shared ancestry component between most Chinese and Malays may reflect recent split between these two populations in addition to potential admixture events . Given the presence of population structure and admixture , we used PC-Relate [21] to infer relatedness between the Living Biobank samples ( Fig 2 ) . Results derived from REAP [20] and RelateAdmix [22] are similar . We classified close relatedness into monozygotic twins ( MZ ) , parent-offspring ( PO ) , full siblings ( FS ) , 2nd degree and 3rd degree based on the estimated kinship coefficient ϕ and the probability of zero-IBD-sharing π0 with thresholds given in [18] . After excluding two pairs with ambiguous relationship ( i . e . , ϕ falls in the range of PO/FS relatedness but π0 falls in the range of 2nd degree relatedness ) , we found two MZ , 53 PO , 96 FS , 38 2nd degree and 24 3rd degree pairs of Chinese , and two MZ , 99 PO , 187 FS , 107 2nd degree and 120 3rd degree pairs of Malays . Interestingly , we also identified eight closely related pairs of one Chinese and one Malay , including two PO , and two 2nd degree and four 3rd degree pairs . We further checked the admixture proportion of these eight Chinese-Malay related pairs and found that all of the eight self-reported Chinese have >35% Malay component , much higher than the average level of ~19% in Chinese . These results provide clear genetic evidence of recent admixture between Chinese and Malay populations . In total , 263 Chinese and 499 Malays ( ~31% of the total sample ) were identified to have close relatives in the sample . We used these individuals to form test datasets to evaluate the performance of different kinship estimators in a homogeneous sample that includes only Chinese ( N = 254 after excluding nine Chinese with >35% Malay admixture component ) and a heterogeneous sample of pooled Chinese and Malays ( N = 762 ) . To evaluate performance of kinship estimators based on off-target sequencing data in typical target sequencing experiments , we down sampled from the original WES data to generate a low-coverage sequencing dataset of ~0 . 15X depth ( Materials and Methods ) . Our evaluation of homogeneous estimators was based on 254 related Chinese individuals . We compared our SEEKIN-hom estimator ( Eq 7 ) with existing estimators for homogeneous samples , including lcMLkin [40] , GCTA [5] , and KING ( specifically the homogeneous estimator , KING-hom ) [18] . First , we used bcftools to call genotypes for these 254 individuals without using LD information [48] . Even though 1 , 541 , 541 SNPs with MAF≥0 . 05 were identified , the number of overlapping SNPs between any pair of individuals was only ~46 , 379 due to large amounts of missing data . Both GCTA and KING performed poorly with strong downward bias in comparison to the gold standard based on array genotyping data ( Fig 3A; Table 1 ) . Due to high computational demands of lcMLkin , we had to trim the full dataset to one SNP in every 20kb genomic region , resulting in 106 , 247 independent SNPs for the lcMLkin analysis . By modeling genotype uncertainty , lcMLkin performed better than GCTA and KING , but still systematically underestimated kinship for PO/FS pairs by ~0 . 026 and overestimated kinship for unrelated pairs by ~0 . 035 . Next , we used BEAGLE without external reference data to call genotypes [42] . This approach uses shared LD information among the individuals to both improve genotype accuracy and impute missing data . After excluding SNPs with MAF<0 . 05 or r2<0 . 5 , the remaining set includes 68 , 785 SNPs with no missing genotypes . The lcMLkin method cannot be applied to this call set because lcMLkin requires genotype likelihoods , which are not available in the LD-based call set generated by BEAGLE . GCTA and KING had improved performance using this call set but still systematically underestimated kinship coefficients ( Fig 3B; Table 1 ) . In comparison , our SEEKIN estimator largely reduced the bias by accounting for genotype uncertainty intrinsic to low-coverage sequencing data . For example , the mean downward bias of the estimated kinship coefficients for PO/FS pairs is 0 . 023 for SEEKIN , much lower than 0 . 093 for GCTA and 0 . 099 for KING . Similar observations hold for other types of relatedness that SEEKIN has the lowest bias and RMSE , except for the unrelated pairs in which GCTA is slightly better than SEEKIN ( Table 1 ) . For self-kinship coefficients , estimates derived from SEEKIN have little bias as we expect , but the RMSE is higher for SEEKIN ( 0 . 043 ) than for GCTA ( 0 . 014 ) . KING does not estimate self-kinship coefficients . It seems counterintuitive that GCTA substantially underestimated kinship coefficients for MZ pairs but performed well in estimating self-kinship coefficients , given that the underlying genotypes are identical for MZ pairs . Our explanation is that at low-coverage setting , the most-likely genotypes in each individual tend to follow a prior assumption of HWE . This is equivalent to assuming a self-kinship of 0 . 5 , close to the truth in human populations with little inbreeding . For SEEKIN , self-kinship estimates have much larger variation than pairwise kinship estimates , which might be due to different amounts of data used in the estimation; self-kinship coefficients were estimated based on data from a single sample , while pairwise kinship coefficients were derived using data from two samples . By incorporating external haplotypes as the reference panel in BEAGLE , we can substantially improve the genotype calling quality for low-coverage sequencing data [41] . In our call set with the 1KG3 reference panel [28] , we retained 4 , 517 , 106 SNPs with MAF≥0 . 05 and r2≥0 . 5 , ~66 times more SNPs than the BEAGLE call set without reference . Furthermore , the genotype concordance rate for SNPs overlapping with the array data increased from 0 . 85 to 0 . 90 . The improved genotype quality led to better performance for all methods ( Fig 3C; Table 1 ) . Nevertheless , GCTA and KING still consistently underestimated kinship coefficients for closely related pairs , while SEEKIN had the smallest empirical bias ( almost 0 ) and RMSE values ( ~3–4 times smaller than GCTA and KING ) . All three methods performed similarly for unrelated pairs . The SEEKIN estimation of self-kinship coefficients remained inaccurate ( RMSE = 0 . 032 ) . We further evaluated accuracy of relationship classification based on the pairwise kinship estimates . Manichaikul et al . [18] proposed a set of classification criteria , in which the ranges of kinship coefficients for PO/FS , 2nd degree , and 3rd degree related pairs are ( 2−5/2 , 2−3/2 ) , ( 2−7/2 , 2−5/2 ) , and ( 2−9/2 , 2−7/2 ) , respectively . We applied the same set of criteria on our kinship estimates to classify relationship . We used the relationship types inferred from array-based kinship estimates as the gold standard ( Fig 2 ) , and calculated the sensitivity and precision in classifying each relationship type using the sequence-based kinship estimates . Due to more accurate kinship estimates , relationship classification based on SEEKIN outperformed other methods ( S1 Table ) . For example , using the BEAGLE+1KG3 call set , SEEKIN achieved perfect sensitivity and precision in classifying PO/FS , 2nd , and 3rd degree relationship with only ~0 . 15X sequencing data , while both GCTA and KING had <96% , <92% , and <63% sensitivity to identify PO/FS , 2nd , and 3rd degree relationship , respectively . We also repeated the evaluation for both kinship estimation and relationship classification using all the off-target sequencing data at ~0 . 75X without down sampling . While all methods had improved performance compared to using ~0 . 15X data , kinship estimation using GCTA and KING remained downward biased in all three call sets ( S2 Fig; S2 Table ) . The sensitivity and precision of relationship classification were highest for the SEEKIN method ( S3 Table ) . For the BEAGLE call set , GCTA and KING misclassified >40% of the 2nd degree relatedness as the 3rd degree relatedness due to underestimation of kinship coefficients , while SEEKIN only misclassified ~2 . 8% of the 2nd degree relatedness . When applied to the 1KG3-guided BEAGLE call set , our SEEKIN method produced kinship estimates almost identical to the gold standard based on array genotyping data ( RMSE≤0 . 007 for all relatedness types ) . Kinship estimation and relationship classification were also much improved for KING and GCTA . It is worth noting that in this setting , the variation of SEEKIN estimates of self-kinship coefficients was much reduced ( RMSE = 0 . 018 , similar to RMSE = 0 . 015 for GCTA ) . To evaluate kinship estimators for heterogeneous samples , we pooled all 762 related individuals from the Singapore Living Biobank Project to form test datasets that include Chinese , Malays and admixed individuals . We evaluated our SEEKIN-het estimator ( Eq 11 ) and existing estimators PC-Relate [21] , REAP [20] , and RelateAdmix [22] at sequencing depth of 0 . 15X and 0 . 75X . We used the SGVP dataset [54] as the reference panel in LASER [39] and ADMIXTURE [23] analyses to derive individual ancestry and thereby individual-specific allele frequencies for SEEKIN , REAP and RelateAdmix . Therefore , our analyses were restricted to SNPs overlapping with the SGVP dataset , including PC-Relate which does not require an external ancestry reference panel . We did not compare with homogeneous estimators because they have been shown by previous studies to perform poorly on admixed samples [20–22] . Before proceeding to kinship estimation , we evaluated if we could accurately estimate individual-specific allele frequencies for sparsely sequenced samples . First , we confirmed that LASER can produce accurate estimation of top PCs using sparse sequencing data . For 762 Chinese and Malays , the top two PCs in the SGVP ancestry space estimated from 0 . 15X sequencing data are almost identical to those derived from GWAS array data ( Procrustes similarity t0 = 0 . 9976 , Fig 4A and 4B ) [56] . Next , we compared individual-specific allele frequencies predicted by top two LASER PCs from either array data or 0 . 15X sequencing data with those from ADMIXTURE analysis of array data . Here , we used the individual-specific allele frequencies derived from ADMXITURE as the gold standard , because ADMIXTURE is a rigorous model-based approach with superior performance demonstrated by previous studies [20 , 22 , 23] . We showed that using array data , the PC-based individual-specific allele frequencies are highly consistent with those derived from ADMIXTURE ( Pearson correlation r = 0 . 9980 , Fig 4C and 4D ) . The correlation dropped slightly to 0 . 9976 when the PCs were derived from 0 . 15X sequencing data instead of array data . These results suggests that our approach based on LASER can accurately estimate individual-specific allele frequencies even when the sequencing depth is extremely low . For kinship estimation in heterogeneous samples , we only considered the BEAGLE and BEAGLE+1KG3 call sets , because we have shown that LD-based call sets performed much better than the bcftools call set at low-coverage setting ( Figs 3 and S2 ) . Without modeling the genotype uncertainty , PC-Relate , REAP , and RelateAdmix underestimated kinship coefficients for related pairs at both 0 . 15X and 0 . 75X sequencing depth ( Figs 5 and S3; Tables 2 and S4 ) . In contrast , SEEKIN reduced the RMSE by >50% and the empirical bias by >65% for kinship estimates between close relatives . In particular , based on the BEAGLE+1KG3 call set at 0 . 75X , SEEKIN’s estimates were almost identical to the gold standard based on array data ( RMSE≤0 . 007 ) . SEEKIN performed similarly to existing methods for unrelated pairs . For self-kinship coefficients , SEEKIN estimates had large RMSE , especially at 0 . 15X , even though the empirical bias was small . The estimates of self-kinship coefficients became more accurate on the BEAGLE+1KG3 call set at 0 . 75X , where all three methods had similar RMSE ( 0 . 018 for SEEKIN and REAP , and 0 . 017 for PC-Relate ) , but SEEKIN has the smallest empirical bias ( 0 . 002 for SEEKIN , -0 . 014 for PC-Relate , and -0 . 017 for REAP ) . For relationship classification , SEEKIN remained the best among all methods in terms of both sensitivity and precision , regardless of sequencing depth and relationship types ( S5 Table; S6 Table ) . Remarkably , SEEKIN achieved >92% precision and >86% sensitivity in classifying 3rd and 2nd degree relatedness based on the BEAGLE call set at 0 . 15X , while PC-Relate , REAP , and RelateAdmix , had <40% precision and sensitivity . For the BEAGLE+1KG3 call set at 0 . 15X , SEEKIN had >95% precision and sensitivity in classifying 3rd and 2nd degree relatedness , while the same metrics for the other methods were <90% . Overall , the performance of the SEEKIN-het estimator on heterogeneous samples is similar to that of SEEKIN-hom on homogeneous samples , suggesting that SEEKIN-het effectively accounts for the diverse ancestry background in samples with population structure and admixture . In this section , we evaluated how SEEKIN can improve kinship estimation in WES studies by incorporating off-target sequencing data , in comparison to the conventional approach that discards off-target data . We analyzed the original WES data of 762 Chinese and Malays , jointly called using BEAGLE with the 1KG3 reference panel across both target and off-target regions . To illustrate the benefits in downstream analyses , we compared heritability estimation based on different estimated kinship matrices for both simulated polygenic traits and 10 metabolic traits . When we focused on target regions , genotypes across 40 , 824 SNPs overlapping with the SGVP dataset were included in the analyses . As expected , the performances of SEEKIN and PC-Relate were highly similar , because genotypes are accurate at SNPs within deeply sequenced target regions ( Fig 6A and 6B; Table 3 ) . For simulated polygenic traits of h2 = 0 . 5 heritability , the targeted SNPs were able to capture ~86% of heritability using the kinship matrix from either SEEKIN or PC-Relate ( estimated h2 = 0 . 43 after averaging across 1000 replicates , Fig 7 ) . When we expanded our analyses to 1 , 054 , 229 SNPs across both target and off-target regions , the RMSE for SEEKIN estimates was reduced by ~50% across different relatedness types and the empirical bias remained close to 0 ( Fig 6C ) . Using the improved kinship estimates , the estimated heritability was increased to 0 . 49 , capturing ~98% of total heritability . In contrast , PC-Relate underestimated kinship coefficients by ~7% for closely related pairs after including off-target data ( Fig 6D ) , leading to ~4% overestimation of the heritability . If we down sampled the off-target data to 0 . 15X , it became more evident that the heritability was overestimated by ~18% because PC-Relate underestimated kinship coefficients when analyzing inaccurate off-target genotypes ( Fig 7 ) . In comparison , the estimated heritability based on the kinship matrix from SEEKIN dropped from 0 . 49 to 0 . 46 ( ~8% underestimation ) because less information was captured by 0 . 15X off-target data . We also tested if our noisy estimation of self-kinship coefficients affects heritability analysis . By replacing the diagonal elements in the estimated kinship matrices with ones or the values estimated from array genotyping data , our heritability estimates remained almost the same , suggesting the noises in our estimated self-kinship coefficients do not introduce bias in heritability analysis . Finally , we estimated heritability for 10 metabolic traits available in the Singapore Living Biobank dataset , adjusting for covariates of age , age2 , sex , and two ancestry PCs ( Materials and Methods ) . When we used the kinship matrix derived from array genotyping data , our heritability estimates were higher than the previously reported values based on unrelated samples but smaller than the values reported by twin studies ( Table 4 ) [57–59] . Although heritability estimates are not directly comparable across studies due to differences in the pedigree structure and population background , the relative values for different traits in the same study are comparable . For example , we found cholesterol levels ( HDL and LDL ) to be more heritable than blood pressure measurements ( DBP and SBP ) , which is consistent with previous studies [57–59] . For WES data , we used the kinship matrices derived from SEEKIN . As shown in Table 4 , heritability estimates based on SNPs within target regions were consistently smaller than the values based on genome-wide array genotyping data by a minimum of 4% ( for HbA1C ) to a maximum of 29% ( for DBP ) . After including off-target SNPs , WES-based estimates of heritability became much closer to the array-based estimates ( from ≤1% difference for HbA1C , DBP , and TC to a maximum of 6% difference for FBG ) . These results , together with the simulations , suggest that our SEEKIN method is useful for WES studies to improve kinship estimation and downstream analyses such as estimation of trait heritability , by properly incorporating sparse data from off-target regions . The whole SEEKIN analysis pipeline involved several steps starting from BAM files , including ( 1 ) genotype calling using BEAGLE , ( 2 ) ancestry estimation using LASER , ( 3 ) individual-specific allele frequency estimation using SEEKIN , and ( 4 ) kinship estimation using SEEKIN . For homogeneous samples , steps ( 2 ) and ( 3 ) can be skipped . As an example , we recorded the computational time of each step in the analysis of the BEAGLE+1KG3 call set for 762 individuals at ~0 . 15X . The BEAGLE step cost ~680 CPU days and ~1 . 7 wall-clock days when we split each chromosome into small chunks and ran the analysis in massive parallelization with 400 CPUs . We note that although the BEAGLE step is computationally intensive , especially with a large reference panel , it is a necessary step for all methods in analyzing shallow sequencing data . The LASER step cost ~34 CPU hours to place 762 individuals onto the ancestry map generated by the SGVP panel . The LASER step is scalable to large datasets because the computational time of LASER scales linearly to the study sample size and the analysis can be easily parallelized [38 , 39] . The last two steps using SEEKIN were fast; estimation of individual-specific allele frequencies across 1 , 285 , 277 SGVP SNPs cost only ~18 CPU minutes , and estimation of kinship coefficients based on the SEEKIN-het estimator cost ~116 CPU minutes . In application to high-quality genotyping data , we do not need to process raw sequencing data so that the computationally intensive BEAGLE step can be skipped and the LASER step can run with a much faster algorithm for genotyping data [39] . To test the applicability of SEEKIN in large genotyping datasets , we further benchmarked the performance of kinship estimation using SEEKIN and existing methods based on two synthetic datasets of N = 10 , 000 individuals , generated by sampling with replacement from the Singapore Living Biobank sample . One dataset consists of M = 100 , 000 SNPs ( 100K dataset ) and the other consists of M = 1 , 000 , 000 SNPs ( 1M dataset ) . For all evaluations , we set the number of CPUs to 10 if the software program supports multi-threading . As shown in Table 5 , SEEKIN is both fast and memory efficient . The computational time of SEEKIN scales linearly to the number of SNPs and the memory usage remains constant ( 2 . 8 GB for SEEKIN-hom and 3 . 8 GB for SEEKIN-het ) . The higher memory cost for SEEKIN-het is due to the storage of individual-specific allele frequencies . The likelihood method , RelateAdmix , is computationally intensive and could not finish within 100 hours even for the smaller 100K dataset . In contrast , the moment methods are fast . SEEKIN-hom used 13 minutes to analyze the 100K dataset , while GCTA and KING only spent ~3 minutes . In the heterogeneous setting , SEEKIN-het spent 55 minutes , about 20 times faster than REAP and 45 times faster than PC-Relate . For the 1M dataset , only KING , SEEKIN-hom and SEEKIN-het managed to complete within 100 hours given 50 GB memory . Therefore , in addition to its unique capability for analyzing sparse sequencing data , SEEKIN is also useful for analyzing high-quality genotype data due to its computational efficiency and scalability to large datasets .
In this study , we have developed moment estimators to infer kinship coefficients using sparse sequencing data for both homogeneous samples and heterogeneous samples with population structure and admixture . We have implemented our method into a computationally efficient and scalable software program named SEEKIN . Under certain model assumptions , our SEEKIN estimators share the same expectations as existing consistent estimators developed for high-quality genotyping data ( GCTA [5] and PC-Relate [21] ) . Based on extensive evaluation on empirical datasets , we have demonstrated that SEEKIN can accurately estimate kinship coefficients using sparse sequencing data at ~0 . 15X , which corresponds to the typical off-target depth in target sequencing experiments . Existing methods , without accounting for the genotype uncertainty , substantially underestimate kinship coefficients when applied to sparse sequencing data . Such patterns persist even when the sequencing depth increases to ~0 . 75X . For WES studies , SEEKIN can improve kinship estimation by properly incorporating off-target sequencing data , as compared to the conventional analysis solely based on genotypes from deeply sequenced exonic regions . Off-target reads , as byproducts of target sequencing experiments , are sparsely distributed genome-wide . The total amount of off-target reads , however , is of the same magnitude as the number of reads aligned to the target regions . Rather than discarding the vast amount of off-target data , we previously proposed to use off-target data to infer individual ancestry and control for population structure using our LASER method [38 , 39] . Now with the SEEKIN method , we can also control for family relatedness in target sequencing studies without additional genotyping data . Such an advancement is important because population structure and family relatedness are major confounders in genetic association studies and unexpected cryptic relatedness is prevalent in many datasets [60] . Because the kinship matrix is often used to model phenotype correlation in mixed models , our method also enables a variety of downstream analyses for target sequencing studies , including estimation of trait heritability and imputation of missing phenotypes [7 , 8] . In addition to target sequencing experiments , sparse human sequencing data can be extracted from metagenomic sequencing data across different human body sites [61] . We envision that both SEEKIN and LASER can be potentially used to infer the genetic background of human hosts , which might help explain patterns in microbiome composition across different individuals [61] . Our method leverages the LD information shared among study individuals and an external reference panel , such as the 1KG3 dataset , to analyze low-coverage sequencing data . Similar ideas of using LD between neighboring genetic markers have recently been proposed for matching forensic samples , which is a special case of identifying monozygotic twins in the inference of genetic relatedness , using either low-coverage sequencing data [29] or disjoint marker sets [62] . When an external reference panel is not available , LD information can be learnt from study individuals alone , especially when the sample size is large . Such LD-based imputation approaches not only increase the number of SNPs shared by any pair of individuals but also improve the overall genotyping accuracy [26 , 41] . We have shown that SEEKIN performs much better on the BEAGLE+1KG3 call sets than the BEAGLE call sets without a reference panel . As more human genomes are sequenced , we expect to achieve better performance in analyzing sparse sequencing data by utilizing larger and more relevant reference panels . Such improvement has been demonstrated for genotype imputation , where imputation accuracy increases as the size of the reference panel increases [63] . Large reference panels , however , are often not available for studies of non-human species , including many molecular ecology studies of wild animals based on non-invasive DNA samples , where inference of kinship from shallow sequencing data is of interests [30] . For these studies , the strategy of phasing without reference will be useful , and the performance of SEEKIN is expected to improve as the study sample size and sequencing depth increase . We account for the genotype uncertainty using the statistical model proposed by Hu et al . [46] . The model ( Eq 1 ) expresses the expectation of imputed dosage as a weighted sum of the true genotype and the mean genotype of the reference panel , with the weight given by the estimated dosage r2 . For Eq ( 1 ) to hold , we need well calibrated genotype probabilities so that the imputed dosage and the estimated r2 reflect the genuine genotype uncertainty [46] . We examined the genotype probabilities output by BEAGLE in our examples by comparing to the array data ( S4 Fig ) . We found that at ~0 . 75X depth , the genotype probabilities were well calibrated for both phasing with and without a reference panel . As the sequencing depth dropped to ~0 . 15X , the calibration remains good when phasing with the 1KG3 reference panel , but becomes inaccurate when phasing without reference panel . These results might explain why SEEKIN slightly underestimates kinship coefficients for the BEAGLE call sets at 0 . 15X ( Figs 3D and 5A ) . Even though we have modeled genotype uncertainty using dosage r2 in our estimators , we excluded SNPs with low quality ( r2<0 . 5 ) for two reasons . First , Hu et al . [46] have shown that Eq ( 1 ) might not hold when r2 is close to 0 . Second , low-quality SNPs contain less information and more noise , and thus might reduce the estimation accuracy when the quality fall below a certain threshold . We tested a lower threshold by including SNPs with r2>0 . 3 , and found that SEEKIN produced similar results in comparison to using SNPs with r2>0 . 5 , while the downward bias observed in the other methods became more evident ( S5 Fig and S6 Fig ) . Another assumption we made in the derivation of SEEKIN estimators is that residuals of Eq ( 1 ) are independent for different individuals ( S1 Text ) . This is a reasonable assumption for sparse sequencing data because the variation in the residuals of imputed dosage is dominated by the randomness in the genomic distribution of sequence reads , which are independent for different sequenced samples . Nevertheless , this assumption does not strictly hold because we expect correlated residuals for related individuals due to their correlated genotypes . We cannot make this assumption for imputed array genotyping data because the input genotypes are highly correlated for closely related individuals . In an extreme example of monozygotic twins , the input array genotypes are identical and thus the imputed dosages are also identical , even though imputation might be inaccurate . For this reason , when applied to the imputed GWAS data , the underestimation for existing methods is largely reduced in comparison to the low-coverage sequencing setting , while SEEKIN overestimates kinship coefficients . Overall , SEEKIN performs well in the low-coverage sequencing datasets we have tested , suggesting that SEEKIN is robust to moderate violation of the assumptions , including independent residuals in the Eq ( 1 ) and accurate calibration of genotype probabilities . Finally , our model implicitly assumes that the level of genotype uncertainty is similar among study individuals , which is reflected by the estimated dosage r2 for each SNP . This assumption posts a potential limitation on SEEKIN that it is not suitable to estimate kinship coefficients between two batches of samples with dramatic quality differences . For example , we cannot apply SEEKIN to identify cryptic relatedness between individuals from a WES dataset with ~1X off-target reads and individuals from a target sequencing dataset with ~0 . 2X off-target reads . For future work , we can generalize our kinship estimators to such scenarios by allowing for two r2 values , one for each dataset , to model different levels of genotype uncertainty in the datasets . A more general approach is to directly use genotype probabilities from each individual , instead of relying on a single estimated r2 statistic , to model genotype uncertainty . With these extensions , we can also identify potential relatedness between sequenced samples and array genotyped samples by treating the array genotyping data as accurate ( i . e . , r2 = 1 or genotype probability equal to 1 ) . The ability to infer relatedness across different studies will be useful to help select samples to include in joint association analyses or in further biological experiments . | Inference of genetic relatedness from molecular markers has broad applications in many areas , including quantitative genetics , forensics , evolution and ecology . Classic estimators , however , are not suitable for low-coverage sequencing data , which have high levels of genotype uncertainty and missing data . We evaluate existing methods and describe a new method for kinship estimation using sparse sequencing data . Our method leverages correlations between neighboring markers and models genotype uncertainty in kinship estimators for both homogeneous populations and admixed populations . We show that our method can accurately estimate kinship coefficient even when the sequencing depth is as low as ~0 . 15X , while existing methods have strong downward bias . Our method can be applied to estimate kinship using sparse off-target data and thus enables control of family structure and estimation of heritability in target sequencing studies , in which the deeply sequenced target regions are often too small to infer genetic relatedness . Even for whole exome sequencing , we show that our method can improve kinship and heritability estimation by including off-target data , compared to conventional analyses solely based on the target regions . | [
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] | 2017 | Estimation of kinship coefficient in structured and admixed populations using sparse sequencing data |
Microbiome-based stratification of healthy individuals into compositional categories , referred to as “enterotypes” or “community types” , holds promise for drastically improving personalized medicine . Despite this potential , the existence of community types and the degree of their distinctness have been highly debated . Here we adopted a dynamic systems approach and found that heterogeneity in the interspecific interactions or the presence of strongly interacting species is sufficient to explain community types , independent of the topology of the underlying ecological network . By controlling the presence or absence of these strongly interacting species we can steer the microbial ecosystem to any desired community type . This open-loop control strategy still holds even when the community types are not distinct but appear as dense regions within a continuous gradient . This finding can be used to develop viable therapeutic strategies for shifting the microbial composition to a healthy configuration .
The human microbiome is a complex and dynamic ecosystem [26] . When modeling a dynamic system we should first decide how complex the model needs to be so as to capture the phenomenon of interest . A detailed model of the intestinal microbiome would include mechanistic interactions among cells , spatial structure of the human intestinal tract , as well as host-microbiome interactions [27–30] . That level of detail however is not necessary for this study , because we are primarily interested in exploring the impact that any given species has on the abundance of other species . To achieve that , a population dynamics model such as the canonical Generalized Lotka-Volterra ( GLV ) model is sufficient [15 , 31] . Indeed , GLV dynamics leveraging current metagenome data has already been used for predictive modeling of the intestinal microbiota [32–34] . Consider a collection of n species in a habitat with the population of species i at time t denoted as xi ( t ) . The GLV model assumes that the species populations follow a set of ordinary differential equations x ˙ i ( t ) = r i x i ( t ) + x i ( t ) ∑ j = 1 n a i j x j ( t ) , i = 1 , … , n ( 1 ) where ( ) · = d d t ( ) . Here ri is the growth rate of species i , aij ( when i ≠ j ) accounts for the impact that species j has on the population change of species i , and the terms a i i x i 2 are adopted from Verhulst’s logistic growth model [35] . By collecting the individual populations xi ( t ) into a state vector x ( t ) = [x1 ( t ) , ⋯ , xn ( t ) ]T , Eq ( 1 ) can be represented in the compact form x ˙ ( t ) = diag ( x ( t ) ) r + A x ( t ) , ( 2 ) where r = [r1 , ⋯ , rn]T is a column vector of the growth rates , A = ( aij ) is the interspecific interaction matrix , and diag generates a diagonal matrix from a vector . Hereafter we drop the explicit time dependence of x . Next we discuss the notion of fixed point , or equivalently steady state , in the GLV dynamics . This notion is important in the context of the human microbiome , as the measurements taken of the relative abundance of intestinal microbiota in the aforementioned studies typically represent steady behavior [4 , 6] . In other words , the intestinal microbiota is a relatively resilient ecosystem [36 , 37] , and until the next large perturbation ( e . g . antibiotic administration or dramatic change in diet ) is introduced , the system remains stable for months and possibly even years [38–40] . The fixed points of system Eq ( 2 ) are those solutions x that satisfy x ˙ = 0 . The solution x = 0 ( i . e . all species have zero abundance ) is a trivial steady state . The set of non-trivial steady states contains those solutions x* such that r + Ax* = 0 . When the matrix A is invertible , it follows that the non-trivial steady state x* = −A−1 r is unique [41] . Our study ultimately investigated the impact that different collections of microbial species have on their steady state abundances . In Fig 1 we presented a detailed analysis showing that if we introduce a new species into the ecosystem in Eq ( 2 ) , the shift of the steady state is proportional to the interaction strengths between the newly introduced species and the previously existing ones . Similarly , if two communities with the same dynamics differ by only one species , then it is the interaction strength of that species with regard to the rest of the community that dictates how far apart the steady states of the two communities will be . This analytical result indicates that heterogeneity of interspecific interactions could lead to the clustering of steady states , and hence the emergence of community types . To systematically investigate how changes in species collection affect the steady state shift in the GLV dynamics , we assumed that two microbial species will interact in the same fashion regardless of the host . Otherwise , if the interactions are host specific and the dynamics are classifiable , we can show that distinct community types will emerge almost trivially ( S1 Text Sec . 6 . 2 and 7 . 1 ) . Consider a universal species pool , also referred to as a metacommunity [42] , indexed by a set of integers S = {1 , … , n} , an n × n matrix A representing all possible pairwise interactions between species , and a vector r of size n containing the growth rates for all the n species . The global parameters for the metacommunity are completely defined by the triple ( S , A , r ) . We consider q Local Communities ( LCs ) , defined by sets S[ν] that are subsets of S , denoting the species present in LCν with ν = 1 , … , q . This modeling procedure is inspired by the fact that alternative community assembly scenarios could give rise to the compositional variations observed in the human microbiome [42] . These LCs represent microbial communities in the same body site across different subjects . For simplicity , we assume that each LC contains only p species ( p ≤ n ) , randomly selected from the metacommunity . The GLV dynamics for each LC is given by LC ν : x ˙ [ ν ] ( t ) = diag x [ ν ] ( t ) r [ ν ] + A [ ν ] x [ ν ] ( t ) , ( 3 ) where the LC specific interaction matrix and growth vector are defined as A [ ν ] = A S [ ν ] , S [ ν ] and r [ ν ] = r S [ ν ] , respectively . That is , A[ν] is obtained from A by only taking the rows and columns of A that are contained in the set S[ν] . A similar procedure is performed in order to obtain r[ν] . Finally for each x[ν] there is a corresponding x [ ν ] ∈ R n that has the abundances for species S[ν] of LCν in the context of the metacommunity species pool S . To reveal the origins of community types in the human microbiome , we decomposed the universal interaction matrix as A = N H ◦ G s , ( 4 ) which contains four components . ( i ) N ∈ R n × n is the nominal interspecific interaction matrix where each element is sampled from a normal distribution with mean 0 and variance σ2 , i . e . [ N ] i j ∼ N ( 0 , σ 2 ) . ( ii ) H ∈ R n × n is a diagonal matrix that captures the overall interaction strength heterogeneity of different species . When studying the impact of interaction strength heterogeneity the diagonal elements of H will be drawn from a power-law distribution with exponent −α , i . e . [ H ] i i ∼ P ( α ) , which are subsequently normalized so that the mean of the diagonal elements is equal to 1 . This is to ensure that the average interaction strength is bounded . For studies that do not involve interaction strength heterogeneity H is simply the identity matrix . ( iii ) G ∈ R n × n is the adjacency matrix of the underlying ecological network: [G]ij = 1 if species i is affected by the presence of species j and 0 otherwise . For details on the construction of G for different network topologies see S1 Text Sec . 3 . 2 . 2 . Note that the Hadamard product ( ◦ ) between H and G represents element-wise matrix multiplication . ( iv ) The last component s is simply a scaling factor between 0 and 1 . Finally , we set [A]ii = −1 . The presence of the scaling factor s and setting the diagonal elements of A to −1 are to ensure an asymptotic stability condition for the GLV dynamics ( S1 Text Sec . 4 . 2 , 4 . 3 . 3 , and 4 . 5 ) . The elements in the global growth rate vector r are taken from the uniform distribution , [ r ] i ∼ U ( 0 , 1 ) . Details concerning the distribution N , P and U can be found in S1 Text Sec . 3 . 1 . 1 . We first studied the role of interspecific interaction strength heterogeneity on the emergence of community types . In order to achieve this , we chose the complete graph topology , i . e . each species interacts with all other species . This eliminates any structural heterogeneity . The nominal interaction strengths were taken from a normal distribution N ( 0 , 1 ) , the scaling component was set to s = 0 . 7 , and the interaction strength heterogeneity was varied from low heterogeneity ( α = 7 ) to a high level of heterogeneity ( α = 1 . 01 ) . Fig 2 displays the distributions of the diagonal elements of the interaction heterogeneity matrix H at various heterogeneity levels . For each level of heterogeneity we constructed 500 LCs , each with 80 species randomly drawn from a metacommunity of 100 species . Fig 2b illustrates the global interaction matrix A as a weighted network . With low heterogeneity all the link weights are of the same order of magnitude . As the heterogeneity increases fewer nodes contain highly weighted links , until there is only one node with highly weighted links when α = 1 . 01 . These nodes with highly weighted links correspond to SISs . Fig 2c presents the results of Principle Coordinates Analysis ( PCoA ) of the steady states associated with the 500 different LCs as a function of α . For low interaction heterogeneity ( α = 7 ) the classical clustering measure , Silhouette Index , is less than 0 . 1 , suggesting a lack of clustering in the data . As the heterogeneity increases the steady states can be seen to separate in the first two principle coordinate axes . At one point ( α = 2 . 0 ) three clusters is the optimal number of clusters . Then as α continues to decrease the optimal number of clusters becomes two . The fact that there are three clusters when α = 2 . 0 is not special , as a different number of optimal clusters can be observed with different model parameters or different clustering measures ( see S1 Text Sec . 7 . 2 ) [7] . While the precise number of clusters is not important here , what is important is the fact that the degree of interaction strength heterogeneity controls the degree to which the clusters appear to be distinct . For low levels of interaction strength heterogeneity the clusters appear to be more like dense regions within a continuous gradient . As the heterogeneity increases , the clusters become more distinct . Indeed , having two clusters for α = 1 . 01 is to be expected , because one of the clusters is associated with all the LCs that contain the single SIS , and the other LCs that do not contain the single SIS constitute the other cluster . The overall trend observed in Fig 2c is unaffected if the complete graph is replaced by an Erdős-Rényi ( ER ) random graph , or if the total number of LCs is increased ( S1 and S2 Figs ) . The result is also generally unaffected by the specifics of the nominal distribution ( S1 Text Sec . 7 . 2 . 1 ) , the mean degree of the ER graph ( S1 Text Sec . 7 . 2 . 2 ) , or the number of species in the LCs ( S1 Text Sec . 7 . 2 . 3 ) . Of course , each LC can be invaded by other species that are currently absent . If this migration occurs relatively fast , then all LCs will converge to roughly the same species collection and the clustering will disappear . Hence in our modeling approach we have to assume that the migration occurs at a relatively slow time scale , and the time interval between species invasions is too long to disrupt the clustering . We also note that if heterogeneous interactions are placed at random in the network the clustering of steady states does not arise ( S3 Fig ) . Our results are also robust ( in the control theoretical sense ) to stochasticity and the migration of existing species [43] . Robustness to migration is illustrated in S4 and S5 Figs , and robustness to stochastic disturbances is illustrated in S6–S8 Figs ( see S1 Text Sec . 4 . 4 for analytical robustness results ) . We can explain the above results as follows: for low interaction strength heterogeneity all of the matrices A[ν] are very similar . In other words , despite containing different sets of species , all the LCs have very similar dynamics . Thus , clustering of steady states is not to be expected . As the heterogeneity of interaction strength increases , however , some of the LCs will have species that are associated with the highly weighted columns in A , i . e . the SISs . Fig 3 presents a detailed analysis of the most abundant ( dominating ) species in each of the three clusters ( community types ) in Fig 2c for α = 2 and α = 1 . 6 , along with the abundances of the SISs within each cluster . It is clear that for different clusters their dominating species are different , consistent with the empirical finding that each enterotype is dominated by a different genus [6] . The SISs that are present in each cluster also vary . For instance with α = 1 . 6 all LCs in the blue cluster contain SISs number 23 and 81 , and none have species 60 or 51 . For the orange cluster it is the opposite scenario . All of the LCs in the orange cluster contain SISs 60 and 51 , and do not contain species 23 or 81 . Most of the LCs in the yellow cluster contain SISs 23 and 51 . Hence , each community type is well characterized by a unique combination of SISs . Note that none of the SISs are dominating species . These findings , along with the analysis in Fig 1 , suggest that heterogeneity in interaction strengths or the presence of SISs leads to the clustering of steady states , i . e . the emergence of community types . We then studied the impact of structural heterogeneity on community types . Four different scenarios are illustrated in Fig 4: ( a ) a complete graph topology as in Fig 2; ( b ) an ER random graph as in S1 Fig; ( c ) a power-law out-degree network; ( d ) a power-law out-degree network with no interaction strength heterogeneity . Fig 4a , 4b and 4c support the main result shown in Fig 2 , i . e . increasing interaction strength heterogeneity leads to the emergence of distinct community types . Fig 4d displays rather unexpected results as it suggests that structural heterogeneity alone does not lead to distinct community types . It is only with the inclusion of interaction strength heterogeneity that structurally heterogeneous microbial ecosystems can display strong clustering in their steady states as shown in Fig 4c . This result is rather surprising , because structural heterogeneity is observed in many real-world complex networks [44–46] and has been shown to affect many dynamical processes over complex networks [47–49] . Note that in the preparation of Fig 4 the steady state abundances were normalized to get relative abundances of the species and the Jensen-Shannon distance metric was used for clustering analysis [50] . The trends discussed above also hold when , instead of the Silhouette Index , the Variance Ratio Criterion is used as the clustering measure , or the Euclidean distance is used for clustering , or when absolute abundances are analyzed along with the Euclidean distance being used ( S9 , S10 and S11 Figs ) . S11 Fig correlates to the analytical results in Fig 1 , where absolute abundances and the Euclidean distance are implicitly used . With the knowledge that each community type can be associated with a specific collection of SISs , we tested the hypothesis that a local community could be steered to a desired community type by controlling the combination of SISs only . Our results for three different scenarios are shown in Fig 5a for α = 1 . 6 . The local community that was controlled in each scenario is shown in magenta and is denoted LC* , which initially belongs to the blue cluster . For Scenario 1 , LC* had the SISs 23 and 81 removed , with species 60 and 51 simultaneously introduced with random initial abundances drawn from U ( 0 , 1 ) . Recall that species 60 and 51 are the SISs present in the orange cluster . This swap of SISs shifts LC* to a slightly different state ( green dot ) within the blue cluster . The GLV dynamics were then simulated and the trajectory goes from the blue cluster to the orange cluster . This result was independent of the initial condition of species 60 and 51 ( Fig 5b ) . This open-loop control of the community type by manipulating a set of SISs also works at lower levels of heterogeneity ( Fig 5c and 5d ) . Here we use the term open-loop to contrast closed-loop control where inputs are designed with feedback so as to continuously correct the system of interest . These findings imply that the SISs , despite their low abundances , can be used to effectively control a microbial community to a desired community type . In Scenario 2 we tested if the same result could be obtained by removing the six most abundant species from LC* and introducing the six most abundant species from the orange cluster at exactly the same abundance level as an arbitrary local community in the orange cluster . The state after this dominating species swap ( red dot ) starts close to the orange cluster , because the six most abundant species from a local community in that cluster were copied . The trajectory does not ultimately converge near the orange cluster , but goes toward the blue cluster instead . The trajectory , however , does not ultimately converge in the blue cluster because it does not contain any of the most abundant species present in the blue cluster . In scenario 3 we explored how the open-loop control methodology just presented could also be used to conceptually justify the success of FMT in treating patients with rCDI [20–22] . This scenario begins by removing 20 species from LC* ( the top two SISs and 18 of the most abundant spaces ) so as to emulate the effect of broad-spectrum antibiotics , resulting in an altered community ( blue dot ) . Then the GLV dynamics were simulated and the local community converged to a new steady state ( black dot ) , representing the CDI state . To emulate an oral capsule FMT 1% of the species abundances from an arbitrary LC in the orange cluster , i . e . the donor , was added to the CDI state , resulting in a slightly altered community ( gray dot ) . The GLV dynamics were then simulated until the final steady state was reached ( white dot ) . As expected the post-FMT steady state is in the orange cluster , the same cluster that is associated with the donor’s LC . Note that if during the FMT the SISs in the donor’s LC were not transplanted then the patient’s post-FMT steady state does not converge in the orange cluster ( S12 Fig ) . The above results indicate that the presence of SISs simplifies the open-loop control design . However , the existence of community types is not a prerequisite for deploying this control methodology . The possibility for open-loop control of the human microbiome will likely be body site specific . Our work focused on the gut specifically because of the fact that this microbial community is very likely dominated by microbe-microbe and/or host-microbe interactions , rather than external disturbances . It is yet to be determined what factors drive the dynamics in other body sites .
In this work we studied compositional shift as a function of species collection using a dynamic systems approach , aiming to offer a possible mechanism for the origins of community types . We found that the presence of interaction strength heterogeneity or SISs is sufficient to explain the emergence of community types in the human microbiome , independent of the topology of the underlying ecological network . The presence of heterogeneity in the interspecific interaction strengths in natural communities has been well studied in macroecology [23–25 , 51] . Extensive studies are still required to explore this interesting direction in the human microbiome . While preliminary analysis is promising , all existing temporal metagenomic datasets are simply not sufficiently rich to infer the interspecific interaction strengths among all of the microbes present in and on our bodies [15] even at the genus level , let alone the species level . Recent studies have tried to overcome this issue by only investigating the interactions between the most abundant species [34] . Our results , however , suggest that SISs need not be the most abundant ones and can still play an important role in shaping the steady states of microbial ecosystems . Ignoring the lack of sufficient richness , system identification analysis with regularization and cross-validation [32 , 52] of the largest temporal metagenomic dataset to date [39] does not disprove the existence of SISs . To the contrary , it supports this assertion ( see S13 Fig ) . Permutation of the time series however also results in the identification of interaction strength heterogeneity ( see S14 and S15 Figs ) . Hence , the presence of SISs needs to be systematically studied with novel system identification methods and perhaps further validated with co-culture experiments [15] . For example , we could first use metabolic network models to predict levels of competition and complementarity among species [53] , which could then be used as prior information to further improve system identification [54] . Note that our notion of SIS is fundamentally different from that of keystone species , which are typically understood as species that have a disproportionately deleterious effect ( relative to their abundance ) on the community upon their removal [55] . One can apply a brute-force leave-one-out strategy to evaluate the “degree of keystoneness” of any species in a given community [56] . Even without any interaction strength heterogeneity , a given community may still have a few keystone species . The SISs defined in this work are those species that have very strong impacts ( either positive or negative ) on the species that they directly interact with . The presence of SISs requires the presence of interaction strength heterogeneity . We emphasize that an SIS is not necessarily a keystone species . In fact , without any special structure embedded in the interaction matrix ( and hence the ecological network ) , there is no reason why the removal of any SIS would cause a mass extinction . It does have a profound impact on the steady-state shift , which is exactly what we expected from our analytical results presented in Fig 1 . Our findings also have important implications as we move forward with developing microbiome-based therapies , whether it be through drastic diet changes , FMT , drugs , or even engineered microbes [57–63] . Indeed , our results suggest that a few strongly interacting microbes can determine the steady state landscape of the whole microbial community . Therefore , it may be possible to control the microbiome efficiently by controlling the collection of SISs present in a patient’s gut . Finer control may be possible through the engineering of microbes . This will involve a detailed mechanistic understanding of the metabolic pathways associated with the microbes of interest . As discussed in Fig 1 , given a new steady state of interest , the parameters b , c , d , s could be chosen such that the new steady state is feasible and stable ( S1 Text Sec . 4 . 3 . 1 ) . Then , with the knowledge of the appropriate parameters b , c , d , s it would be possible to introduce a known microbe with those characteristics or engineer one to have the desired properties . We emphasize that the stability and control of the microbial ecosystem must be studied at the macroscopic scale using a systems and control theoretic approach . This is similar to what is carried out in aerospace applications . The design of wings and control surfaces for an aircraft incorporate sophisticated fluid dynamic models . The control algorithms for planes however are often derived from simple linearized reduced order dynamic models where linear control techniques can be easily deployed [64] . Taken together , our results indicate that the origins and control of community types in the human microbiome can be explored analytically if we combine the tools of dynamic systems and control theory , opening new avenues to translational applications of the human microbiome .
The methods section begins with a toy example to illustrate the construction of the universal interaction matrix A = NH ◦ Gs in Eq ( 4 ) , where steps: ( i ) N = 0 0 . 2 0 . 4 - 0 . 1 0 . 7 0 0 . 3 0 . 4 - 0 . 1 0 . 7 0 0 . 1 - 0 . 3 - 0 . 2 0 . 4 0 ( i i ) H = 10 0 0 0 0 0 . 2 0 0 0 0 0 . 2 0 0 0 0 0 . 4 ( i i i ) G = 0 1 1 1 1 0 1 0 1 0 0 0 0 0 1 0 ( i v ) s = 1 ( v ) [ A ] i i = - 1 final result: A = - 1 0 . 04 0 . 08 - 0 . 04 7 - 1 0 . 06 0 - 1 0 - 1 0 0 0 0 . 08 - 1 Given that H is diagonal , it scales the columns of N . If one thinks of A as the adjacency matrix of a digraph , then H scales all of the edges leaving a node . Thus one can consider H as controlling the interaction strength heterogeneity of A . Given the Hadamard product between H and G , the off-diagonal elements of G that are zero will result in the corresponding off-diagonal elements of A being zero as well . In the first study ( Fig 2 ) , to explore the impact of interaction heterogeneity on steady state shift , we varied the exponent −α of the power-law distribution of [H]ii to generate five different universal interaction matrices A of dimension 100 × 100 . For each universal interaction matrix A , the nominal component N consists of independent and identically distributed elements sampled from a normal distribution N ( 0 , 1 ) . The topology for this study was a complete graph and thus all the elements in G are equal to 1 . The heterogeneity element H is constructed in two steps . First , five different vectors h ¯ ( α ) ∈ R 100 are constructed where each element is sampled from a power-law distribution P ( α ) for α ∈ {7 , 3 , 1 . 6 , 1 . 2 , 1 . 01} . Then , each of the h ¯ ( α ) is normalized to have a mean of 1 , h = h ¯ / mean ( h ¯ ) . Finally the heterogeneity matrix is defined as H = diag ( h ) . For this study s = 0 . 07 , ensuring uniform asymptotic stability for the case of low heterogeneity ( see S1 Text Theorem 17 ) . The final step in the construction of A is to set the diagonal elements to −1 . For each α the following simulation steps were taken . There are a total of 100 species , S = {1 , 2 , … , 100} , in the metacommunity , and each of the 500 local communities contains 80 species , randomly chosen from S . The MATLAB command used to perform this step is randperm . The initial condition for each of the 500 local communities , x[ν] ( 0 ) , were sampled from U ( 0 , 1 ) . The dynamics were then simulated for 100 seconds using the MATLAB command ode45 . If any of the 500 simulations crashed due to instability or if the norm of the terminal discrete time derivative was greater than 0 . 01 then that local community was excluded from the rest of the study . Those simulations that finished without crashing and with small terminal discrete time derivative were deemed steady . Less than 1% of simulations were deemed unstable in the preparation of Fig 2 . It is worth noting that by constructing the dynamics as described above the abundance profiles for our synthetic data do not contain the heavy-tailed abundance profile that is observed in the HMP gut data [4] . The networks presented in the second row of Fig 2 were constructed by considering A as the weighted adjacency matrix of the network . Note that arrows showing directionality and self loops were suppressed . The links were color coded in proportion to the absolute value of the entries in A . For the last row of Fig 2 a clustering analysis was performed . For each α the steady state abundances of the 500 local communities were normalized so that we have 500 synthetic microbial samples . Then k-medoids clustering was performed for k ∈ {1 , 2 , … , 10} using the Jensen-Shannon distance metric ( S1 Text Sec . 5 . 1 ) . Silhouette analysis was performed to determine the optimal number of clusters and the clustering results were illustrated in the 2-dimensional principle coordinates plot . For S1 Fig the same steps as for the preparation of Fig 2 were performed , but with G representing the adjacency matrix of an Erdős-Rényi digraph with mean degree of 20 ( mean in-degree of 10 and mean out-degree of 10 ) and s = 1 / 10 . Details on the construction of an Erdős-Rényi digraph can be found in S1 Text Section 3 . 2 . 1 . For S2 Fig the same steps as above were performed in Fig 2 but with p = 5 , 000 local communities . Fig 4 is a macroscopic analysis of how network structure plays a role in the steady state shift with values of α ∈ ( 1 , 5] . For each topology ten different universal matrices A were generated . Fig 4a shows the results of a complete graph and for each of the ten universal A the same steps as in the preparation of Fig 2 were carried out . Fig 4b shoes the result of an Erdős-Rényi random digraph topology and for each of the ten A matrices the same steps as in the preparation of S2 Fig were carried out . Fig 4c shows results for networks with a power-law out-degree distribution with a mean out-degree of 10 , where the out-degree sequence uses the same h ¯ in the construction of H . More information on the construction of G for a power-law out-degree network can be found in S1 Text Sec . 3 . 2 . 2 . Fig 4d shows results for networks with a power-law out-degree distribution with mean out-degree of 10 and there is no interaction strength heterogeneity , i . e . H is the identity matrix . For this study the Silhouette Index was constructed from normalized steady state data using the Jensen-Shannon distance . S9 Fig is the same as Fig 4 , but instead of the Silhouette Index , the variance ratio criterion is used with the Jensen-Shannon distance , from normalized steady state abundance ( S1 Text Sec . 5 . 4 ) . In S10 Fig the Silhouette Index is determined from the Euclidean distance with normalized steady state abundance . Finally , in S11 Fig the Silhouette Index is determined by the Euclidean norm with the absolute steady state abundance . Fig 5 contains a PCoA analysis of the results from Fig 2 , but with the Euclidean distance being used instead of the Jensen-Shannon distance , making PCoA equivalent to principle component analysis . This enables us to project the open-loop control trajectories into the principle coordinates ( S1 Text Sec 5 . 6 ) . This procedure was also used in the preparation of S12 Fig . S13–S15 Figs contain system identification analyses for temporal gut microbiome data of two subjects [39] . The data is publicly available from the metagenomics analysis server MG-RAST:4457768 . 3-4459735 . 3 and can also be accessed ( as we did ) from Qiita ( http://qiita . ucsd . edu ) under study ID 550 . The processed data was downloaded as biom file “67_otu_table . biom” ( 2014-11-17 13:18:50 . 591389 ) . The Operational Taxonomic Units ( OTUs ) were then grouped from the genus level and up , depending on the availability of known classifications for OTUs , and converted to a txt file using MacQIIME version 1 . 9 . 0-20140227 with the command summarize_taxa . py with the options -L 6 -a true . Data was collected over 445 days with 336 fecal samples from Subject A and 131 fecal samples from Subject B . Details on the system identification algorithm are now given . The dynamics in Eq ( 2 ) can be approximated in discrete time as [32] e i ( k ) + log x i ( t k + 1 ) - log x i ( t k ) = r i + ∑ j = 1 n a i j x j ( t k ) ( 5 ) for i = 1 , 2 , … , n where k = 1 , 2 , … , N − 1 is the sample index , N is the total number of samples , tk is the time stamp of sample k , and e is an error term that arises because of the assumption that x ( t ) is constant over each interval t ∈ [tk , tk+1 ) . Eq ( 5 ) can be rewritten in terms of a regressor vector ϕ ( k ) = [ 1 , x 1 ( t k ) , x 2 ( t k ) , … , x n ( t k ) ] T , the parameter vector θi = [ri , ai1 , ai2 , … , ain] and the log difference yi ( k ) = log ( xi ( tk+1 ) ) − log ( xi ( tk ) ) as e i ( k ) + y i ( k ) = θ i ϕ ( k ) . The identification problem can then be defined as finding the parameter matrix estimate Θ ^ = [ θ ^ 1 T , θ ^ 2 T , ⋯ , θ ^ n T ] T of the true parameter matrix Θ = [ θ 1 T , θ 2 T , ⋯ , θ n T ] T . Letting y ( k ) = [ y 1 ( k ) , y 2 ( k ) , … , y n ( k ) ] T be the log difference vector for all species and Y = [y ( 1 ) , y ( 2 ) , … , y ( N − 1 ) ] be the log difference matrix the system identification problem can be compactly presented as min Θ ^ ‖ Y − Θ ^ Φ ‖ F 2 + λ ‖ Θ ^ ‖ F 2 where Φ = [ϕ ( 1 ) , ϕ ( 2 ) , … , ϕ ( N − 1 ) ] is the regressor matrix , ‖⋅‖F denotes the Frobenius norm , λ ≥ 0 is the Tikhonov regularization term [65] . The minimal solution to the above problem can be given directly as arg min Θ ^ ( ‖ Y − Θ ^ Φ ‖ F 2 + λ ‖ Θ ^ ‖ F 2 ) = Y Φ T ( Φ Φ T + λ I ) − 1 where I is the identity matrix . Next we discuss how missing data , zero reads , and λ were chosen . The difference equation in Eq ( 5 ) only uses sample data over two consecutive time samples . Therefore , in the construction of Y and Φ we only include samples that for which there is data from the next day as well . Also , given that logarithms are used , when a sample has zero reads for a given taxa , a read value of one is inserted . Then relative abundances are computed before the logarithm is taken . Finally we discuss how the regularization parameter is chosen . For S13 and S14 Figs the following cross-validation is performed . For Subjects A and B two-thirds of data was used for training and one-third for testing . More precisely , for each λ two-thirds of the data from Subject A and two-thirds of the data from Subject B were used to identify their corresponding dynamical constants . Then the combined error from the two test sets was used to find the optimal λ . The regularization value used in S15 Fig is simply the same regularization value used in S13 Fig . | We coexist with a vast number of microbes that live in and on our bodies , and play important roles in physiology and disease . Two interesting phenomena have been observed in the human microbiome . The first is the stratification of healthy individuals based on the relative abundances of their microbes , which holds promise for drastically improving personalized medicine . The second is the astounding success of fecal microbial transplantation in treating certain diseases related to disordered microbiomes . Surprisingly , both phenomena have not been analytically or quantitatively understood , despite a few early qualitative attempts . This work shows that through a dynamic systems and control theoretical approach the success of fecal microbial transplantation can be explained and that the microbiome-based stratification can be as simple as the existence of strongly interacting species . | [
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] | 2016 | On the Origins and Control of Community Types in the Human Microbiome |
The organization and the mechanisms of condensation of mitotic chromosomes remain unsolved despite many decades of efforts . The lack of resolution , tight compaction , and the absence of function-specific chromatin labels have been the key technical obstacles . The correlation between DNA sequence composition and its contribution to the chromosome-scale structure has been suggested before; it is unclear though if all DNA sequences equally participate in intra- or inter-chromatin or DNA-protein interactions that lead to formation of mitotic chromosomes and if their mitotic positions are reproduced radially . Using high-resolution fluorescence microscopy of live or minimally perturbed , fixed chromosomes in Drosophila embryonic cultures or tissues expressing MSL3-GFP fusion protein , we studied positioning of specific MSL3-binding sites . Actively transcribed , dosage compensated Drosophila genes are distributed along the euchromatic arm of the male X chromosome . Several novel features of mitotic chromosomes have been observed . MSL3-GFP is always found at the periphery of mitotic chromosomes , suggesting that active , dosage compensated genes are also found at the periphery of mitotic chromosomes . Furthermore , radial distribution of chromatin loci on mitotic chromosomes was found to be correlated with their functional activity as judged by core histone modifications . Histone modifications specific to active chromatin were found peripheral with respect to silent chromatin . MSL3-GFP-labeled chromatin loci become peripheral starting in late prophase . In early prophase , dosage compensated chromatin regions traverse the entire width of chromosomes . These findings suggest large-scale internal rearrangements within chromosomes during the prophase condensation step , arguing against consecutive coiling models . Our results suggest that the organization of mitotic chromosomes is reproducible not only longitudinally , as demonstrated by chromosome-specific banding patterns , but also radially . Specific MSL3-binding sites , the majority of which have been demonstrated earlier to be dosage compensated DNA sequences , located on the X chromosomes , and actively transcribed in interphase , are positioned at the periphery of mitotic chromosomes . This potentially describes a connection between the DNA/protein content of chromatin loci and their contribution to mitotic chromosome structure . Live high-resolution observations of consecutive condensation states in MSL3-GFP expressing cells could provide additional details regarding the condensation mechanisms .
Over the past decades mitotic chromosomes have been shown to have a high degree of organization . However , the exact configuration of the DNA molecule and its reproducibility within a chromosome are unknown . Consolidation of the results from diverse experimental approaches has not yet led to a thorough understanding of chromosome structure . Structural features of chromosomes are beyond the resolution of light microscopy , and tight compaction and lack of contrast in electron microscopy are among the main technical obstacles [1] , [2] . Even though the correlation between DNA sequence composition and its contribution to the chromosome-scale structure has been suggested before [3] , [4] , it is unclear if any DNA sequence is equally able to participate in intra- or inter-chromatin or DNA-protein interactions , leading to formation of mitotic chromosomes . Alternatively , some regions may be suited for this purpose more than others . Distinct models of mitotic chromosomes concentrate on different aspects of their structure [5] . Complete or partial extraction of chromosomes known to modify the native chromosome morphology has lead to the “radial-loop” model [6] , [7] . The original “radial-loop” model , with its later modifications based on biochemical and cytological experiments on fully condensed mitotic chromosomes [8] , postulated the existence of specialized DNA sequences anchoring chromatin loops to non-histone proteins at the cores of chromosomes approximately every 100 kbp and indispensable for a variety of other biological functions besides mitotic condensation . Models of this class do not specify the organization of the “30 nm fiber” between the anchoring points . Alternative , “hierarchical-coiling” models , based on observations of bulk chromatin at different stages of mitotic condensation with light or electron microscopy , in part due to insufficient resolution , conceptually overlook the possibility of correlation between the DNA sequence/protein composition of a specific chromatin region and its contribution to chromosome structure [9] . These models concentrate on “large-scale” structural features ranging in size from several tens to several hundred nm and therefore detectable with microscopy . Additional models with features borrowed from both “radial-loop” and “hierarchical coiling” models also have been proposed [10] , [11] . Despite identification of a number of proteins necessary for successful condensation and segregation of chromosomes in mitosis , key features of the structure , among which are banding patterns , reproducible chromosome geometry , and localization of topoisomerase II or condensin complexes within chromosomes , await their consolidation and explanation by a model . The question of whether all DNA sequences equally participate in the formation of chromosomes or whether the structural role is entrusted to a narrower class of specialized sequences remains unanswered . Here we probed the connection between the function of chromatin loci in terms of transcriptional activity and their position on mitotic chromosomes . Dosage compensated genes on the X chromosome in fruit flies provide a functionally distinct subset of genes with a possibility of labeling for fluorescence microscopy . As demonstrated by both cytological and chromosome-wide mapping studies , the euchromatic arm of the X chromosome is specifically bound by MSL complex throughout the cell cycle , including mitosis [12]–[15] , providing a convenient label for Drosophila melanogaster chromatin in its native state in live cells . As a source of mitotic chromosomes , we used diploid dividing cells from live fly tissues and freshly isolated primary cultures from cellularized embryos expressing GFP fused with MSL3 , one of the components of the Drosophila dosage compensation complex ( DCC ) , also called MSL complex ( Male Specific Lethal ) [16] . In live embryonic cultures or live 3rd instar larval tissues , specific MSL3-binding sites were detected through localization of MSL3-GFP , the feature characteristic of active genes on the male X chromosome . We further explored the potential relationship between transcriptional activity and location of sequences within mitotic chromosomes by immunostaining for specific post-translationally modified histones [17] , [18] . In a variety of organisms , both transcriptionally silent chromatin , characterized by relatively condensed DNA , and more decondensed transcriptionally active chromatin are marked by specific histone modifications [19] . Various histone marks may continuously stretch over regions of tens of kbp on the scale of gene clusters [20] , [21] and remain stable over several cell cycles [22]–[24] . In Drosophila , methylation of histone H3 at lysine 4 is associated with actively transcribed sequences and found in interbands of polytene chromosomes . Monomethylation of lysine 27 in H3 ( H3K27me1 ) is found at pericentric heterochromatin and in most euchromatic bands in polytene chromosomes [25]; monomethylated lysine 20 at H4 ( H4K20me1 ) is known to associate with chromocenter heterochromatin and a high number of euchromatic bands [19] . Combining novel fluorescence microscopy techniques with improved spatial and temporal resolution [26] and labeling of specific chromatin loci on the genome scale , we were able to study distribution of native chromatin loci within intact mitotic chromosomes in cells isolated from Drosophila embryos . Our results reveal a higher than expected degree of organization , suggesting that the radial distribution of specific chromatin loci are non-uniform in fly mitotic chromosomes . Actively transcribed sequences were found to localize at the periphery of chromosomes during mitosis as labeled by specific histone modifications in fixed cells or by MSL3-GFP in vivo , while silent chromatin occupied more internal positions .
To visualize discreet , specific loci in live Drosophila cells , we took advantage of the observation that ∼80% of active X chromosome genes are clearly marked by DCC and only ∼1% of genes are free of DCC . DCC specifically binds a subset of genes on the euchromatic arm of the X chromosome in males and is necessary for about 2-fold up-regulation in expression levels through local modification of chromatin [27] . For live imaging of the DCC , a fly line was created carrying four copies of an MSL3-GFP fusion , marking specific MSL3-binding sites on the X chromosome with GFP , and two copies of a Drosophila H2A histone variant , His2AvD of the H2A . F/Z family , fused with mRFP [28] labeling total chromatin ( Figure S1A ) . His2AvD is widely distributed in the genome . It is enriched in thousands of euchromatic bands and the heterochromatic chromocenter [29] . H2AvD , similar to H2A , associates less tightly with DNA in transcribed sequences . MSL3-GFP was fully functional as judged by transgenic rescue of msl3 mutant males . The transgene was expressed from the native msl3 promoter , and the presence of four copies did not cause ectopic staining as judged by the similarity to wild type MSL3 immunofluorescence staining patterns and the lack of cytoplasmic or nucleoplasmic background . To study the organization of the euchromatic arm of the X chromosome we focused on neuroblasts ( NBs ) [30]: diploid , dividing , and easily identifiable cells in dissected brains of 3rd instar larvae ( Figure S1 B ) and primary cultures isolated from 5–6-h-old embryos ( Figure S1C ) . After isolation , primary cultures and tissues survived for up to 4 h of imaging without a change in medium , going through several divisions with normal cytokinesis and producing normal progeny . Embryonic cultures were isolated and deposited in a drop of Chan-Gehring medium on a cover slip glued to a microscope slide and sealed with enough air . The identity of NBs was confirmed by their size , 8–12 µm , the presence of smaller cells around them , and antibody staining against Dpn [31] . Fixed samples were imaged with wide-field deconvolution microscopy and the recently implemented structured illumination microscopy ( SIM ) technique . SIM has doubled resolution in X , Y , and Z , as compared to conventional wide-field microscopy . The excitation illumination dose was minimized through the use of optimized and dedicated emission filter sets: DAPI ( 460±25 nm ) , FITC ( 515±15 nm ) , and RHOD ( 590±15 nm ) . The 3D positions , orientations , and magnifications of signals imaged with FITC and RHOD emission channels varied systematically due to the differences in alignment of cameras and the chromatic aberration . In multi-color images , these channels were aligned using parameters calculated from multi-color micro-bead Z-stacks for wide-field microscopy or SIM ( described in Supporting Methods in Text S1 ) . The values of parameters were found as an optimization problem solution minimizing differences between the positions of the beads in different channels ( Text S1 and Figure S2 ) . In live embryos , bright foci of MSL3-GFP binding scattered uniformly over the entire nucleus are first detected late in cell cycle 14 , during interphase before the first asynchronous division in the cellularized embryo . Within a single cell cycle , scattered MSL3-marked foci relocate into a relatively compact nuclear sub-region , ∼10%–30% of the nucleus area in projection ( Figure 1A ) . The signal retains its specificity and brightness during the entire cell cycle throughout development , making it possible to use embryonic and larval brain NBs for imaging of chromatin loci specific to male X chromosomes ( Video S1 ) . To study localization of MSL3-GFP-marked specific sites on X chromosomes , live primary embryonic cultures isolated from the fly line expressing both MSL3-GFP and His2AvDmRFP1 were imaged with wide-field microscopy . Fast Z-stacks , 20–30 sections per second , were collected , followed by deconvolution with a measured point-spread function ( PSF ) . In embryonic cultures , all interphase and late prophase through telophase cells showed peripheral localization of MSL3-GFP with respect to adjacent chromatin ( Figure 1A–F ) . An example Z-stack of a fixed metaphase NB expressing MSL3-GFP and His2AvDmRFP1 is shown in Video S2 . In early prophase , MSL3-GFP domains were often found sandwiched between bulk chromatin domains ( Figures 1B and 2A ) running the entire width of the chromosome . In live anaphase chromosomes of dissected 3rd instar larval brains imaged as Z-projections , MSL3-GFP was also peripheral in all observed cases . On all anaphase chromosomes , the MSL3-GFP pattern looked like two approximately parallel , ∼1–3 µm long , segments separated by ∼200–300 nm ( Figure 1E ) . Figure 1F shows a cross-section of a live anaphase chromatid where the mRFP1-marked chromatin signal is clearly inside the peripheral GFP signal . The majority of foci of interphase MSL3-GFP , similarly to mitosis , localized to the periphery of chromatin domains marked by His2AvDmRFP1 with occasional partial overlap ( Figure 1A ) . A similar organization of chromatin was observed in embryonic cultures fixed after isolation . This is very different from polytene chromosomes in which MSL3-GFP and His2AvDmRFP1 bands demonstrated , although not perfectly , a high degree of co-localization ( 1A ) . Immunostaining of fixed embryonic cultures for MSL2 ( another DCC component ) confirmed our finding that in X chromosomes , specific DCC-binding sites marked by MSL3-GFP target to the edges of compact chromatin domains in interphase or at the chromatid surface in mitosis ( Figures S3 and S4 and Video S3 ) . In live or fixed interphase cells expressing MSL3-GFP and His2AvDmRFP1 , the MSL3-GFP labeled X chromosome arm was a diffuse “cloud” of 20–30 foci of different intensity occupying 10%–30% of the nucleus area in projection , or 3–5 µm in linear dimensions . These foci were found at the periphery of condensed chromatin domains labeled with His2AvDmRFP1 . In early prophase cells , the MSL3-GFP labeled condensing arm is a relatively compact structure , ∼4–6 µm long and ∼1 µm thick ( Figure 2A ) . Interestingly , the MSL3-GFP signal was found not at the periphery of early prophase chromosomes but across their entire width between the bulk condensed chromatin regions ( arrowheads in Figure 2A ) . The early prophase MSL3-GFP signal was complementary to the bulk chromatin domains marked by His2AvDmRFP1 but not peripheral . Transition from the internal to peripheral localization of MSL3-GFP occurred between early and late prophase ( Figure 2A and B ) before segregation of sister chromatids became apparent . After segregation at metaphase , MSL3-GFP stayed peripheral on both chromatids ( Figure 2C ) . MSL3-GFP is found inside condensing early prophase chromosomes; however , starting from late prophase , MSL3-GFP signal is found only at the periphery of mitotic chromosomes in live or fixed cells . DCC localization to the periphery of condensed chromosomes suggests that mitotic chromosome organization is correlated with its function . However , an alternative explanation could be that MSL complex reorganizes during mitosis to be released from condensed regions , and then re-binds after decondensation . Despite the small size of MSL3-GFP ( ∼100 kDa ) , the fully assembled MSL complex is thought to be at least 1 MDa . If the accessibility of chromatin targets inside condensed mitotic chromatin is limited , DCC complexes displaced during mitotic condensation would need to re-assemble at their proper targets during decondensation . We found no evidence for significant or noticeable redistribution or loss of MSL3-GFP during mitotic condensation in agreement with the extremely stable association of MSL2 with its targets both during interphase and mitosis [32] . The dynamics of the MSL3-GFP-labeled chromatin regions could be followed during mitotic condensation . In our Video S1 , we show an example of progression from smaller faint speckles scattered over a large area to bright and compact foci on mitotic chromosomes through condensation and fusion . To further analyze possible redistribution of MSL complexes over the cell cycle , anaphase cells of embryonic cultures or larval brains were imaged for extended periods of time after cytokinesis to allow decondensation of chromatin and cell cycle-related redistribution of nuclear proteins . Dividing cells of embryonic cultures ( Figure 3A ) or in dissected 3rd instar larval brains ( Figure 3B ) were imaged with fast Z-stacks or Z-projections . During post-mitotic decondensation , MSL3-GFP-marked regions peripheral in anaphase moved outwards during decondensation , expanding 2–3-fold in the area over a period of 10–20 min , shown in time-series in Figure 3A and B and Video S4 . The unlabeled regions of chromosomes , internal during anaphase , remain unlabeled for up to 30 min or more than a half cell cycle duration , when accessibility of the euchromatic X chromosome arm should no longer be an issue . For embryonic cultures expressing MSL3-GFP and His2AvDmRFP1 , it takes 4 to 6 min for a dividing cultured NB to proceed from mid-anaphase to a state in G1 with a round nucleus , fully decondensed chromatin , and reformed nucleoli as judged by His2AvDmRFP1 staining . The increase in the area of the MSL3-GFP-marked region occurred exclusively through expansion of chromosome arm , not redistribution or de novo binding of MSL3-GFP . We conclude that the regions devoid of MSL3-GFP signal in mitotic chromosomes do not appear to be targets of MSL complex upon decondensation . Another line of evidence for limited re-distribution comes from the low , little changing cytoplasmic MSL3-GFP background over the entire cell cycle . The background intensity of MSL3-GFP in mitotic cytoplasm is comparable to the uniform background intensity outside the cells created by out-of-focus and scattered light . For a metaphase cell , the outside background was 15–35 units ( mean 24 ) , the cytoplasm was 25–55 ( mean 38 ) , compared to the labeled X chromosome arm—125–525 ( mean 305 ) . In interphase , the nuclear and cytoplasmic background intensity of MSL3-GFP is comparable or higher than in mitosis . This suggests that in mitosis the majority of MSL3-GFP is divided between daughter cells by traveling on chromosomes and that there is minimal loss of MSL3-GFP from chromatin targets during mitotic condensation . The MSL3-GFP labeled loci often surround an area of no or low GFP signal in live embryos of dissected tissues ( Figure 3C and D and Figure S1C and B , respectively ) , despite their extremely dynamic behavior in interphase . In the majority of interphase nuclei , MSL3-GFP labeled regions demonstrate apparent reduction of GFP signal intensity in the middle of the labeled arm as shown in Figure 3C and D . These observations are consistent with the previous FISH studies of fixed tissue culture cells [33] , [34] . The distribution of MSL3-GFP during mitosis or interphase is clearly distinct from the binding patterns of perichromosomal layer proteins , such as Ki-67 and nucleophosmin , which are associated with the outer surface of chromosomes in mitosis and populate the vicinity of chromosomes in the form of granules and fibrils [35] . MSL3-GFP and components of the DCC remain bound exclusively to chromatin locations of the euchromatic X chromosome arms at all stages of the cell cycle . In contrast , the proteins of the perichromosomal layer cover the periphery of all mitotic chromosomes over their entire length , except centromeres , from prophase to telophase . In interphase , the proteins of the perichromosomal layer are found in nucleoplasm and cytoplasm with preferential accumulation at nucleoli . Dosage compensated genes represent a large subset of active male X chromosome genes with the transcription rate up-regulated about 2-fold as compared to non-compensated genes [27] , [36] . Drosophila chromatin regions of different transcription states are known to be marked with specific histone modifications . Patterns of covalent core histone modifications are established in Drosophila embryos by cell cycle 15 . We chose di- and trimethylation of lysine 4 on histone H3 ( H3K4me2 , 3 ) as a marker for active euchromatin , and H3K27me1 and H4K20me1 as markers for silent , non-coding regions in euchromatic chromosomal arms for immunofluorescence . Double-antibody staining served two purposes: ( a ) to study the distribution of actively transcribed sequences over the entire X chromosome and autosomes , and ( b ) to study the distribution of histone modifications specific to different transcription states . In mitotic chromosomes , anti-H3K27me1 and anti-H4K20me1 antibodies were found to stain all chromosomes uniformly along their lengths , on both euchromatic and heterochromatic arms . In contrast , anti-H3K4me2 , 3 was limited to euchromatic arms of mitotic chromosomes , an indication of the specificity of the antibodies . We found that immunofluorescence signals from anti-H3K27me1 and anti-H4K20me1 were consistently found at more internal locations on chromosomes compared to the anti-H3K4me2 , 3 , as summarized in Figure 4A–C for mitotic cells . Line profiles were used for better visualization of non-uniform distribution of different antibodies ( Figure 4D ) . Anti-H3K4me2 , 3 , as well as anti-MSL2 , antibodies always stained the periphery of chromosomes , with a significant fraction of the signal found outside the visible DAPI signal . This is different from anti-H3K27me1 and anti-H4K20me1 signals , which were found mostly inside chromosomes with no or little signal extending into DAPI-free regions . In multiple examples , anti-H4K20me1 staining coincides with the DAPI signal uniformly staining chromosomes ( Figure 4C ) . Anti-H3K27me1 signal stains , though not uniformly , the entire width of chromosomes or often with visible reduction of signal at chromosomal cores ( Figure 4A and B ) . A more internal and uniform signal of anti-H4K20me1 antibody compared to anti-H3K27me1 is consistent with localization of H4K20me1 to relatively more condensed regions of genome ( chromocenter and few euchromatic bands in polytene chromosomes ) . To support these observations , the widths and distributions of fluorescent labels after immunofluorescence staining with different antibodies or in live cells were measured ( Table 1 ) . The widths of chromosomes , immunostaining , and MSL3-GFP signals were measured as FWHM in averaged profiles . It is seen that anti-H3K4me2 , 3 and live MSL3-GFP signals localize to the periphery of mitotic chromosomes and are depleted at the cores of mitotic chromosomes relatively to the anti-H3K27me1 and anti-H4K20me1 signals , which show less depletion at the core ( Figure S5 ) . This is additional evidence that active coding sequences target to the periphery of chromosomes in mitosis . Hypothesis testing of the null hypothesis of equal means was done for each pair of data sets for different labeling methods and summarized in Table S1 . In support of our observations and measurements , the null hypotheses of equal means were rejected for the following pairs: H3K4me2 , 3 and H4K20me1; H3K4me2 , 3 and H3K27me1; H4K20me1 and MSL3-GFP; MSL3-GFP and H3K27me1 . Rejection of the null hypothesis of equal means is not supported for the following pairs: H3K4me2 , 3 and MSL3-GFP; H3K27me1 and H4K20me1 . This is in agreement with similarity in the distributions of the signals and their widths . All primary antibodies used for immunofluorescence were of the monomeric IgG type , and secondary antibodies were F ( ab' ) 2 fragments labeled with a fluorophore . In fixed interphase cells , actively transcribed sequences labeled with anti-MSL2 or anti-H3K4me2 , 3 ( pseudo-colored magenta ) are found outside chromatin regions labeled with DAPI and were complementary to them ( Figure 5A and B , respectively ) . In contrast , anti-H3K27me1- and anti-H4K20me1-labeled silent chromatin was a subset of DAPI stained chromatin largely overlapping with it ( Figure 5C and D , respectively ) . To investigate the accessibility of mitotic chromatin to antibodies , we stained fixed mitotic cells with antibodies to Barren and to CID-GFP , both known to be buried inside mitotic chromosomes . Barren , a member of the kleisin family and an ortholog of human CAP-H , binds to the head domains of the SMC heterodimer in a complex with two other non-SMC subunits [37] . As a part of the condensin complex , Barren accumulates at the core regions of mitotic chromosomes starting in prophase through metaphase . Anti-barren [38] immunofluorescence signal was found at the central core regions of the DAPI stained chromosomes imaged with wide-field or SIM ( Figure S6A and B , respectively ) , similar to live distributions ( Y . Strukov , unpublished results ) . CID , a Drosophila ortholog of human CENP-A , is an H3-like protein that replaces canonical H3 in all eukaryotic centromeres [39] . It was proposed that CID is the epigenetic mark and a foundation for fly centromeres and localizes beneath the kinetochore with some overlap with the inner kinetochore [40] . Anti-GFP immunofluorescence of CID-GFP embryonic cultures gave a uniform labeling over all centromeres in mitotic cells ( the same as in live cells ) , demonstrating accessibility of chromatin buried by the kinetochore structures to antibodies under our fixation conditions ( Figure S6C and D ) . Centromeres of CID-GFP expressing cells had the same size and shapes irrespective of the imaging modality: live imaged with wide-field deconvolution , antibody-stained imaged with wide-field deconvolution , or antibody-stained imaged with SIM ( Figure S6E ) , demonstrated by intensity profiles ( Figure S6F ) .
A 5 . 5-kb BamHI genomic fragment containing the promoter and open reading frame of the msl3 gene [41] was subcloned from cosmid msl3-5-1 ( AE003560 . 1 position 60298–92793 ) into the pBluescript II SK ( − ) vector [12] . A blunted NcoI/NotI fragment containing eGFP from the pEGFP-N1 vector ( Clontech ) was subcloned in-frame into the CelII blunted pBS-msl3 construct . The resulting MSL3-GFP BamHI fragment was subcloned into pCaSpeR3 to make the final MSL3-GFP–pCaSpeR3 construct . Several independent transgenic lines were produced by P-element-mediated transformation [42] . Two independent lines , one with the transgene on the 2nd and one with it on the 3rd chromosome , were crossed to generate a stock with homozygous MSL3-GFP on both chromosomes ( 4 copies ) . Fly line msl3-gfp , His2AvDmRFP1; msl3-gfp was created by recombination of msl3-gfp; msl3-gfp with a His2AvDmRFP1 transgenic line [28] for dual-color live experiments; CID-GFP line was generated in the lab of S . Henikoff ( FHCRC ) . Embryonic cultures were isolated according to a previously published protocol [30] . The fixation and immunostaining protocols were adapted from [43] . Antibodies were from Abcam ( Cambridge , MA ) : rabbit polyclonal anti-H4K20me1 ( ab9048 ) , and anti-GFP ( ab290 ) , mouse monoclonal anti-H3K4me2 , 3 ( ab6000 ) , and Upstate Scientific: rabbit anti-H3K27me1 ( 07-448 ) , all monomeric IgG . Rabbit anti-MSL2 antibody was generated in the Kuroda laboratory [44] . Goat anti-mouse or anti-rabbit secondary antibodies were from Molecular Probes: A-11017 , A-11018 , A-11070 , A-11071 . Live , wide-field optical sectioning and SIM were done on a custom-made inverted microscope [26] supplied with a set of excitation lasers and cooled back-thinned CCD cameras ( Andor ) . Deconvolution and SIM reconstruction were done using a measured PSF [45] . Image processing and computations were done using Priism , Python ( align . py and simplex . py ) , and Octave scripts available upon request ( contact YGS: yu . strukov@gmail . com ) .
Our investigation has provided insights into mitotic chromatin organization and its connection to chromatin function . We observed several novel features of mitotic chromosomes in Drosophila cells . First , MSL3-binding sites , specific to the X chromosome , target to the periphery of mitotic chromosomes . Second , spatial distribution of chromatin loci within mitotic chromosomes was correlated with their functional properties judged by the core histone modifications . Third , during late prophase-to-anaphase condensation of chromatids , active sequences remain peripheral , suggesting rearrangement of chromatin within prophase chromatids and arguing against simple coiling of prophase chromatids during condensation . Although several investigations have been undertaken in the past , to our knowledge , ours is the first when native chromosomes in live cells have been studied for localization of specific DNA sequences at high resolution . All imaging systems with multi-color capability are known to suffer from chromatic aberrations and offsets in translation , rotation , and magnifications between color channels . For interpretation of multi-color data sets , correct superimposition of different color channels was therefore critical . To exclude the influence of the chromatic aberration of the objective lens , variations in the CCD camera specifications , and differences in optics between different emission channels , control multi-color data sets were collected with multi-color micro-beads , separately for wide-field or SIM and compensated to a sub-pixel accuracy using custom software ( Supporting Methods in Text S1 and Figure S2 ) . Based on these measurements , we could conclude that peripheral localization of specific sequences marked by DCC or core histone modifications was not due to chromatic aberration or differences in the optics of individual channels . MSL complex specifically marking dosage compensated genes in Drosophila provides a means for visualization of a functionally distinct fraction of the genome . The 22 Mbp X chromosome arm , predicted to contain about a thousand active genes , is ∼5% of the total DNA content of a diploid male Drosophila cell . There is evidence that ∼80% of active genes on the X chromosome are bound by DCC and less than 1% are clearly free of it , the rest of the genes are bound by intermediate amounts of MSL complex [46] . MSL3 binds preferentially to 3′ ends of transcribed regions of most active genes . In larval polytene chromosomes , MSL complex binds to gene-rich interbands , complementary to DAPI-stained bands , and co-localizes with H4 acetylated at lysine 16 , a specific mark for open , transcriptionally active chromatin in general , both in vivo and in vitro [47] . Little is known about MSL binding dynamics , however it is possible that MSL localization is established at most active gene clusters early in development and maintained in a relatively static pattern throughout development [47] . However , blocking transcription can inhibit MSL complex binding at a transgenic target , suggesting that the MSL pattern is not completely static [48] . There is a possibility that MSL complex changes its localization in condensing chromosomes , but the fact that it looks similar to H3K4me2 , 3 ( and different from H4K20me1 ) is strong evidence that it has stayed with the active regions . Our results support the possibility that little or no change in MSL targeting occurs during mitosis . We have shown that there is no appreciable dissociation and relocation of MSL3-GFP from chromosome targets to other cellular compartments at the beginning or during mitosis by measuring the cytoplasmic and nucleoplasmic backgrounds of MSL3-GFP . The entire population of MSL3-GFP remains bound to the X chromosome . No significant new binding of MSL3-GFP to the chromosome targets was observed during post-mitotic decondensation ( Figure 3A and B ) . This is consistent with a number of earlier findings: MSL complex does not bind at significant levels to non-coding sequences and more than 90% of MSL complexes are found within genes [13] , [14]; there has been found little [12] , [49] or no [50] variation in the binding levels at specific loci during development . Redistribution of MSL3-GFP within the X chromosome by fast dissociation from the interphase set of targets to a new non-overlapping mitotic set would be hard to imagine for several reasons . First , most genes on the X chromosome in interphase are bound by MSL complexes [16] and there is no binding of MSL complex to non-coding DNA at the levels sufficient to accommodate the entire pool of DCC . This suggests a great deal of overlap between interphase and mitotic MSL complex binding sites . Second , available data on the dynamics of MSL binding to its targets show that the time-scale for MSL targeting is on the order of hours [50] , which is not consistent with very fast cell mitoses and cycles of chromatin condensation-decondensation in developing Drosophila tissues . Testing mitotic distributions of MSL3 with ChIP at high resolution is currently unfeasible due to the technically challenging procedure of isolating sufficient quantities of purified mitotic cells from dissected tissues and embryonic cultures from Drosophila . At the resolution of fluorescence microscopy analysis we have demonstrated that binding of MSL3-GFP is not cell-cycle stage specific . We chose His2AvDmRFP1 as a contrasting fluorescent marker because it is found in the heterochromatic chromocenter , on transcribed and non-transcribed genes and in non-coding euchromatin [29] . The current concepts of nuclear organization suggest a relationship between the activity of chromatin loci and their positions within nuclei or interphase chromosomes [51] . However , whether this principle can be extended to also include live and fixed mitotic chromosomes has not been investigated . The question of whether antibodies faithfully represent the imaged features is always important . There are two aspects to this problem: first , uniform accessibility of chromosomal epitopes; and second , the finite size of the antibody complex with a potential to change the size and shape of sampled features . We argue that with our sample preparation and staining techniques mitotic chromatin was available for antibodies . Anti-barren staining produced a continuous axial pattern indicating that internal regions of chromosomes were uniformly accessible . Anti-GFP antibody staining of embryonic cultures isolated from CID-GFP expressing fly embryos gave the patterns of centromere labeling with similar shapes and sizes as in live cells . Consistent with our observations are previous studies of centromere and kinetochore organization where both structures were shown to be accessible after formaldehyde fixation to various antibodies raised against different centromeric or kinetochore proteins [52] , [53] . It has been demonstrated that in live cells , proteins with molecular dimensions in the size range of components of the transcription machinery ( several hundred kDa ) can diffuse freely inside condensed chromatin domains [54] . The mass of individual IgG molecules is ∼150 kDa , and the size of the primary and secondary fluorophore-labeled antibody complex has been reported to be about 20 nm [55] , which makes it small enough to faithfully reflect the features of imaged objects at a resolution of about 200 nm used for immunofluorescence experiments . Using both immunofluorescence of fixed cells and live observations we showed that MSL3-GFP stays peripheral from late prophase to telophase in the same cell arguing against hierarchical coiling condensation [1] . If consecutive coiling is involved , the large-scale fibers have to have persistence length on the order of their thickness , and simultaneously , intra-fiber rearrangements have to be involved to keep the genes at the periphery of the X chromosome as mitotic condensation progresses . Our working model is shown in Figure 6: patches of chromatin carrying active genes , spanning the entire width of chromosomes at early prophase , become peripheral from late prophase through telophase as a result of large-scale rearrangements within condensing chromosomes . An interesting explanation for why active DNA sequences are found at the periphery of mitotic chromosomes comes from biochemical studies of the “bookmarking” mechanism that helps cells remember which genes were active before mitosis . It was reported that active promoters/genes remain bound by a transcription factor TFIID in mitosis [56] and may escape the condensin complexes action through recruitment of the TBP-PP2A mitotic complex [57] . Transcribed sequences show more mitotic TBP binding than silent DNA . TBP interacts with the condensin I subunit CAP-G and condensin inhibitor phosphatase PP2A during mitosis at many chromosomal sites active before mitosis . Our findings are consistent with the results of a number of earlier studies concentrated on the localization of specific DNA sequences or sequences of specific properties on mitotic chromosomes . However , our conclusions are based on observations of native chromatin loci in the context of unperturbed chromosomes . Specifically stained AT-rich DNA sequences in Munjac chromosomes formed a full-diameter coil at gene-poor regions and uncoiled in gene-rich regions staying at the core [7] . In accordance with the radially non-uniform organization , the AT-rich sequences were at the core regions of the gene-rich bands , while the rest of DNA in the bands was more peripheral . Radially different and reproducible positions of specific sequences after FISH of salt-extracted isolated chromosomes was observed in agreement with the radial-loop model , with no indication , however , of their positions in native chromosomes [6] . Preferentially external lateral positions of specific sequences on mitotic chromosomes in mitotic spreads have also been reported after FISH [58] . However , the conclusions were not as convincing due to limited resolution in the images and FISH procedure-induced disturbance of native morphology . The degree of reproducibility of radial positions of stably transfected and gene amplified lac op repeats varied in different tissue culture cell lines , probably due to position effects [4] , [59] . Lac op repeats could be found either at the core regions of chromosomes or throughout the width of chromosomes . Reproducibility of positioning of specific sequences might be related to functional contributions of diverse classes of loci to the structure . Actively transcribed sequences may be spared a structural function or cannot be involved because of their specific protein composition or kinetic restrictions due to delay in condensation compared to silent or non-coding DNA . Alternatively , there could be a difference in degree of condensation or in its temporal sequence between peripheral and more central regions of mitotic chromosomes . Together , our results suggest novel structural features of mitotic chromosomes that can contribute to the understanding of mitotic condensation , with important implications for understanding the connection between chromatin organization and its epigenetic regulation . | Mitotic chromosomes of eukaryotes are relatively large rod-like cellular organelles , about 1 µm in diameter and 10 µm long , of well-studied composition but unknown structure . The question of whether all DNA sequences equally contribute to the interactions leading to the formation of mitotic chromosomes has never been asked . To find an answer , we determined whether the radial positions of specific chromatin loci within mitotic chromosomes were reproduced at every cell cycle or were purely random . Based on fluorescence microscopy images of live or fixed chromosomes in cells from Drosophila embryos or Drosophila larval tissues expressing the MSL3-GFP fusion protein from a transgene , we report that the large-scale organization of mitotic chromosomes is reproduced not only longitudinally , as in the well-known chromosome banding phenomenon , but also radially . Actively transcribed , dosage-compensated genes of the Drosophila male X chromosome were always found at the periphery of mitotic chromosomes , starting from late prophase . Histone modifications specific to active chromatin were found to be more peripheral compared to silent chromatin that tended to be more central in the condensed chromosome . These findings are both exciting and significant for the field of cell and chromatin biology because they may help reconcile the old controversy between the existing models of chromosome structure that posit either radial loops of chromatin or consecutive coiling . In addition , we offer new insights into the mechanisms of mitotic condensation and suggest a link between structural and functional roles of different chromatin domains . | [
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] | 2011 | Evidence of Activity-Specific, Radial Organization of Mitotic Chromosomes in Drosophila |
Chronic infection by Trypanosoma cruzi could cause heart conduction disturbances . We sought to analyze electrocardiographic abnormalities among children with chronic T . cruzi infection with and without trypanocidal treatment with benznidazole . We studied 111 children 6–16 years of age with asymptomatic chronic T . cruzi infection who were recruited in 1991–1992 in Salta , Argentina . Most children were randomly assigned to benznidazole 5 mg/Kg/day ( n = 47 ) or matching placebo ( n = 48 ) for 60 days . Remaining children ( n = 16 ) received treatment with benznidazole 5 mg/Kg/day open-label . Electrocardiograms were obtained at baseline and in 1995–1996 , 1998 , 2000 and 2005 , and were analyzed using the Buenos Aires method . Among the 94 children with an electrocardiogram at baseline , 8 ( 8 . 5% ) had electrocardiographic abnormalities , including 4 ( 4 . 7% ) children with right bundle branch block . Proportion of abnormal electrocardiograms in the full population ( n = 111 ) remained constant over time ( media follow-up 8 . 6 years ) . Multivariable adjusted prevalence ratios ( 95% confidence interval [95%CI] ) for electrocardiographic abnormalities in 1995–1996 , 1998 , 2000 and 2005 comparing children treated with benznidazole versus those not treated were 2 . 76 ( 0 . 66 , 11 . 60 ) , 2 . 33 ( 0 . 44 , 12 . 31 ) , 3 . 06 ( 0 . 48 , 19 . 56 ) , and 1 . 94 ( 0 . 33 , 11 . 25 ) , respectively . Among the 86 children with a normal electrocardiogram at baseline , 16 ( 18 . 6% ) developed electrocardiographic abnormalities during follow-up . The multivariable adjusted hazard ratio for incident electrocardiographic abnormalities comparing children treated with benznidazole versus those not treated was 0 . 68 ( 95%CI: 0 . 25 , 1 . 88 ) . Electrocardiographic abnormalities are frequent among children with chronic T . cruzi infection . Treatment with benznidazole for 60 days may not be associated with less electrocardiographic abnormalities .
Chagas’ disease is a chronic condition characterized by cardiovascular , digestive and neurologic manifestations , which is caused by a vector borne parasitic infection ( Trypanosoma cruzi ) endemic in Latin America [1] . Chagas’ disease is an important cause of premature death , disability , reduced quality of life and high costs for health systems in endemic countries [1 , 2] . Emigration from Latin America ( mainly to US , Canada , Europe and Australia ) as well as alternative routes of transmission ( i . e . , vertical or through blood transfusion ) have transformed Chagas’ disease in a major global threat [3–6] . Every year , Chagas’ disease is responsible for 806 , 170 disability-adjusted life-years lost and US$ 627 . 46 million in direct healthcare costs worldwide , with more than 14% of these costs emanating from non-endemic countries [7] . Most individuals with Chagas’ disease have chagasic cardiomyopathy [1 , 8 , 9] . Chagasic cardiomyopathy usually appears in the adulthood , after 10 to 20 years of chronic infection by T . cruzi [1] . However , early stages of chagasic cardiomyopathy can also be detected among children or adolescents [10] . Chagasic cardiomyopathy is commonly preceded by heart conduction disturbances , which can be detected through electrocardiography [9 , 11–13] . Electrocardiographic abnormalities are considered an important marker of chagasic cardiomyopathy severity and progression [9 , 11] . Benznidazole is effective to induce parasite clearance [14–17] and is recommended for treatment of acute , congenital and reactivated T . cruzi infection as well as among children with chronic infection [18 , 19] . Evidence from animal models suggest that treatment with benznidazole could prevent or control chagasic cardiomyopathy [20] , although results from observational studies have been controversial [16] . Treatment with benznidazole for 60 days was not effective to prevent clinical progression in adults with chagasic cardiomyopathy ( mean age 55 years ) in a large randomized clinical trial ( Benznidazole Evaluation for Interrupting Trypanosomiasis , BENEFIT , NCT00123916 ) [21] . These results support current guidelines which do not recommend treatment with benznidazole among individuals with chronic T . cruzi infection 50 years of age or older or with advanced cardiomyopathy [18 , 22] . Few studies analyzed the characteristics and natural history of electrocardiographic abnormalities among children with chronic T . cruzi infection and the effect associated with treatment with benznidazole [16 , 19] . The main objective of the present study was to investigate the presence of electrocardiographic abnormalities in a cohort of children with chronic T . cruzi infection , some of whom received treatment with benznidazole . We hypothesized that electrocardiographic abnormalities will be frequent among children with chronic T . cruzi infection and less common among those treated with benznidazole versus those not treated .
We conducted a retrospective cohort study using data collected during a double-blind randomized controlled clinical trial with extended follow-up . The clinical trial was conducted in Salta province , Argentina from 1991 through 1996 and was aimed at investigating the parasite clearance and safety associated with treatment with benznidazole among children 6 to 12 years of age with asymptomatic chronic infection by T . cruzi [15] . The region where the study was conducted had continuous surveillance for T . cruzi vectors by sanitary agents since 1982 , and the possibility of reinfection after treatment was considered low . During enrolment in 1991–1992 , children attending local elementary schools were screened by history , physical examination and 3 serology tests for T . cruzi using different techniques: indirect hemagglutination inhibition , indirect immunofluorescence assay , and enzyme-linked immunosorbent assay . Of relevance to the current analysis , information on age , sex , body weight and place of residence was collected . Children were considered eligible for the clinical trial if they had chronic infection by T . cruzi , defined by at least 2 positive serology tests using different techniques . Exclusion criteria were presence of any acute infection or chronic condition , or unstable residence . Children with Chagas’ disease , defined by the presence of cardiovascular , digestive or neurologic symptoms , were excluded from the study . Children included in the clinical trial were matched by age and place of residence , and randomly assigned to benznidazole 5 mg/Kg/day ( benznidazole group , n = 55 ) or placebo ( placebo group , n = 51 ) for 60 days . Participants were followed for 48 months through 1995–1996 . At the end of the clinical trial , all participants in the placebo group were offered treatment with benznidazole if follow-up for adverse events was considered feasible . A total of 18 children in the placebo group completed a properly documented treatment with benznidazole open-label in 1997 , following the same treatment protocol as in the clinical trial . No treatment with benznidazole was documented among the remaining 33 children assigned to placebo . An enzyme-linked immunosorbent assay using a flagellar calcium-binding protein F29 ( F29 ELISA ) and xenodiagnosis were performed in children included in the clinical trial in 2005 . A cohort of 19 children with asymptomatic chronic infection by T . cruzi who completed the study anamnesis , physical examination and serology tests but were not included in the clinical trial received treated with benznidazole open-label 5 mg/Kg/day for 60 days in 1991–1992 ( benznidazole cohort ) . Reasons for exclusion from the clinical trial included age <6 or >12 years , abnormal laboratory parameters ( leukocytosis or anemia ) , intestinal parasitosis , and unstable residence . Electrocardiograms were obtained from children enrolled in the clinical trial and in the benznidazole cohort in 1991–1992 , 1995–1996 , 1998 , 2000 and 2005 . For the present analysis , we included children enrolled in the clinical trial or in the benznidazole cohort who had at least 1 valid electrocardiogram to assess electrocardiographic abnormalities . Written informed consent to participate in the study was obtained from legal guardians before assessment for enrollment and once again before randomization among those included in the clinical trial . Written informed consent to participate in subsequent examinations ( i . e . , in 1998 , 2000 and 2005 ) was obtained from the participant or the legal guardian , according the participant’s age . The protocol was reviewed and approved by the Institutional Review Board of the “Instituto Nacional de Chagas Dr . Mario Fatala Chaben” , Buenos Aires , Argentina before the study initiation . Study procedures were conducted in accordance with the principles stated in the Declaration of Helsinki . All electrocardiograms were analyzed by the same cardiologist ( NP ) using the Buenos Aires method [23] . The Buenos Aires method is an electrocardiographic recording and reading guide designed for epidemiological studies on Chagas’ disease . This method analyzes 5 electrocardiographic measurements and 48 items classified into 9 diagnostic categories: overall assessment , rhythm , supraventricular arrhythmias , ventricular arrhythmias , atrioventricular conduction disturbances , ventricular conduction defects , abnormal initial QRS complex , primary ST-T wave changes , and miscellaneous . The inter-rater agreement to identify electrocardiographic abnormalities using the Buenos Aires method is substantial ( kappa statistic: 0 . 66 , standard error: 0 . 02 ) [23] . Electrocardiograms with missing date or coded as not evaluable by the cardiologist were excluded from the current analysis . Electrocardiographic abnormalities were defined by any abnormal finding identified using the Buenos Aires method . Potential confounders assessed at baseline which were used for statistical adjustment in the present analysis include age , gender , body weight and rural residence . Baseline characteristics of participants included in the current analysis who were randomly assigned to benznidazole and placebo , separately , and those in the benznidazole cohort are reported using median and 25th-75th percentiles for continuous variables , and percentage for binary variables . Differences between groups were analyzed using Kruskal-Wallis or Fisher’s exact tests , as appropriated . We calculated the proportion of electrocardiograms with electrocardiographic abnormalities in each assessment period ( i . e . , 1991–1992 , 1995–1996 , 1998 , 2000 and 2005 ) , separately . Some participants have more than 1 electrocardiogram recorded in the same period . Therefore , we used a mixed effect model with random intercept to estimate appropriated 95% confidence intervals ( CI ) taking into account repeated measurements from a same participant . We used the last observation carried forward method for the main analysis because some participants did not have an electrocardiogram in each assessment period . The regression model was fit using the maximum likelihood method with a binomial distribution and log link , and including the assessment periods as dummy variables with 1991–1992 as the reference . We used least-squares means to estimate the proportion and 95% CI for electrocardiographic abnormalities in each period . We tested for a trend in the proportion of electrocardiograms with electrocardiographic abnormalities over time by analyzing the assessment period as an ordinal variable . We used a panel analysis and Poisson regression models with robust variance to analyze the association between treatment with benznidazole and electrocardiographic abnormalities . We used Poisson regression models because log-binomial regression models including multivariable adjustment did not converge . Model 1 included terms for each assessment period using dummy variables as described above and an indicator variable for treatment with benznidazole . Model 2 included variables in Model 1 plus age , gender , body weight and rural residence . All models included interactions between each assessment period and treatment with benznidazole to estimate the effect modification associated with benznidazole after baseline [24] . Prevalence ratios and 95% CI for electrocardiographic abnormalities were estimated after exponentiation of coefficients for the interactions between the assessment periods and treatment with benznidazole . These prevalence ratios represent the relative effect of benznidazole on electrocardiographic abnormalities after adjusting for baseline differences in the proportion of electrocardiograms with abnormalities between children treated and not treated with benznidazole . For our main analysis , we considered that children randomly assigned to benznidazole in the clinical trial and those in the benznidazole cohort were treated with this medication ( intention-to-treat analysis ) . Several sensitivity analyses of the association between treatment with benznidazole and electrocardiographic abnormalities were conducted . First , we repeated the analysis without using the last observation carried forward method . Second , we conducted a per-protocol analysis , considering children who did not complete 30 days of treatment with benznidazole as not treated , and children who received treatment with benznidazole in 1997 as treated in 1998 , 2000 and 2005 . We used 30 days to determine whether children were treated as prior studies have shown that a treatment with benznidazole shorter than 60 days can be effective to induce T . cruzi clearance [25 , 26] . Finally , we repeated the analysis limited to children enrolled in the randomized controlled clinical trial . We conducted analyses limited to children without electrocardiographic abnormalities at baseline . Baseline characteristics of participants in these analyses as well as the characteristics of incident electrocardiographic abnormalities and the proportion of electrocardiograms with abnormalities over time were calculated as described above . We used a Weibull regression model ( accelerated failure time ) to conduct an interval-censoring analysis of the association between treatment with benznidazole and incident electrocardiographic abnormalities among children with a normal electrocardiogram at baseline [27] . Hazard ratios and 95% CI for incident electrocardiographic abnormalities associated with treatment with benznidazole were calculated as described by Collett [28] . In addition to a crude model , a multivariable adjusted model was fit , including adjustment for age , gender , body weight and rural residence . Finally , we analyzed F29 ELISA and xenodiagnosis results in 2005 among children treated with benznidazole in the clinical trial who had incident electrocardiographic abnormalities . All statistical analyses were performed using SAS v . 9 . 4 ( SAS Institute Inc . , Cary , NC ) . All tests were 2-sided and used a level of significance alpha <0 . 05 .
Children in the benznidazole cohort ( n = 19 ) were similar to participants enrolled in the clinical trial ( n = 106 ) regarding gender ( 47 . 4% vs 52 . 8% females , Fisher’s exact test p-value: 0 . 80 ) and place of residence ( 57 . 9% vs 45 . 3% rural residents , p-value: 0 . 33 ) , but were older ( median age in years [25th-75th percentiles]: 10 [9–14] vs 10 [8–11] , Wilcoxon rank-sum test p-value: 0 . 05 ) . Between 1991 and 2005 , 500 electrocardiograms were obtained from this population . We excluded electrocardiograms with missing date ( n = 1 ) and those coded as not evaluable by the cardiologist ( n = 14 ) . After these exclusions , 111 children had at least 1 valid electrocardiogram during the study period ( 485 electrocardiograms in total ) and were included in the current analysis . The distribution of children and electrocardiograms included in the analysis is shown in Fig 1 . The number of children who participated at follow-up examinations and had an electrocardiogram was reduced over time , mainly because migration . Children included in the analysis who were assigned to the benznidazole ( n = 48 ) and placebo ( n = 47 ) groups of the clinical trial , separately , and those in the benznidazole cohort ( n = 16 ) were similar in age , body weight , gender and rural residence ( Table 1 , top panel ) . However , children in the benznidazole cohort had less electrocardiograms during follow-up as compared to those enrolled in the clinical trial . Median follow-up ( 25th-75th percentile ) was 8 . 6 ( 7 . 1–14 . 1 ) years . A total of 94 children had an electrocardiogram in 1991–1992 , including 8 ( 8 . 5% ) children with electrocardiographic abnormalities ( Table 2 ) . Most common electrocardiographic abnormalities included rR’ or R wave in V1 ( i . e . , right bundle branch block ) and left anterior fascicular block . Proportion of electrocardiograms with electrocardiographic abnormalities reminded relatively stable across assessment periods , ranging from 8 . 6% ( 95% CI: 4 . 3%-16 . 7% ) in 1991–1992 to 11 . 3% ( 95% CI: 6 . 5%-18 . 9% ) in 1998 ( Fig 2 , left panel ) . The prevalence of electrocardiograms with abnormalities was higher among children treated with benznidazole compared with those not treated in all assessment periods following the baseline evaluation ( Table 3 ) . Prevalence ratios for electrocardiographic abnormalities associated with treatment with benznidazole were not statistically significant in any post-baseline assessment . Results were similar in sensitivity analyses . Baseline characteristics of the 86 children without electrocardiographic abnormalities in 1991–1992 are shown in Table 1 , bottom panel . The proportion of electrocardiograms with electrocardiographic abnormalities increased over time in this population ( Fig 2 , right panel ) . A total of 16 ( 18 . 6% ) children developed incident electrocardiographic abnormalities during follow-up , including 8 participants who received treatment with benznidazole in 1991–1992 ( Table 4 ) . Among those with incident electrocardiographic abnormalities , 4 children ( 3 children treated with benznidazole ) developed rR’ or R in V1 . The crude hazard ratio for incident electrocardiographic abnormalities comparing children treated with benznidazole versus those not treated was 0 . 74 ( 95% CI: 0 . 28–1 . 97 , p-value: 0 . 54 ) . After adjustment for age at baseline , gender , rural residence and body weight , the hazard ratio for incident electrocardiographic abnormalities associated with treatment with benznidazole was 0 . 68 ( 95% CI: 0 . 25–1 . 88 , p-value: 0 . 46 ) . All of the 5 children treated with benznidazole in the clinical trial who had incident electrocardiographic abnormalities and completed a F29 ELISA and xenodiagnosis test in 2005 had negative results for T . cruzi infection .
We analyzed the characteristics and frequency of electrocardiographic abnormalities among children with chronic T . cruzi infection and the effect associated with treatment with benznidazole . In our analysis , children with chronic T . cruzi infection frequently presented or developed electrocardiographic abnormalities . Most of these electrocardiographic abnormalities , including right bundle branch block , and left anterior fascicular block , are more common among individuals with chronic T . cruzi infection [29] . After statistical adjustment , treatment with benznidazole for 60 days was not associated with less electrocardiographic abnormalities as compared with no treatment over a median follow-up of 8 . 6 years . We found no evidence of treatment failure among children with incident electrocardiographic abnormalities who completed treatment with benznidazole at baseline . These results should be interpreted in the context of the few number of participants analyzed , the number of electrocardiographic abnormalities and the long term evolution of chagasic cardiomyopathy . Treatment with benznidazole is currently recommended in acute , congenital and reactivated infection by T . cruzi , and among children with chronic infection [18 , 19 , 30 , 31] . The recommendation to treat children with chronic T . cruzi infection is based on 2 clinical trials conducted in the 1990s which found that benznidazole is effective to induce T . cruzi clearance in this population [14 , 15] . However , these studies have not shown that treatment with benznidazole can prevent heart conduction disturbances or chagasic cardiomyopathy . In 1991 , de Andrade et al . carried out a clinical trial including 130 children 7 to 12 years of age with chronic T . cruzi infection who were randomly assigned 1:1 to treatment with benznidazole 7 . 5 mg/Kg/day or placebo for 60 days [14] . Over 3 years of follow-up , 1 child in the treatment group and 4 children in the control group developed a complete right bundle branch block ( p-value: 0 . 36 ) . None of the children showed evidence of chagasic cardiomyopathy after 6 years of follow-up in the extension study [32] . Using data from the other clinical trial conducted in the 1990s , we observed no difference in the presence of a broader spectrum of electrocardiographic abnormalities between children with chronic T . cruzi infection who were and were not treated with benznidazole . Results from these studies are important considering the few data available about the natural history of electrocardiographic abnormalities and the effect of treatment with benznidazole on heart conduction disturbances among children with chronic T . cruzi infection . Taken together , results from these studies suggest that treatment with benznidazole in the current scheme of 60 days may not prevent electrocardiographic abnormalities in this population . Few studies have investigated the efficacy of benznidazole to prevent electrocardiographic abnormalities or Chagas’ heart disease progression among adults [16 , 33 , 34] . In the BENEFIT trial , treatment with benznidazole did not reduce the risk for clinical outcomes compared with placebo among 2 , 854 adults with chagasic’ cardiomyopathy . After 7 years of follow-up , the hazard ratio for death , cardiac arrest , insertion of a pacemaker or an implantable cardioverter–defibrillator , sustained ventricular tachycardia , cardiac transplantation , new heart failure , stroke , transient ischemic attack , or a thromboembolic event associated with benznidazole was 0 . 93 ( 95% CI: 0 . 81–1 . 07 ) . These results support some current guidelines which do not recommend treatment with benznidazole among adults more than 50 years old with chronic T . cruzi infection given their lower rate of seroconversion and a higher risk for side effects compared with children [18 , 19 , 35] . Results from TRAENA ( NCT02386358 ) , another large randomized clinical trial designed to investigate the efficacy of benznidazole to prevent major cardiovascular outcomes among adults with Chagas’ disease , are expected to be published by the end of 2016 [36] . In our analysis , we found no evidence of persistent T . cruzi infection among children with incident electrocardiographic abnormalities who received treatment with benznidazole . However , conventional tests for T . cruzi infection ( i . e . , serology tests , xenodiagnosis and polymerase chain reaction [PCR] ) have important limitations to determine a complete parasite elimination following treatment with benznidazole [37] . Specifically , serology tests may remain positive several years after treatment with benznidazole , and xenodiagnosis and PCR are negative in many individuals with chronic T . cruzi infection [19 , 38] . Prior studies have shown a trypanocidal effect of benznidazole among individuals with chronic T . cruzi infection using serology tests , xenodiagnosis and PCR [14–17 , 34] . However , some individuals may remain with persistent T . cruzi infection after treatment . In the BENEFIT trial , 53 . 3% of participants with a positive PCR test at baseline who received treatment with benznidazole had a positive PCR test after 5 years of follow-up [21] . Even a few number of T . cruzi specimens could be enough to maintain an autoimmune response with production of antibodies against nervous and cardiac muscle which could play an important role in the development and progression of heart conduction disturbances and chagasic cardiomyopathy [30 , 33 , 39] . This could have contributed to an apparent lack of efficacy of benznidazole to prevent electrocardiographic abnormalities or chagasic cardiomyopathy in prior studies . Future studies should focus on developing diagnostic methods with high sensitivity and specificity to detect persistent T . cruzi infection after treatment with trypanocidal drugs as well as to determine whether individuals with persistent T . cruzi infection would benefit from retreatment . Most participants included in the present analysis were initially enrolled in a clinical trial and all procedures for data collection followed the same study protocol . Also , treatment with benznidazole was performed in accordance with current recommendations [18 , 19 , 35] . Despite these strengths , results from the present analysis should be interpreted in the context of potential limitations . Following young populations in low resource settings is challenging and some study participants were lost during follow-up , mainly because migration . Only few covariates were available for statistical adjustment for potential confounders , which is related to the fact that risk factors for chagasic cardiomyopathy among individuals with chronic T . cruzi infection remain largely unknown . Several factors may have contributed to attenuate a possible association between treatment with benznidazole and lower risk for electrocardiographic abnormalities in our study . Some children who received treatment with benznidazole may have remained with persistent T . cruzi infection . We cannot exclude the possibility of reinfection among children successfully treated with benznidazole , although this was considered unlikely . Also , some children who were analyzed as untreated in the present study may have received treatment with benznidazole during follow-up , which was not documented . Some electrocardiographic abnormalities observed in this analysis , including bundle branch block , may be unrelated with T . cruzi infection as they may also be detected among uninfected children [29 , 40] . However , a prior study using the Buenos Aires method reported that electrocardiographic abnormalities , including bundle branch block and left anterior fascicular block , are more common among individuals with chronic T . cruzi infection compared with uninfected controls [29] . Because the small sample size , our analysis had low statistical power to exclude a clinically relevant effect to prevent electrocardiographic abnormalities associated with treatment with benznidazole . For example , in our main analysis , the lower bound of the 95% CI for the prevalence ratio in the second assessment period was 0 . 66 . This means that we cannot exclude a reduction on the prevalence of electrocardiographic abnormalities associated with benznidazole as large as 44% . Finally , because the study was conducted in a restricted geographic area , results may not be generalizable to children with chronic T . cruzi infection from other regions . Results from the present study should not be interpreted as indicative that children with chronic T . cruzi infection should not be treated with benznidazole . Treatment with benznidazole among children with chronic T . cruzi infection can contribute to induce T . cruzi clearance [14 , 15] , and reduce the number of incident cases by vertical transmission [41–43] , blood transfusion and organ transplant [3 , 31] . Treatment with benznidazole can also contribute to reduce the risk for a reactivation associated with immunodeficiency disorders or immunosuppression , and reaching seroconversion could be beneficial for the wellbeing of children and their relatives [31] . Instead , results from our study highlight the need for further research on prevention of cardiovascular manifestations of Chagas’ disease which should be recognized in the agenda of health research priorities in endemic countries [44] . Although many endemic countries have implemented public health actions aimed to increase the use of benznidazole among children with chronic T . cruzi infection , treated children may still contribute to high direct healthcare costs because their higher risk for cardiovascular manifestations . Further longitudinal studies are needed to investigate whether tripanocides with new schemes can prevent cardiovascular outcomes beyond electrocardiographic abnormalities , including heart failure and sudden death , among children with chronic T . cruzi infection . This is important because there are few data available about the clinical significance of electrocardiographic abnormalities among children with chronic T . cruzi infection as most studies on heart conduction disturbances and Chagas disease have been conducted among adults [11 , 13] . In conclusion , electrocardiographic abnormalities are common among children with chronic T . cruzi infection . There are several reasons for indicating trypanocidal therapy among children with chronic T . cruzi infection . However , results from the present study suggest that treatment with benznidazole for 60 days may not be associated with a lower occurrence of electrocardiographic abnormalities . | There are few data available on the natural history of electrocardiographic abnormalities among children with chronic Trypanosoma cruzi infection . Also , few studies analyzed the effect of benznidazole to prevent electrocardiographic abnormalities in this population . In the current study , electrocardiographic abnormalities were frequent among children with chronic T . cruzi infection . Results from the current study also suggest that treatment with benznidazole may not be associated with less electrocardiographic abnormalities . The current study highlights the need of further research to prevent cardiovascular manifestations associated with chronic T . cruzi infection . | [
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] | 2016 | Electrocardiographic Abnormalities and Treatment with Benznidazole among Children with Chronic Infection by Trypanosoma cruzi: A Retrospective Cohort Study |
Varicella zoster virus ( VZV ) is a lymphotropic alpha-herpesvirinae subfamily member that produces varicella on primary infection and causes zoster , vascular disease and vision loss upon reactivation from latency . VZV-infected peripheral blood mononuclear cells ( PBMCs ) disseminate virus to distal organs to produce clinical disease . To assess immune evasion strategies elicited by VZV that may contribute to dissemination of infection , human PBMCs and VZV-specific CD8+ T cells ( V-CD8+ ) were mock- or VZV-infected and analyzed for immunoinhibitory protein PD-1 , PD-L1 , PD-L2 , CTLA-4 , LAG-3 and TIM-3 expression using flow cytometry . All VZV-infected PBMCs ( monocytes , NK , NKT , B cells , CD4+ and CD8+ T cells ) and V-CD8+ showed significant elevations in PD-L1 expression compared to uninfected cells . VZV induced PD-L2 expression in B cells and V-CD8+ . Only VZV-infected CD8+ T cells , NKT cells and V-CD8+ upregulated PD-1 expression , the immunoinhibitory receptor for PD-L1/PD-L2 . VZV induced CTLA-4 expression only in V-CD8+ and no significant changes in LAG-3 or TIM-3 expression were observed in V-CD8+ or PBMC T cells . To test whether PD-L1 , PD-L2 or CTLA-4 regulates V-CD8+ effector function , autologous PBMCs were VZV-infected and co-cultured with V-CD8+ cells in the presence of blocking antibodies against PD-L1 , PD-L2 or CTLA-4; ELISAs revealed significant elevations in IFNγ only upon blocking of PD-L1 . Together , these results identified additional immune cells that are permissive to VZV infection ( monocytes , B cells and NKT cells ) ; along with a novel mechanism for inhibiting CD8+ T cell effector function through induction of PD-L1 expression .
Varicella zoster virus ( VZV ) is a lymphotropic , human alpha-herpesvirinae subfamily member that produces varicella ( chickenpox ) upon primary infection , after which virus establishes latency in ganglionic neurons along the entire neuraxis [1] . With aging or immunosuppression , such as seen in patients with HIV , cancer or immunomodulatory therapies , VZV reactivates to produce herpes zoster ( shingles ) , vascular disease and vision loss . The burden of disease produced by VZV is significant , since 90% of the world population harbors latent virus and at least 50% will experience reactivation by 85 years of age to develop zoster [2] . Zoster can be complicated by postherpetic neuralgia and is an established risk factor for stroke and myocardial infarction [3] . VZV infection of human peripheral blood mononuclear cells ( PBMCs ) is an essential step in virus dissemination and clinical disease . Following inhalation of viral particles during primary infection , infected PBMCs in the tonsils carry virus to skin to produce varicella rash [1]; virus can also spread to other organs to cause glomerulonephritis , abdominal pain and hepatitis [4 , 5] . During reactivation , VZV spreads transaxonally and is also detected in PBMCs , albeit at a low rate with 1/10 , 000–100 , 000 PBMCs that are infected [6]; however , in immunosuppressed patients with disseminated zoster ( cancer or HIV ) , rates of viremia may be higher [7] . The mechanism ( s ) that facilitates spread of VZV-infected PBMCs without effective immune clearance is unknown; however , upregulation of immunoinhibitory proteins may be important . Therefore , we hypothesized that VZV infection of PBMCs induces immunoinhibitory proteins to evade immune clearance . Such cell surface proteins normally act to halt an immune response after clearance of damaged or infected cells so that healthy cells are not harmed by inflammatory cytokines or activated immune cells [8–10] . For example , programmed cell death protein-1 ( PD-1 ) , a receptor expressed exclusively on immune cells and mainly T cells , is induced during T cell activation and chronic infections [9] . PD-1 elicits its immunoinhibitory function by binding with programmed death ligand-1 ( PD-L1 ) or PD-L2 , both of which can be expressed on virtually all cells , to inhibit positive signaling through the T cell receptor ( TCR ) and subsequent cytokine secretion [9 , 10] . Cytotoxic T lymphocyte-associated protein-4 ( CTLA-4 ) inhibits T cell function by binding to the T cell co-receptors CD80 and CD86 with a stronger affinity than that to the stimulatory co-receptor CD28 [11 , 12] . Lymphocyte activation gene-3 ( LAG-3 ) inhibits T cell activation since it binds with a higher affinity to MHC-II than CD4 [13] and also inhibits CD8+ T cell function during chronic viral infection [14] . Finally , T cell immunoglobulin and mucin-domain-containing-3 ( TIM-3 ) inhibits TCR signaling and IL-2 secretion through interaction with its ligand galectin-9 [15] . Cancer- and virus-mediated upregulation of these immunoinhibitory proteins to evade clearance is well-established . Cancer cells induce the expression of immunoinhibitory ligands , such as PD-L1 and PD-L2 , in the tumor microenvironment to prevent immune cell activation , enabling progression or metastasis . In that context , therapeutic targeting of immunoinhibitory proteins , mainly PD-1/PD-L1 and CTLA-4 , has revolutionized cancer therapy [8] . Herpes simplex virus-1 ( HSV-1 ) , another alpha-herpesvirinae subfamily member , induces PD-1 expression during infection , and blockade of PD-L1 in mice enhanced primary and secondary CD8+ T cell immune responses [16] . PD-L1 expression was induced in HSV-1-infected neurons in mice and limited the survival of CD8+ T cells [17] . In addition , recombinant HSV-1 overexpressing CD80 permitted dendritic cell viral replication through binding of PD-L1 that resulted in enhanced T cell activation in mice [18] . While Epstein-Barr virus ( EBV ) , a gammaherpesvirinae subfamily member , has a tropism for B cells and can transform them into Hodgkin’s lymphoma or Burkitt’s lymphoma cells , the combined blockade of PD-1 and CTLA-4 in humanized mouse models of EBV prevented lymphomagenesis [19] . Finally , HIV infection is associated with expression of several immunoinhibitory proteins on HIV-specific CD4+ and CD8+ T cells , such as PD-1 , CTLA-4 , TIM-3 and LAG-3 [20–23] . While earlier studies showed that VZV infection of human tonsillar T cells induces PD-1 expression [24] and that zoster patients have elevated PD-1 expression in T cells during reactivation [25] , gaps remain in our knowledge of VZV dissemination via infected PBMCs . Thus , the permissiveness of PBMC subsets for VZV infection , the ability of virus to differentially modulate expression of immunoinhibitory proteins in a cell type-specific manner , the possible effects of viremia on uninfected bystander PBMCs and the clinical implications are still unclear . Understanding how VZV modulates immunoinhibitory proteins during viremia may have therapeutic value , which restores the ability of immune cells to clear virus infection and prevent hematogenous spread to other organs . Here , we analyzed both the ability of VZV to infect multiple immune cell subsets and the alterations in expression of immunoinhibitory proteins ( PD-1/PD-L1/ PD-L2/CTLA-4/ LAG-3/TIM-3 ) in virus- and uninfected human PBMCs .
To determine the permissiveness of immune cells to VZV infection , human PBMCs were infected with cell-associated VZV ( Ellen strain ) or vaccine strain ( vOka ) and analyzed 48 h later for expression of VZV surface glycoprotein E ( gE ) using flow cytometry ( Fig 1A ) . The cell associated requirement for viral transmission of VZV is well known and this is an established method for infecting human immune cells with VZV [26 , 27] . Flow cytometry gating scheme for individual immune cells is provided ( S1 Fig ) . Results from PBMCs from 12 different healthy donors infected with VZV Ellen showed that monocytes were the most permissive to VZV infection ( mean: 70% , range: 35–97% ) followed by NK cells ( mean: 32% , range: 12–61% ) , NKT cells ( mean: 19% , range: 12–32% ) , B cells ( mean: 16% , range: 7–29% ) , CD4+ T cells ( mean: 14% , range: 5–29% ) and CD8+ T cells were the least permissive to infection ( mean: 10% , range: 4–17% ) ( Fig 1B and S1 Table ) . Monocytes showed a significantly higher infection rate when compared to all other immune cells analyzed ( Fig 1B ) . Next , NK cells showed significantly higher levels of infection compared to all other immune cells analyzed with the exception of monocytes; NKT cells showed significantly higher levels of infection compared to both CD4+ and CD8+ T cells; B cells and CD4+ T cells showed significantly higher levels of infection compared to CD8+ T cells ( Fig 1B ) . Results from PBMCs from 5 different healthy donors infected with vOka showed similar trends in permissiveness to VZV infection as the Ellen strain with monocytes having significantly higher infection rates when compared to all other immune cells analyzed , NK cells having significantly higher infection rates than all immune cells analyzed aside from monocytes , and NKT cells and B cells having significantly higher infection rates than CD8+ T cells ( Fig 1C and S2 Table ) . To confirm cell surface staining of VZV gE , we infected human PBMCs using cell-associated GFP-expressing strain of VZV ( VZV-GFP ) . Aside from B cells being slightly more permissive to VZV-GFP infection than NKT , the preferential infection rates of VZV-GFP were similar to surface staining of VZV gE shown using both Ellen and vOka strains ( S2 Fig and S3 Table ) , further supporting our observations . To assess changes in VZV-infected PBMCs over time we co-cultured human PBMCs from 4 healthy individuals with uninfected- or VZV-infected HFLs ( Ellen strain ) and harvested PBMCs at 24 , 48 and 72 h post infection ( hpi ) and analyzed for surface VZV-gE expression . PBMCs were co-cultured on separate 10cm2 petri dishes for each time point with VZV-infected HFLs that were infected with identical titers to allow the entire PBMC populations to be harvested and analyzed . Monocytes were 87% , 88% and 71% VZV-gE+ at 24 , 48 and 72 hpi with a significant decrease in surface VZV-gE expression from 48 and 72 hpi ( P = 0 . 006 ) ( S3 Fig and S4 Table ) . B cells were 30% , 14% and 8% VZV-gE+ at 24 , 48 and 72 hpi with significant decreases in surface VZV-gE expression at 24 hpi compared to both 48 and 72 hpi ( P = 0 . 04 and 0 . 008 , respectively ) ( S3 Fig and S4 Table ) . Interestingly , the remaining PBMC subsets showed slight increases in surface VZV-gE expression from 24 hpi to 48 hpi which was maintained at 72 hpi as well ( S3 Fig and S4 Table ) ; yet no statistically significant changes were observed . NK cells were 19% , 23% and 22% VZV-gE+ at 24 , 48 and 72 hpi; NKT cells were 11% , 17% and 17% VZV-gE+ at 24 , 48 and 72 hpi; CD4+ T cells were 9% , 17% and 17% VZV-gE+ at 24 , 48 and 72 hpi; and CD8+ T cells were 6% , 10% and 11% VZV-gE+ at 24 , 48 and 72 hpi . To assess for viral expression levels of VZV in PBMC subsets we gated individual immune cells based upon VZV-gE expression levels . VZV-gE+lo cells were defined as having VZV-gE expression levels of log0-1 and VZV-gE+hi cells >log1 at 48 hpi . Monocytes had the highest % of VZV-gE+hi cells ( 44 . 5% ) which was significantly higher than all other PBMC subsets analyzed aside from B cells ( S4 Fig ) . B cells had 29 . 7% VZV-gE+hi cells which was significantly higher than NKT cells , CD8+ T cells and CD4+ T cells ( S4 Fig ) . NK cells had 21 . 3% VZV-gE+hi cells , NKT cells had 16 . 3% VZV-gE+hi cells , CD8+ T cells had 10 . 8% VZV-gE+hi cells and CD4+ T cells had 8 . 3% VZV-gE+hi cells ( S4 Fig ) . Taken together , these results indicate that both the VZV Ellen and vaccine strain can infect all immune cell populations in the PBMC pool with preferential infection of monocytes , followed by NK cells , NKT cells and B cells; with CD4+ and CD8+ T cells being the least permissive to infection . To confirm cell surface flow cytometry VZV-gE expression in human PBMCs , PBMC subsets from 2 healthy donors were sorted using flow cytometry and stained for nuclear VZV ORF63 expression using immunofluorescence . As a positive control for ORF63 expression VZV-infected HFLs were analyzed as well . All VZV-infected monocytes , NK cells , NKT cells , B cells , CD4+ T cells , CD8+ T cells and HFLs showed nuclear VZV ORF63 expression indicative of productive infection ( Fig 2A ) that was not observed with isotype control stains ( Fig 2B ) , while uninfected PBMCs and HFLs showed no ORF63 expression as expected ( Fig 2C ) . Taken together , these results confirm that all VZV-infected PBMC subsets express nuclear VZV ORF63 . The productive replication cycle of all herpesviruses occurs through an orderly chronological cascade of gene expression composed of immediate early , early and late genes [28] . To confirm that the flow cytometry findings showing VZV gE expression on infected PBMCs represented productive virus infection , viral transcripts were examined in each of these VZV-infected cell populations . Specifically , PBMCs were infected with VZV for 48 h , immune cells were sorted and determined to be >93% pure based upon flow cytometry analyses . RNA was extracted and q-RT-PCR analyses for immediate early ( ORF63 ) and late ( ORF68 ) viral transcripts along with the housekeeping gene GAPdH from uninfected and VZV-infected PBMCs were performed ( n = 3 healthy donors ) . A threshold of 36 for Ct values for all transcripts was set and data analyzed using the 1/Ct method ( threshold = 0 . 028 ) ( Fig 3 ) . All VZV-infected immune cell populations analyzed showed expression of both immediate early and late viral transcripts along with GAPdH ( Fig 3 ) . As a control for productive viral transcript expression , VZV-infected HFLs that were >90% VZV gE+ based upon flow cytometry analyses were harvested and subjected to the same q-RT-PCR analyses as PBMCs . VZV-infected HFLs had similar expression levels of ORF63 and ORF68 transcripts when compared to all PBMC subsets ( Fig 3 ) , further confirming that PBMCs are productively infected by VZV . In addition , VZV-infected immune cell populations and HFLs were analyzed for q-RT-PCR analyses without reverse transcriptase following DNase treatment and Ct values were undetermined for both ORF63 and GAPdH ( S5 Table ) , indicating no contamination from viral DNA . Uninfected immune cells were also sorted and analyzed for viral transcripts and GAPdH , no expression of viral transcripts was observed ( S5 Table ) . Taken together , these results support that VZV can productively infect monocytes , NK cells , NKT cells , B cells , CD4+ T cells and CD8+ T cells . Since VZV infection causes a viremia upon primary infection and VZV-infected immune cells are how virus is disseminated to skin and other organs [1] , we assessed if all VZV-infected immune cell subsets are capable of transmitting virus to another cell type . VZV-infected monocytes , NK cells , NKT cells , B cells , CD4+ T cells and CD8+ T cells from 2 different healthy donors were sorted using flow cytometry then washed with citrate buffer to remove any potential virus adhering to the cell surface that would not be transferred by a productively-infected immune cell as this is a commonly used method for ensuring productive infection by alphaherpes viruses [29] . Infected cells were then washed with FACS buffer and co-cultured with HFLs for 3 days . After 5 days , adherent HFLs were fixed and analyzed for ORF63 and VZV gB expression using immunofluorescence . All VZV-infected monocytes , NK cells , NKT cells , B cells , CD4+ T cells and CD8+ T cells were capable of transmitting virus to HFLs as demonstrated by the expression of both VZV ORF63 and VZV gB ( Fig 4 ) . Additionally , VZV infected monocytes , NK cells , NKT cells , B cells , CD4+ T cells and CD8+ T cells from 2 different healthy donors were sorted and co-cultured with HFLs without washing with citrate buffer and analyzed for VZV gE expression using flow cytometry after 5 days . All immune cells were capable of transmitting virus to HFLs as well ( S5 Fig ) . In summary , VZV infected monocytes , NK cells , NKT cells , B cells , CD4+ T cells and CD8+ T cells were all capable of transmitting virus to another cell type which supports the notion that during viremia , any of these cells are capable of carrying virus to the skin and distal organs . The involvement of the PD-1:PD-L1 pathway in immune evasion during viral infection and carcinogenesis is well-established [9 , 10] . PBMCs were co-cultured with VZV-infected HFLs and utilizing flow cytometry gating on VZV gE expression , the mean fluorescent intensity ( MFI ) levels of PD-L1 , PD-L2 and PD-1 in uninfected immune cells ( UI ) , VZV gE+ immune cells ( V+ ) and VZV gE-negative bystander cells ( Bys ) was determined ( Fig 5A ) . Immune cells were gated for immunoinhibitory protein expression using FMO controls ( Figs 5B and 6A ) . All V+ immune cells had significant elevations in PD-L1 MFI levels when compared to their UI counterparts ( Figs 5C and 6B ) . Aside from CD4+ T cells , all V+ immune cell populations analyzed had significant elevations in PD-L1 MFI levels compared to their Bys counterparts ( Figs 5C and 6B ) . Only Bys monocytes and CD4+ T cells had significant elevations in PD-L1 MFI levels compared to UI counterparts ( Figs 5C and 6B ) . PD-L2 MFI levels were significantly elevated in V+ B cells compared to UI cells ( Fig 5D ) . Only V+ NKT cells and CD8+ T cells had statistically significant elevations in PD-1 MFI levels compared to both their UI and Bys counterparts ( Figs 5E and 6B ) . To test for additional immunoinhibitory proteins that can be induced in CD4+ and CD8+ T cells , we examined CTLA-4 , LAG-3 and TIM-3 expression since these pathways , like that of PD-1 , can also suppress T cell activation [11 , 14 , 15] . No significant changes in CTLA-4 , LAG-3 or TIM-3 expression levels were detected in either CD4+ or CD8+ T cells ( Fig 6B ) . Statistical analyses of all immunoinhibitory proteins analyzed is provided ( S4 and S6 Tables ) . As a control for immunoinhibitory protein staining , PBMCs were cultured alone and treated with or without PMA/Ionomycin and significant elevations of all immunoinhibitory proteins was observed in PMA/Ionomycin treated CD8+ T cells ( S6 Fig ) . In summary , all VZV-infected immune cells had significant elevations in PD-L1 expression when compared to their uninfected counterparts , while only VZV-infected NKT cells and CD8+ T cells had significant inductions in PD-1 expression when compared to both UI and Bys cells . PD-L2 was only significantly elevated in VZV-infected B cells compared to UI cells; indicating that the main immunoinhibitory pathway induced during VZV infection of PBMCs is the PD-1:PD-L1 pathway . VZV-specific CD8+ T cells that recognize discrete HLA A*0201-restricted nonamer epitopes in either VZV ORF34 or ORF18 proteins have been enriched and characterized [30] . These cells are HLA compatible with both HFLs and HBVAFs used in our experiments as confirmed by staining with an HLA-A*0201-reactive monoclonal antibody . Uninfected- or VZV-infected HBVAFs were cultured for 72 h after infection; cells were then co-cultured without or with VZV ORF34- or ORF18-specific CD8+ T cells for 48 h and analyzed . Phase microscopy showed that in the absence of T cells , uninfected HBVAFs formed a confluent monolayer ( Fig 7A , top left panel ) , whereas VZV-infected HBVAFs formed clusters ( syncytia ) of infected cells ( Fig 7A , bottom left panel ) . In the presence of VZV-specific CD8+ T cells directed against ORF34 or ORF18 , uninfected HBVAFs maintained a confluent monolayer ( Fig 7A , top right panel ) , whereas VZV-infected HBVAFs had significant cell lysis and disruption of the clustered cells ( Fig 7A , bottom right panel ) . Concurrently , 24 h after exposure of uninfected- and VZV-infected HFLs/HBVAFs to VZV-specific CD8+ T cells , conditioned supernatant was collected and analyzed for IFNγ levels using ELISA . Both VZV ORF34- and ORF-18-specific CD8+ T cells had dramatic elevations in IFNγ levels when co-cultured with VZV-infected cells when compared to uninfected cells ( Fig 7B , P<0 . 0001 for both ) , which further supports their ability to mount a cellular-mediated immune response towards VZV infection . To confirm that IFNγ secretions elicited by VZV ORF34- and ORF-18-specific CD8+ T cells were due to proper MHC-I recognition of VZV antigen we co-cultured uninfected- and VZV-infected HBVAFs with HLA-A*0201-restricted HSV-2 UL47 specific CD8+ T cells or HLA-B*0702-restricted HSV-2 UL49 specific CD8+ T cells during the same experiments . Virtually no IFNγ secretions were elicited by either CD8+ T cells specific for HSV-2 during co-culture with either uninfected- or VZV-infected HFLs ( S7 Fig ) . Additionally , we confirmed our previous reports on VZV-mediated down-regulation of MHC-I in HBVAFs [31] and show that VZV-infected HBVAFs maintain significant expression levels of MHC-I when compared to isotype control stains ( S8 Fig ) . Overall , our data indicate that VZV-infected HBVAFs are still capable of presenting antigen to VZV-specific CD8+ T cells . VZV-infected HBVAFs and uninfected HBVAFs had no autonomous IFNγ secretions when cultured alone which confirms the dramatic induction of IFNγ elicited by VZV-specific CD8+ T cells during co-culturing with VZV-infected HBVAFs ( S7 Fig ) . While the VZV ORF34- and ORF18-specific CD8+ T cells elicited a robust anti-viral immune response towards VZV-infected HBVAFs they were also permissive to VZV infection based upon flow cytometry analyses of VZV gE expression ( Fig 7C ) . On average 16% of VZV-ORF34- and 14% of ORF18-specific CD8+ T cells expressed VZV gE after 48 h of co-culturing ( Fig 7D ) . Taken together , the VZV ORF34- and ORF18-specific CD8+ T cells induced robust levels of IFNγ secretions and recognition of VZV-infected HBVAFs/HFLs; importantly , these T cells were also prone to VZV infection based upon surface VZV gE expression . To assess for immunoinhibitory proteins induced in VZV ORF34- or ORF18-specific CD8+ T cells during clearance of VZV-infected HBVAFs/HFLs , we harvested cells as mentioned above and analyzed for PD-1 , PD-L1 , PD-L2 , CTLA-4 , LAG-3 and TIM-3 expression levels using flow cytometry . The same gating scheme of UI , Bys and V+ cells was used for analyses ( Fig 8A ) . Cells were gated using an FMO control for all immunoinhibitory proteins analyzed and MFI levels were compared amongst the 3 populations ( Fig 8B ) . All V+ cells in both VZV ORF34- and ORF18-specific CD8+ T cells had statistically significant elevations in PD-1 , PD-L1 , PD-L2 and CTLA-4 MFI levels compared to UI cells and Bys cells ( Fig 8C ) . Additionally , all Bys cells in in both VZV ORF34- and ORF18-specific CD8+ T cells had statistically significant elevations in PD-1 and CTLA-4 MFI levels compared to UI cells ( Fig 8C ) . No statistically significant elevations in LAG-3 or TIM-3 MFI levels were observed in either VZV ORF34- or ORF18-specific CD8+ T cells when compared amongst UI , Bys or V+ cells ( Fig 8C ) . Statistical analyses of all immunoinhibitory proteins analyzed is provided ( S7 Table ) . In addition , both VZV ORF34- and ORF18-specific CD8+ T cells had significantly higher percentages of VZV-gE+hi cells when compared to VZV-infected CD8+ T cells from healthy donor PBMCs ( S4 Fig ) , which could explain the VZV-mediated induction of CTLA-4 and PD-L2 observed in these cells that was not observed in CD8+ T cells from healthy donor PBMCs . In summary , both VZV-specific CD8+ T cell clones had significant inductions of PD-1 , PD-L1 , PD-L2 and CTLA-4 expression in VZV-infected cells when compared to uninfected cells; while a bystander effect for PD-1 and CTLA-4 induction was also observed in both clones . Since primary infection with VZV induces viremia , we infected cryopreserved/thawed PBMCs with VZV and co-cultured them with VZV ORF34- or ORF18-specific CD8+ T cells to mimic leukocyte-leukocyte interactions during the viremic phase of primary VZV infection . The ORF34- and ORF18-specific CD8+ effector T cells and VZV-infected PBMCs were all from the same donor . PBMCs were co-cultured with uninfected- or VZV-infected HFLs for 48 h , and non-adherent cells were harvested and analyzed for VZV infection of CD45+ cells using flow cytometry before co-culturing with VZV-specific CD8+ T cells . Both uninfected- and VZV-infected non-adherent cells were 99% CD45+ ( Fig 9A ) , and VZV-infected PBMCs were approximately 45% VZV-gE+ ( Fig 9B ) based on flow cytometry analyses . VZV-infected autologous PBMCs were cultured with VZV ORF34- or ORF18-specific CD8+ T cells at a 1:1 ratio in the presence of anti-PD-L1 ( αPD-L1 ) , anti-PD-L2 ( αPD-L2 ) or anti-CTLA-4 ( αCTLA-4 ) blocking antibodies or isotype controls . Since no induction of LAG-3 or TIM-3 expression was observed these immunoinhibitory proteins were not blocked . After 24 h of co-culturing autologous PBMCs with VZV ORF34- or ORF18-specific CD8+ T cells , cell culture supernatants were harvested and analyzed for IFNγ levels using ELISA ( Fig 9C ) . All VZV-infected PBMCs co-cultured with VZV ORF34- or ORF18-specific CD8+ T cells had significant elevations in IFNγ levels as compared to their uninfected counterparts ( P<0 . 0001 ) . Importantly , only blocking of PD-L1 induced significant elevations in IFNγ levels when compared to isotype controls ( P<0 . 0001 for both ) . Virtually no changes in IFNγ levels were observed when PD-L2 or CTLA-4 was blocked compared to isotype controls for either VZV ORF34- or ORF18-specific CD8+ T cells co-cultured with VZV-infected PBMCs . Also , cell culture supernatants from autologous PBMCs , from the same donor from whom the VZV-specific CD8+ T cells were derived , co-cultured with uninfected- and VZV-infected HFLs were analyzed for IFNγ levels and virtually no IFNγ secretions were detected during co-culturing with uninfected- or VZV-infected HFLs ( S7 Fig ) indicating that only the VZV ORF34- and ORF18-specific CD8+ T cells were responsible for IFNγ inductions observed . In addition , VZV ORF34- or ORF18-specific CD8+ T cells were co-cultured with HBVAFs in the presence of anti-PD-L1 blocking antibody ( αPD-L1 ) or isotype controls for 24 h and cell culture supernatants were harvested and analyzed for IFNγ levels using ELISA . Neither VZV ORF34- nor ORF18-specific CD8+ T cells showed a change in IFNγ levels between isotype and αPD-L1 treatments when co-cultured with uninfected HBVAFs , whereas PD-L1 blockade in both ORF34- and ORF18-specific CD8+ T cells showed significant elevations in IFNγ levels as compared to isotype controls during co-culture with VZV-infected HBVAFs ( P<0 . 001 and P<0 . 01 , respectively ) ( S9 Fig ) . In summary , blocking only PD-L1 enhanced CD8+ effector T cell functioning in response to VZV .
Herein , we examined the ability of VZV to infect human PBMCs and modulate expression of multiple immunoinhibitory proteins in a cell-type specific manner . Strikingly , VZV productively infected all PBMC subsets and we report here for the first time the productive infection of monocytes , B cells and NKT cells . While VZV has been widely regarded as a T cell tropic virus [1] , a recent study showed that NK cells are productively infected by VZV and the most permissive to VZV infection when compared to T cells , NKT cells and CD3-CD56- lymphocytes [32] . While the infection rates amongst the lymphocyte populations reported here were similar to that of Campbell et al . , their study did not investigate the permissiveness of VZV infection of monocytes or B cells and did not confirm productive infection of NKT cells or CD3-CD56- lymphocytes . We show here that all PBMC subsets are productively infected with VZV . This finding is consistent with the only other study investigating the permissiveness of VZV-infection of PBMCs during varicella and zoster in human patients , which revealed that T cells , monocytes and B cells express VZV gE [6] . Our results shed new light into the lymphotropism of VZV that leads to a better understanding of viral transmission during primary infection and reactivation . During primary VZV infection , viral particles are inhaled and the first site of replication is tonsils where it is presumed that tonsillar T cells become infected and subsequently traffic virus to skin promoting the vesicular rash associated with varicella/chickenpox [1] . However , our studies suggest that additional immune cell types in peripheral blood are capable of being infected with VZV . Thus , the proximity of immune cells relative to the initial inhaled virus may be the determining factor for which immune cells are responsible for trafficking virus to skin and distal organs . In support of T cells being the “viral traffickers” of VZV to skin and distal organs , we report here that all T-lineage cells and NK cells have slight increases in surface VZV-gE expression at 48 and 72 hpi when compared to 24 hpi , while monocytes and B cells showed decreased surface VZV-gE expression over time . Therefore , T-lineage cells and NK cells appear to be more capable of withstanding viral infection for longer amounts of time that would enable them to traffic virus throughout the body . T-lineage cells are the most abundant immune cell in PBMCs ( approximately 60–70% ) while NK cells represent a much smaller fraction ( <5% ) which might explain why only T-lineage cells were initially recognized as carriers of virus during primary infection . The preferential targeting of VZV infection towards innate immune cells ( monocytes and NK cells ) shown here would have several detrimental implications on the host immune response . First , an adaptive T cell or B cell immune response directed against VZV during primary infection takes approximately 2 weeks [33] . Therefore , VZV preferentially infects NK cells as these cells are capable of immediately detecting virus-infected cells as they use germline-encoded receptors to mount an immune response [34] . Indeed , fatal varicella has been identified in patients with NK cell deficiency [35 , 36] . NKT cells are considered both an innate and adaptive immune cell and disseminated VZV infection due to VZV vaccine strain was reported in a child with a rare deficiency in NKT cells [37] , indicating NKT cells contribute to host defense against VZV as well . Second , monocytes can differentiate into macrophages or dendritic cells ( DCs ) , both of which are the main antigen presenting cells in the body required for CD4+ T cell activation . VZV infection of monocytes would presumably prevent monocyte maturation and subsequent CD4+ T cell activation that is absolutely required for controlling VZV infection along with simian varicella virus ( SVV ) [1 , 38] . Interestingly , during primary infection of SVV in African green macaques , SVV was predominantly detected in both DCs and macrophages in the lung [39] , while an additional study showed similar results in lymph nodes during SVV reactivation in rhesus macaques [40] , all of which further support our findings . A caveat to the primary infection model of SVV in African green macaques was that the SVV-GFP virus used in these studies was severely attenuated compared to wild-type virus with regards to viral DNA found in PBMCs ( approximate 1000-fold decrease ) [39] . We also show here that PBMCs infected with VZV-GFP have lower levels of infection across all PBMC subsets when compared to wild-type VZV . Another striking finding was the induction of PD-L1 expression by VZV in all subsets of human PBMCs examined , along with the enhancement of T cell effector function after blocking PD-L1 in VZV-specific CD8+ T cells . The significant induction in IFNγ secretions during PD-L1 blockade in both VZV-specific CD8+ T cell lines shown here are similar to results in lymphocytic choriomeningitis virus ( LCMV ) -infected mice , where only anti-PD-L1 blockade and not anti-CTLA-4 rescued CD8+ T cell effector function [41] . We used flow cytometry gating based upon VZV gE expression to distinguish between VZV-infected and uninfected bystander cells . Bystander cells are presumably the CD8+ T cells responsible for killing VZV-infected cells as the infected VZV-specific CD8+ T cells probably do not elicit the same anti-viral immune response as their uninfected counterparts . Further supporting this notion , a bystander effect for PD-1 and CTLA-4 induction was only observed in VZV-specific CD8+ T cells and not in CD8+ T cells from healthy donor PBMCs which would contain <0 . 01% of VZV-specific CD8+ T cells as previously reported [33] . Therefore , utilizing flow cytometry gating we can explain why blocking PD-L1 and not CTLA-4 enhanced VZV-specific CD8+ T cell effector function . For example , both VZV-specific CD8+ T cell lines had modest 30–50% inductions in CTLA-4 and PD-1 expression levels in bystander cells compared to uninfected cells . However , VZV-infected PBMCs had a 2- to 14-fold induction in PD-L1 expression levels compared to uninfected PBMCs , which can explain the enhanced IFNγ levels observed when blocking PD-L1 and not CTLA-4 . Induction of PD-L2 expression by VZV was minimal in PBMCs compared to PD-L1 levels , which can explain the lack of enhanced IFNγ levels observed when blocking PD-L2 . The induction of the PD-1:PD-L1 pathway during viral infection has been well documented and PD-1 expression has been shown to be increased in CD8+ T cells from zoster patients when compared to healthy controls [25] . We report here for the first time the VZV-mediated induction of PD-L1 expression in all VZV-infected PBMC subsets and VZV-specific CD8+ T cells that could clearly aid in immune suppression during zoster . VZV-infected PBMCs are present during both varicella and zoster but at a very low rate ( 1/10 , 000–100 , 000 cells ) [6] which would provide minimal immune suppression . However , we found a bystander effect for induction of PD-L1 expression in both monocytes and CD4+ T cells , which may potentially amplify immune suppression during varicella or zoster especially considering that monocytes and CD4+ T cells represent the vast majority of immune cells in the PBMC pool ( approximately 70–80% ) . Aside from zoster , VZV reactivation can also produce VZV vasculopathy presenting as stroke , giant cell arteritis and granulomatosis aortitis [42] . Intriguingly , macrophages from patients with coronary artery disease have elevated PD-L1 expression and blocking PD-L1 in response to VZV enhanced VZV-specific CD4+ T cell responses [43] . Results from this study further support the role of VZV in promoting vascular disease and indicate a role of the PD-1:PD-L1 pathway during disease progression . Overall , our comprehensive examination of VZV infection in human PBMCs shows that all immune cell populations are permissive for VZV infection . The ability of these immune cells to transmit virus combined with the induction of PD-L1 expression in all PBMCs provides novel immune evasion strategies elicited by VZV infection . Induction of PD-L1 in PBMCs combined with the induction of PD-1 expression on CD8+ T cells and NKT cells could greatly diminish the effectiveness of the immune system in clearing virus . The enhanced CD8+ T cell effector function after PD-L1 blockade during VZV infection shows that VZV-mediated immune suppression can be reversed to attenuate virus dissemination and multisystem disease associated with VZV .
Human fetal lung fibroblasts ( HFLs ) ( ATCC , Manassas , VA ) and human brain vascular adventitial fibroblasts ( HBVAFs ) ( Sciencell , Carlsbad , CA ) were cultured in basal fibroblast medium supplemented with 2% fetal bovine serum ( FBS ) , 1% fibroblast growth serum and 1% 100X penicillin-streptomycin ( PS ) ( Sciencell ) . Cells were grown to approximately 80% confluency and then infected with cell-associated viruses ( 40 pfu/ml ) for 48–72 h . The VZV Ellen strain and vOka strains were used along with VZV-GFP that has been previously described [44] . At the height of infection culture medium was changed to basal fibroblast medium containing 2% FBS and 1% PS 4–6 h before immune cell addition . PBMCs isolated from whole blood using density gradient centrifugation on Ficoll ( GE Healthcare Bio-Sciences , Pittsburgh , PA ) were cultured in RPMI supplemented with 5% human serum ( Gemini Bio-Products , West Sacramento , CA ) and 1% PS ( Sciencell ) at a density of 2 . 0 x 10^6 cells/ml , after which 1 . 0 x 10^7 PBMCs were co-cultured for 48 h with uninfected- or VZV-infected HFLs grown in 10-cm2 cell culture dishes . There are 8 . 0 x 10^6 HFLs/HBVAFs on a confluent monolayer in 10-cm2 cell culture dishes , so approximately 1 . 25 PBMCs:1 HFL were co-cultured together . To confirm immunoinhibitory protein staining in flow cytometry , PBMCs were cultured alone with- or without treatment with PMA/Ionomycin ( Biolegend , San Diego , CA ) for 48 h before harvesting . Polyclonal VZV-specific CD8+ T cell lines that recognize specific epitopes in either VZV ORF34 or ORF18 proteins in the context of HLA A*0201 [30] were tetramer-sorted to >96% purity from PBMC of VZV-infected HLA A*0201-bearing donors and expanded with non-specific mitogens , cryopreserved , thawed before use , and cultured as described above in 12-well plates . Both VZV-specific CD8+ T cell lines were obtained from the same donor , such that autologous PBMCs were used as antigen presenting cells in some experiments . Polyclonal HSV-2-specific CD8+ T cell lines that recognize specific epitopes in either HSV-2 UL47 or UL49 proteins in the context of HLA-A*0201 ( UL47 ) [45] and HLA-B*0702 ( UL49 ) [45] were tetramer-sorted to >96% purity from PBMC of HSV-2-infected HLA A*0201- or HLA-B*0702-bearing donors and expanded with non-specific mitogens , cryopreserved , thawed before use , and cultured as described above in 12-well plates . Frozen PBMCs from six healthy donors of age 29–50 years were obtained commercially from Astarte Biologics ( Bothell , WA ) . Whole blood from twelve healthy donors of age 22–40 years were obtained commercially from Bonfils ( Denver , CO ) . Informed consent was obtained by the source companies identified above from all adult subjects providing PBMCs and whole blood for this research project; samples were de-identified by the company prior to our receipt . For flow cytometry and FACS sorting experiments , fluorochrome-conjugated antibodies against the following antigens were used: CD45 ( clone HI30; conjugated to BV421 ) , CD3 ( OKT3; BV605 & AF700 ) , CD56 ( HCD56; PE/Cy7 ) , CD8 ( SK1; BV510 & APC/Cy7 ) , CD4 ( SK3; FITC ) , CD19 ( HIB19 , PerCP/Cy5 . 5 ) , CD14 ( M5E2; APC ) , HLA-DR ( LN3; BV711 ) , PD-L1 ( 29E . 2A3; BV605 ) , LAG-3 ( 11C3C65; AF647 ) , TIM-3 ( F38-2E2; FITC & BV785 ) , HLA-ABC ( W6/32; PE/Cy7 ) , Isotype ( eBMG2b; PE ) ( MOPC-173; PE/Cy7 ) ( all Biolegend ) ; CD4 ( SK3; UV395 ) and PD-L2 ( MIH18; BV711 & BV785 ) ( all BD Biosciences ) ; CTLA-4 ( 14D3; PE/Cy7 ) , PD-L1 ( MIH1; APC ) , PD-1 ( MIH4; FITC ) ( all ThermoFIsher , Waltham , MA ) ; VZV gE ( MilliporeSigma , Burlington , MA ) conjugated in house to R-PE as previously described [31] . For immunofluorescence analyses experiments , unconjugated antibodies against the following antigens were used: VZV gB ( Mouse: Abcam , Cambridge , MA ) and VZV ORF63 ( Rabbit ) that was previously described [46] . Secondary antibodies consisted of Alexa Fluor 488 donkey anti-rabbit IgG and Alexa Fluor 594 donkey anti-mouse IgG ( MilliporeSigma ) . Tetramers of HLA A*0201 and VZV ORF34 and ORF18 proteins were obtained from the Fred Hutchinson Cancer Research Center Immune Monitoring Core . PBMCs or VZV-specific CD8+ T cells were harvested , washed with cold PBS and live/dead aqua-stained on ice as per the manufacturer’s protocol ( ThermoFisher ) . Cells were then resuspended in FACS buffer ( phosphate-buffered saline containing 1% FBS and 10 mm EDTA ) with addition of antibodies on ice for at least 30 min . Then , cells were fixed in 1% paraformaldehyde ( ThermoFisher ) or fixed and permeabilized to stain for intracellular CTLA-4 , using fixation/permeabilization kit ( ThermoFisher ) . For FACS staining of PBMCs , after live/dead staining and washing , cells were cultured with human TruStain FcX ( Biolegend ) and True-Stain Monocyte Blocker ( Biolegend ) for 5 min on ice per manufacturer’s instructions before the addition of fluorescence-conjugated antibodies . Fluorescence-minus-one ( FMO ) controls were used for all immunoinhibitory proteins as were isotype controls for VZV gE and CTLA-4 staining . For flow cytometry staining of HBVAFs , cells were harvested with a citrate buffer as previously described [31] and then stained as described above . Cells were analyzed using an LSR-II flow cytometer ( BD Immunocytometry Systems , San Jose , CA ) ; >500 , 000 events were collected for all samples except for HBVAFs staining where 20 , 000 events were collected . Electronic compensation was performed with antibody capture beads ( BD Biosciences , San Jose , CA ) and subsequent data were analyzed using Diva software ( BD Biosciences ) and FlowJo software ( Tree Star , Ashland , OR ) . Human PBMCs were harvested on ice , washed with FACS buffer and then resuspended in FACS buffer with the addition of antibodies for 30 min on ice . No viability stain was conducted on the sorted cells , however , PBMCs were stained for live/dead aqua as described above before the sorting process to confirm viable cells ( All PBMCs sorted were >90% viable ) . PBMCs were sorted using a FACS-Aria cytometer ( BD Immunocytometry Systems ) . All sorted immune cell subsets were >93% pure based upon flow cytometry analyses . VZV-infected PBMCs were sorted based upon VZV-gE+ along with their lineage markers described in S1 Fig , while uninfected PBMCs were sorted based upon their lineage markers . A minimum of 15 , 000 sorted cells was obtained for all immune cell populations analyzed in all experiments . The addition of CD45 fluorochrome-conjugated antibody was used in FACS sorting gating scheme described in S1 Fig . After FACS sorting of PBMCs , individual VZV-infected immune cell subsets ( 15 , 000–20 , 000 per subset ) were resuspended in complete RPMI media and added to semi-confluent monolayers of HFLs in 96-well plates . After 3 days of co-culturing , HFLs were washed with PBS and harvested using trypsin ( Sciencell ) then plated on ibidi 24-well μ-Plate ( ibidi , Martinsried , Germany ) for an additional 48 h to allow viral infection to spread . In some experiments , sorted PBMCs were washed in citrate buffer ( 40 mM C6H507Na3 , 135 mM KCl , pH = 3 . 5 ) for 3 min , then washed with FACS buffer before co-culturing with HFLs to confirm no potential virus was “stuck” to PBMCs , ensuring that productive viral transmission occurred from VZV-infected PBMCs as previously described [29 , 32] . For flow cytometry analyses of productively infected HFLs , HFLs were harvested 5 days after co-culturing as described above , followed by cell surface staining with VZV gE ( R-PE ) for 30 min on ice . HFLs were then fixed with 1% paraformaldehyde and analyzed using flow cytometry as described above . HFLs were propagated as described above in an ibidi 24-well μ-Plate ( ibidi ) and analyzed for immunofluorescence as previously described [47] . Briefly , HFLs were fixed with 4% paraformaldehyde for 20 min at room temperature , followed by permeabilization with Triton-X ( 0 . 1% ) for 10 min and blocked with normal donkey serum ( 10% ) for 1 hour , then stained against ORF63 ( 1:1000 ) , VZV gB ( 1:500 ) or respective isotype control for 16 h at 4°C , while secondary antibodies were incubated for 1 hour at room temperature . Cells were washed 3 times in PBS following each antibody incubation . Following secondary antibody application and PBS washes , DAPI ( [4′ , 6-]diamidino-2-phenylindole ) ( Vector Laboratories , Burlingame , CA ) was added to the ibidi chambers at a 1:500 dilution for 5 min , washed in PBS and visualized by microscopy . For IFA of PBMCs , individual immune cell subsets were fixed in 1% paraformaldehyde for 24 h at 4°C after flow cytometry sorting and then cytospin was performed based upon manufacturer’s instructions ( ThermoFisher ) . Briefly , cells were cytospinned at 800 RPM for 10 min , followed by permeabilization with Triton-X ( 0 . 1% ) for 10 min and then blocked in normal donkey serum and stained for ORF63 and DAPI as described above . As a positive control for nuclear ORF63 expression and cellular size , uninfected- and VZV-infected HFLs were harvested with trypsin then fixed with 1% paraformaldehyde as described above and cytospinned in the same manner as PBMCs described above . Total RNA was extracted from sorted uninfected- and VZV-infected human PBMCs along with from uninfected- and VZV-infected HFLs using the Direct-zol RNA miniprep kit ( Zymo Research , Irvine , California ) . Enzyme degradation of residual DNA was completed using the Turbo-DNA free kit ( ThermoFisher ) . First strand cDNA synthesis was completed using the Transcriptor first strand cDNA synthesis kit ( Roche , San Francisco , California ) . RNA extraction , DNase treatment and cDNA synthesis were all performed according to the respective manufacturer’s instructions . For q-RT-PCR amplification , primer and probe sets for VZV ORF63 and ORF68 were used as previously described [48]; along with housekeeping gene glyceraldehyde 3-phosphate dehydrogenase ( GAPdH; FWD: CACATGGCCTCCAAGGAGTAA , REV: TGAGGGTCTCTCTCTTCCTCTTGT , Probe: VIC/CTGGACCACCAGCCCCAGCAAG ) . Q-RT-PCR cycling conditions consisted of a holding stage at 95°C for 10 min , followed by a cycling stage of 95°C for 30 seconds and 60°C for 1 min ( 40 cycles ) . As a control for viral DNA contamination , cDNA synthesis was performed without the addition of reverse transcriptase and analyzed for q-RT-PCR analyses in the same manner as mentioned above . For PD-L1 blockade experiments in HBVAFs , HLA A*0201 ( + ) HBVAFs were grown in 12-well plates at an approximate density of 5 . 0 x 10^5 cells/well , uninfected- or VZV-infected , treated with anti-PD-L1 ( 10 μg/ml; Biolegend clone 29E . 2A3 ) or isotype control ( 10 μg/ml; Biolegend ) for 30 min , and co-cultured with VZV-specific CD8+ T cells ( 2 . 0 x 10^6 cells/well ) for 24 h before harvest of cell culture supernatants for IFNγ ELISA analyses . For PD-L1 , PD-L2 and CTLA-4 blockade experiments using PBMCs from the same donor from whom the VZV-specific CD8+ T cells were derived , frozen PBMCs were co-cultured with uninfected- or VZV-infected HFLs for 48 h as described above and only non-adherent cells were harvested , washed in FACS buffer , seeded in 96-well plates ( 1 . 0 x 10^5 cells/well ) and treated with either anti-PD-L1 ( 10 μg/ml; Biolegend ) , anti-PD-L2 ( 10 μg/ml; Biolegend clone MIH18 ) , anti-CTLA-4 ( 10 μg/ml; Biolegend clone L3D10 ) or isotype control ( 10 μg/ml; Biolegend ) for 1 h before co-culture with VZV-specific CD8+ T cells ( 1 . 0x10^5 cells/well ) for 24 h . Cell culture supernatants were then harvested for IFNγ ELISA analyses . Levels of IFNγ in cell culture supernatants were measured using the Meso Scale Discovery human IFNγ kit ( Rockville , MD ) according to the manufacturer’s instructions . IFNγ levels were calculated by reference to a standard curve and all samples were analyzed in duplicate . Statistical analysis was performed using GraphPad Prism ( GraphPad , San Diego , CA ) . Statistical significance was determined using the Student’s unpaired t-test , repeated measures ( RM ) one-way ANOVA with the Greenhouse-Geisse correction and Tukey posttest , and ordinary one-way ANOVA with the Tukey posttest . | The burden of disease produced by VZV is significant , since 90% of the world population harbors latent virus . At least 50% of infected individuals will reactivate by 85 years of age to develop zoster , which is an established risk factor for stroke and myocardial infarction , as well as multisystem diseases with or without rash . VZV-infected PBMCs disseminate virus to distal organs to produce clinical disease . PD-L1 is an immunoinhibitory protein that interacts with PD-1 , its receptor , expressed mainly on T cells to prevent their activation and subsequent clearance of virus- or malignantly transformed cells . We show here that all peripheral blood mononuclear cells have a dramatic induction of PD-L1 expression upon infection with VZV , which is combined with the induction of PD-1 expression on CD8+ T cells , NKT cells and VZV-specific CD8+ T cells . Blocking PD-L1 during co-culturing of VZV-specific CD8+ T cells with autologous VZV-infected PBMCs enhanced IFNγ levels almost 2-fold compared to isotype controls . These results indicate that blocking PD-L1 expression during varicella or zoster may restore CD8+ T cell effector function , enabling effective clearance of virus-infected cells to reduce viral spread and multisystem disease . | [
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] | 2019 | Varicella zoster virus productively infects human peripheral blood mononuclear cells to modulate expression of immunoinhibitory proteins and blocking PD-L1 enhances virus-specific CD8+ T cell effector function |
Crimean-Congo hemorrhagic fever virus ( CCHFV ) is a tick-borne bunyavirus causing outbreaks of severe disease in humans , with a fatality rate approaching 30% . There are no widely accepted therapeutics available to prevent or treat the disease . CCHFV enters host cells through clathrin-mediated endocytosis and is subsequently transported to an acidified compartment where the fusion of virus envelope with cellular membranes takes place . To better understand the uptake pathway , we sought to identify host factors controlling CCHFV transport through the cell . We demonstrate that after passing through early endosomes in a Rab5-dependent manner , CCHFV is delivered to multivesicular bodies ( MVBs ) . Virus particles localized to MVBs approximately 1 hour after infection and affected the distribution of the organelle within cells . Interestingly , blocking Rab7 activity had no effect on association of the virus with MVBs . Productive virus infection depended on phosphatidylinositol 3-kinase ( PI3K ) activity , which meditates the formation of functional MVBs . Silencing Tsg101 , Vps24 , Vps4B , or Alix/Aip1 , components of the endosomal sorting complex required for transport ( ESCRT ) pathway controlling MVB biogenesis , inhibited infection of wild-type virus as well as a novel pseudotyped vesicular stomatitis virus ( VSV ) bearing CCHFV glycoprotein , supporting a role for the MVB pathway in CCHFV entry . We further demonstrate that blocking transport out of MVBs still allowed virus entry while preventing vesicular acidification , required for membrane fusion , trapped virions in the MVBs . These findings suggest that MVBs are necessary for infection and are the sites of virus-endosome membrane fusion .
Crimean-Congo hemorrhagic fever virus ( CCHFV ) is a tick-borne virus causing outbreaks of severe hemorrhagic disease in humans , with a fatality rate approaching 30% . The virus is endemic to much of Eastern Europe , the Middle East , Asia , and Africa , although recent studies have detected CCHFV in ticks collected in Spain , indicating an expanding geographic distribution [1]–[4] . Despite the high mortality and global distribution of CCHFV , there are presently no licensed therapeutics to prevent or treat the disease . CCHFV belongs to the family Bunyaviridae . It is an enveloped , pleomorphic virus , possessing a tripartite single-stranded RNA genome in negative orientation . The small segment , S , encodes the nucleocapsid protein N , whose role is to encapsidate viral RNA during transcription and genome replication . The large segment , L , encodes the RNA-dependent RNA polymerase , which associates with N to form the viral polymerase complex [5] . The medium segment , M , contains the gene for the viral glycoprotein polyprotein , which is co-translationally cleaved and post-translationally modified to generate two structural transmembrane proteins , Gc and Gn , and non-structural proteins GP38 and NSm [5]–[9] . The Gc and Gn form complexes on the virion surface and are responsible for binding to the cellular receptors and subsequent fusion of the viral envelope with host membranes [10] , [11] . Virus entry into the cell is the first and critical step in the virus replication cycle . The host receptor of CCHFV has not been identified , although a recent study has suggested that nucleolin plays a necessary role in virus entry and that Gc is essential for binding to the cell [12] . Virus uptake occurs through clathrin-dependent endocytosis and requires cholesterol and low pH to productively infect host cells [13] , [14] . An earlier study implicated Rab5 , a small GTPase critical for vesicular transport from the plasma membrane to early endosomes , as important for infection [13] . The lack of the involvement of Rab7 , which controls vesicular trafficking to late endosomes , in infection and the requirement for pH 6 . 0 to inactivate the virus led to speculation that virus fusion with host membranes takes place at early endosomes [13] , although direct localization of virus to the early endosomes was not demonstrated . Little else is known about trafficking of the virus along the endocytic route or the identity of cellular compartments where the fusion of the viral and host membranes takes place . Here , we investigated the mechanism of transport of CCHFV through the host cell in more detail .
CCHFV enters cells by clathrin-mediated endocytosis [13] , [14] . The virus was also previously shown to require Rab5 during infection of cells [13] , suggesting a requirement for trafficking through early endosomes . However , localization of the virus to early endosomes has not been demonstrated , and so we examined uptake and trafficking kinetics of virus particles in more detail . Human adenocarcinoma cell line , SW13 , has been demonstrated to support CCHFV replication [15] and , therefore , was utilized in our study . SW13 cells were incubated with CCHFV for up to 120 min and then stained with antibodies to virus nucleoprotein N and early endosome antigen 1 ( EEA1 ) , which localizes exclusively to early endosomes [16] . CCHFV is known to enter cells within 90 min [14] , and therefore the N protein signal was likely to represent incoming virions . We observed that virus localized to early endosomes as early as 15 min and reached steady state by 30 min , with approximately 10% of the virions being EEA1-associated ( Fig . 1A ) . Our results directly confirm that CCHFV is trafficked through early endosomes during infection . To test whether Rab5A facilitates CCHFV movement to early endosomes , we expressed a fusion of enhanced green fluorescent protein ( eGFP ) and the dominant negative form of the Rab5A containing a substitution of serine to asparagine at position 34 ( DN Rab5A ) in SW13 cells and then infected the cells with wild-type virus . The control included cells expressing eGFP . The DN Rab5A arrests transport of vesicles from the cell surface due to a block in maturation of early endosomes [17] , [18] and , therefore , we expected to observe accumulation of virions near the cell surface . Indeed , cells expressing the DN , but not eGFP , showed virions localized close to the plasma membrane , in EEA1-positive structures ( Fig . 1B ) . This finding confirms that CCHFV is transported in a Rab5A-dependent manner . While expression of DN Rab5A inhibits formation of early endosomes , expression of a constitutively active mutant of Rab5A containing a substitution of glutamine to leucine at position 79 ( CA Rab5A ) enhances the formation of the endosomes , making the vesicles appear drastically enlarged , but also compromises maturation of and cargo transport to later endosomal compartments [19]–[22] . To determine whether CCHFV entry involves passage through endosomal compartments downstream of early endosomes , SW13 cells expressing a fusion of eGFP and CA Rab5A or eGFP alone as a control were infected with CCHFV for 24 h to allow virus to establish replication sites [13] , [14] . The N distribution in eGFP-expressing cells was similar to that seen in untransfected cells and likely represented pools of newly expressed protein due to virus gene expression and genome replication . In contrast , in CA-expressing cells , N staining was limited and likely represented incoming virus trapped in endosomes , consistent with that described in the above figures ( Fig . 1C , left and middle panels ) . The percentages of eGFP-expressing cells that were infected with CCHFV were found to be 47% and 1% in control eGFP- and CA-expressing cells , respectively ( Fig . 1C , right panel ) . These data demonstrate that productive infection by CCHFV requires trafficking through early endosomes as well as downstream endosomal compartments . Over time , cellular cargo from early endosomes can become concentrated on intraluminal vesicles within vacuolar domains , generating multivesicular bodies ( MVBs ) [23] , [24] . Several viruses traffic through the MVB and depend on its sorting machinery during early steps in infection , including influenza A virus , vesicular stomatitis virus ( VSV ) , Lassa fever virus ( LASV ) , and lymphocytic choriomeningitis virus ( LCMV ) [25]–[28] . To test whether CCHFV localizes to MVBs during entry , we incubated SW13 cells with virus for up to 120 min and then stained them for N and tetraspanin protein CD63 , which is enriched in MVBs [29] . As shown in Fig . 2A , virus localized to CD63-positive structures , presumably MVBs , starting at 60 min post-infection . This association appeared to accelerate over time until a major redistribution of the organelle occurred within the cell ( Fig . 2A ) . CD63 is also known to contain a putative lysosomal targeting signal and to colocalize with late endosomal/lysosomal-associated membrane proteins Lamp1 and Lamp2 [30] , suggesting that a fraction of this protein is in late endosomes and lysosomes . To address the question whether CCHFV localizes to these endosomal compartments during infection , we infected cells with CCHFV for 120 min and then stained them with antibodies detecting either ( i ) N and ALG-2-interacting protein X/apoptosis-linked-gene-2-interacting protein 1 ( Alix/Aip1 ) , which associates with MVBs to coordinate vesicle formation and biogenesis [31]; or ( ii ) N and Lamp1 . As shown in Fig . 2B , 35% of CCHFV particles localized with Alix/Aip1 , while only 3% of virions were found in Lamp1-positive endosomes . While it is possible that the Lamp1-positive endosomes represent late endosomes or lysosomes , the relevance of the association to virus infection mechanism is questionable since Rab7 , which controls vesicular transport out of MVBs [32] , does not play a role in CCHFV infection [13] . Thus , our findings demonstrate that virus is transported through MVBs during early stages of infection . Several studies have reported that Rab7 controls cargo movement out of early endosomes [33] , [34] , while others indicate the function of this Rab later in the endocytic pathway , from MVBs to lysosomes [32] . To test whether Rab7A has a role in virus transport to MVBs in SW13 cells , we overexpressed the DN form of Rab7A , containing a substitution of threonine to asparagine at position 22 [35] , in cells , challenged them with virus , and then tested for localization of virus to CD63-positive compartments . As a control , we transfected cells with a plasmid expressing eGFP alone . The overexpression of the DN or eGFP had no effect on localization of the virus to the MVBs ( Fig . 2C ) , suggesting that Rab7A does not control virus transport between early endosomes and MVBs . Because Rab7 was shown as not important for CCHFV infection [13] , our findings also indicate that CCHFV might not traffic beyond MVBs . According to our data , CCHFV colocalizes with and redistributes MVBs during early stages of infection . It is unclear , however , whether there is a functional significance of this association . To study CCHFV infection in more detail , we generated CCHFV that incorporated a minigenome segment encoding the red fluorescent protein mKate2 ( CCHFV-mKate2 ) . BsrT7/5 cells [36] were transfected with the minigenome construct and plasmids expressing viral N and polymerase and then mock-infected or infected with wild-type CCHFV . The recombinant virus was collected 48 h after infection and inoculated onto fresh SW13 cells to assess packaging of the minigenome . As seen in Fig . 3A , inoculation of the supernatant from the cells infected with the virus resulted in the expression of the mKate2 gene in the cells , demonstrating the generation of recombinant CCHFV-mKate2 . Without superinfection , no mKate2 signal was seen ( Fig . 3A ) . To verify that CCHFV-mKate2 infection is comparable to the wild-type CCHFV , we tested a range of pharmacological inhibitors . Since CCHFV infection has been shown to depend on clathrin-dependent endocytosis , cholesterol , and low pH [13] , [14] , we used the following reagents: ( i ) bafilomycin A , a specific inhibitor of vacuolar-type H+-ATPase [37]; ( ii ) 5- ( N-Ethyl-N-isopropyl ) amiloride ( EIPA ) , an inhibitor of the Na+/H+ exchanger that specifically blocks macropinocytosis [38]; ( iii ) nystatin , which sequesters cholesterol in the plasma membrane [39]; ( iv ) dynasore , a specific inhibitor of dynamin , which is essential for the formation of clathrin-coated and caveolae vesicles [40]; and ( v ) chlorpromazine hydrochloride ( CPZ ) , a specific inhibitor of clathrin-dependent endocytosis [41] . Similar to wild-type virus , CCHFV-mKate2 required low pH , free cholesterol , and the formation of clathrin-coated pits to infect host cells ( Fig . 3A , right panel ) . MVB formation requires class III PI3K activity , which directs synthesis of the lipid phosphatidylinositol 3-phosphate ( PI3P ) [25] , [42] , [43] . The requirement for PI3K in CCHFV infection was examined using the drug LY294002 , a potent and specific inhibitor of this enzyme [43] , [44] . As shown in Fig . 3B , treatment of the cells with the inhibitor blocked CCHFV-mKate2 infection by approximately 80% , supporting a possible functional role for MVBs in CCHFV infection . MVB biogenesis critically depends on a group of class E vacuolar protein sorting ( Vps ) regulators , which form three large hetero-oligomeric complexes within the ESCRT pathway and are designated ESCRT-I , II , and III . The cargo , which is initially selected in early endosomes , is passed on to ESCRT-I on MVB membranes , where tumor susceptibility gene 101 ( Tsg101 ) protein plays a central role in recognizing the cargo and activating ESCRT-II and subsequently ESCRT-III complexes [45] . ESCRT-associated ATPases Vps4A and B are important in the later stages of the MVB pathway by catalyzing disassembly of ESCRT-III complex , a step critical for sorting cargo into intraluminal vesicles within MVBs [46] . Alix/Aip1 interacts with Tsg101 and components of ESCRT-III complex and , as indicated above , directly modulates the formation of intraluminal vesicles , giving rise to MVBs [31] . To further investigate whether MVB biogenesis is critical for CCHFV infection , we tested the effect of depleting cellular Tsg101 , Vps24 ( ESCRT-III component ) , Vps4B , and Alix/Aip1 ( Fig . 4C ) on efficiency of CCHFV-mKate2 infection . Treatment of cells with siRNAs specific to these ESCRT regulators , but not with a non-targeting siRNA , blocked infection by >60% , with Alix/Aip1 siRNAs being the most potent ( Figs . 4A–B ) . These data demonstrate that the MVB/ESCRT pathway controls CCHFV infection . Our results indicate that CCHFV is transported through MVBs and that productive virus infection requires MVB biogenesis . However , it is unclear what step of the viral lifecycle is regulated by the MVB pathway; it could be entry and/or viral gene expression and genome replication . Pseudotyped virus particles have become a valuable tool for analysis of entry mechanism of numerous viruses . However , to date , no pseudotype system has been described for CCHFV . To generate VSV pseudotyped with CCHFV glycoproteins ( VSV-CCHFVG ) , we expressed CCHFV glycoprotein precursor G or β-galactosidase ( control ) in 293FT cells and then inoculated the cells with Venezuelan equine encephalitis virus glycoprotein ( VEEV GP ) pseudotyped VSV stock encoding a firefly luciferase reporter gene ( VSV-VEEVGP ) . VSV-VEEVGP was used because of its ability to grow to high titers and because residual VEEV GP is short-lived in target cells ( our unpublished data ) . As VSV core is replicated and new viral particles are assembled , the overexpressed CCHFV glycoproteins would become incorporated into nascent virions . β-galactosidase-expressing cells served as an indicator of VSV-VEEVGP carryover in the media of the inoculated cells since no viral glycoprotein was expressed there . The pseudotyped virus was collected 48 h after addition of VSV-VEEVGP and added to monolayers of SW13 cells to assess titers by measuring luciferase activity . The intensity of luminescence in cells incubated with VSV-CCHFVG was typically 8 times higher than in cells incubated with the control supernatant ( Fig . 5A ) . Since Gc is crucial for CCHFV binding to the cell [12] , we performed a neutralization test using a polyclonal anti-Gc antibody to assess whether functional CCHFV glycoprotein complexes were present on the pseudovirion surface . VSV-CCHFVG or VSV-VEEVGP was incubated with the antibody , and the pseudotype-antibody mixtures were transferred onto SW13 cells . Luciferase activity was measured 24 h later . The antibody treatment inhibited VSV-CCHFVG , but not VSV-VEEVGP infection in a dose-dependent manner , indicating that the pseudovirus entry was glycoprotein-mediated ( Fig . 5B ) . CCHFV infection is pH-dependent , requiring endosomal acidification during entry ( [13] , [14] and Fig . 2A ) . To test pH dependency of VSV-CCHFVG , SW13 cells treated with DMSO or bafilomycin A were challenged with the pseudotyped virus . As seen in Fig . 5C , bafilomycin A treatment inhibited infection by >98% , demonstrating that , similarly to wild-type CCHFV , the pseudotyped virus requires acidic environment for infection and confirming that glycoprotein activation depends on low pH . We next used VSV-CCHFVG to verify whether the MVB pathway had a role in CCHFV entry . SW13 cells depleted of cellular Tsg101 , Vps24 , Vps4B , or Alix/Aip1 ( Fig . 4C ) were incubated with VSV-CCHFVG . A recent study reporting the involvement of ESCRT regulators in arenavirus entry excluded the possibility that these ESCRT-specific siRNA treatments affected cytoplasmic transport or replication of the VSV core [25] . As seen in Fig . 5D , silencing ESCRT regulators significantly inhibited VSV-CCHFVG infection , suggesting that the MVB/ESCRT pathway is crucial for CCHFV entry . According to our results , CCHFV is transported through MVBs and requires ESCRT regulators during entry . The drug U18666A inhibits lipid transport from MVB/late endosomal compartments [47] , [48] and disrupts the trafficking of MVB-associated membrane proteins [48]–[50] . To test whether virus needs to traffic beyond MVBs , mock-treated cells or cells treated with U18666A were challenged with wild-type CCHFV for 24 h and then stained with anti-N antibody to assess infection and with anti-CD63 antibody to examine MVB morphology . We found that U18666A had no effect on virus infection as the expression level and the intracellular distribution of N or infection efficiency ( approximately 4% ) were similar to those in mock-treated cells ( Fig . 6A ) . The N distribution was consistent with previously reported data [51] , appearing as aggregates of various sizes close to the cell nucleus . These did not colocalize with the MVB marker CD63 , despite an increase in size and number of CD63 puncta ( Fig . 6A ) , likely due to the block of sphingolipid and cholesterol traffic out of the organelle [47]–[50] . Indeed , in agreement with previous reports [50] , [52] , we observed an accumulation of cholesterol in MVBs in cells treated with U18666A , but not in mock-treated cells , by staining with the cholesterol-binding compound filipin III ( Fig . 6B ) . We next examined whether U18666A treatment affected virus entry . Mock-treated cells or cells treated with U18666A were incubated with VSV-CCHFVG . Controls were pseudotyped viruses containing either Ebolavirus ( EBOV ) or LASV glycoprotein ( VSV-EBOVGP and VSV-LASVGP , respectively ) . EBOV entry depends on the cholesterol transporter protein Niemann-Pick C1 and therefore is sensitive to U18666A treatment [53] , [54] . LASV passes through MVBs during entry to fuse with late endosomal membranes where Lamp1 serves as a fusion receptor [25] , [55] . We found that the inhibitor had no effect on VSV-CCHFVG infection , while infections of VSV-EBOVGP and VSV-LASVGP were blocked by >98% and >85% , respectively ( Fig . 6C ) , suggesting that lipid traffic out of MVBs is not required for CCHFV entry . These data and findings that Rab7 does not play a role in CCHFV infection [13] or localization to MVBs ( Fig . 2C ) demonstrate that virus does not require trafficking beyond MVBs during entry . Our results indicate that MVBs might represent the last endocytic compartment before CCHFV escape into the cytoplasm for replication ( Figs . 2C and 6 ) . In Fig . 3A and work by others [13] , [14] , the virus also requires an acidic environment to establish productive infection . Therefore , blocking endosomal acidification should trap virus in vesicles prior to sites of membrane fusion . Cells treated with bafilomycin A or DMSO were incubated with wild-type virus for 24 h . We then assessed the intracellular distribution of viral N protein and N-MVB colocalization . According to both Simon et al . [14] and our findings ( Fig . 5C ) , inhibition of vesicular acidification for 24 h blocked virus entry . We observed that , while DMSO treatment did not affect virus infection , treatment with bafilomycin A resulted in accumulation of N , presumably virions , within MVBs ( Fig . 7A , top and middle panels ) . The amounts of N found in MVBs were 4% in DMS0-treated cells and 67% in bafilomycin A-treated cells ( Fig . 7A , lower left panel ) . Next , we determined whether virus genome replication took place in MVBs . Cells treated with DMSO in duplicate or bafilomycin A were inoculated with CCHFV . We then isolated RNA from one set of DMSO-treated cells 2 h later and from the other two samples 24 h after virus addition . The RNA was used to determine virus genome copies present , where the sample collected from the first set of DMSO-treated cells served as a control , since virus genome replication is not detectable 2 h after incubating cells with virus [14] . As seen in Fig . 7B , no significant difference in the genome copy number was observed between the control sample and the bafilomycin A-treated sample . In contrast , the second set of DMSO-treated cells exhibited a 6-log increase in genome equivalents , demonstrating that bafilomycin A treatment blocks CCHFV replication . To test whether virus replication was a requirement for virus localization to MVBs , we repeated the experiment identical to that described in Fig . 7A but used CCHFV that was inactivated by gamma-irradiation . We observed that approximately 40% of virions associated with MVBs in cells that were treated with either DMSO or bafilomycin A ( Fig . 7C ) , demonstrating that CCHFV association with MVBs is independent of genome replication . Altogether , our findings suggest that CCHFV membrane fusion or capsid penetration into the cell cytoplasm likely occurs from MVB compartments .
Entry into host cells is the first committal step in any virus replication cycle . In this study , we characterized the entry route taken by CCHFV after internalization from the plasma membrane . We confirmed previous work that the virus was transported through early endosomes in a Rab5A-dependent manner , but additionally showed that MVBs play an important role in productive infection . Virions localized to and reorganized the intracellular distribution of MVBs , and ESCRT pathway-related proteins involved in MVB formation and function were needed for entry . We also determined that endocytic trafficking out of MVBs did not affect CCHFV infection and that blocking endosome acidification resulted in accumulation of virions in the MVBs . These findings indicate that during entry the MVB is a late stage destination of CCHFV particles and is likely the site from which they are released into the cell cytoplasm to initiate genome replication . CCHFV enters cells by clathrin-dependent endocytosis [13] , [14] . The process is rapid , with endocytosed ligands and receptors being sorted to different organelles for processing [56]–[59] . Early endosomes have been considered to be initial sorting organelles [57] , [59] , and since CCHFV infection was shown to require Rab5 , the virus was thought to traffic through this compartment [13] . However , actual localization of virions to early endosomes was not previously demonstrated . In the current study , we used microscopy to track movement of CCHF virions through endocytic compartments . Virions were found in early endosomes starting at 15 min post-infection ( Fig . 1A ) , although we do not exclude the possibility that the virus localized to early endosomes at even earlier time points , as has been demonstrated for influenza A virus [59] . The increase in percentage of viral particles in the endosomes at later time points , however , indicates that CCHFV may enter host cells at a slower pace , reflecting potential differences in endosomal kinetics in different cell lines , markers used to identify the endosomes , or viral entry mechanisms . Recently , Lakadamyali et al . suggested that early endosomes consist of two populations with distinct maturation kinetics , designated dynamic and static [59] . Cargo in the static population undergoes endocytosis less rapidly and depends , at least in part , on the presence of adaptor protein complex 2 ( AP-2 ) [59] , [60] . CCHFV infection requires AP-2 [13] , while influenza A virus infection does not [59] , suggesting that these two viruses may utilize different sets of early endosomes for uptake into cells . Cargo sorted in early endosomes can be progressively shuttled along the endocytic pathway toward MVBs [23] , [24] . Several viruses , including those entering cells by clathrin-mediated endocytosis , have been demonstrated to localize to MVBs and depend on the sorting protein complex , ESCRT , during infection . Influenza A virus , LASV , and LCMV appear to pass through MVBs on their way toward late endosomes , while VSV needs the compartment to release genome into the cytoplasm for replication [25]–[28] . For CCHFV , MVB involvement seems to be distinct . We found that CCHF virions localized to and dramatically affected intracellular distribution of MVBs ( Fig . 2A ) . ESCRT regulators controlled CCHFV entry ( Figs . 4 and 5D ) , and trafficking beyond MVBs appeared to be dispensable for virus infection and entry ( Figs . 2C and 6 ) , suggesting that MVBs might be the last endosomal compartment before virus exit into the cytoplasm . The small number of virus particles in Lamp1-positive compartments ( Fig . 2B ) raised a question about a role , if any , of late endosomes or lysosomes in CCHFV infection . Since Rab7 controls vesicular transport out of MVBs [32] and is not essential for virus infection [13] , it is unlikely that localization of virus particles to compartments downstream of MVBs has functional significance . Additionally , a small amount of Lamp1 is found in MVBs [61]–[63] , so CCHF virions might have localized to these Lamp1-positive MVBs . We detected virus particles by staining infected cells with an anti-N antibody , and therefore our data indicate that MVBs may be where virus-endosome fusion takes place or where , similarly to VSV , nucleocapsids are released into the cytoplasm , or both , provided membrane fusion and nucleocapsid release are concurrent . Because our data also showed that blocking vesicular acidification resulted in inhibition of a novel CCHFV pseudotype ( Fig . 5C ) , affecting glycoprotein function and therefore virus entry , and accumulation of N , presumably virions , in MVBs ( Figs . 7A and 7C ) , MVBs are likely the site of fusion of the viral and host membranes . The role of the MVB redistribution during CCHFV infection is unclear and requires additional examination , but , to our knowledge , was not observed during infection by any other virus . While we identified Rab5A as a factor controlling CCHFV traffic from the plasma membrane to early endosomes ( Fig . 1B ) , it is less clear how virions are transported from early endosomes to MVBs . Rab7 is known to localize on a variety of organelles including early and late endosomes , MVBs , and lysosomes [32] , [64] , [65] . It is unclear , however , whether Rab7 regulates transport between these organelles or is itself trafficked via each to reach compartment ( s ) it functions on . A study by Vanlandingham and Ceresa showed that silencing Rab7 expression had no effect on MVB biogenesis , but instead affected lysosomal degradation of the epidermal growth factor in complex with its receptor by blocking transport/fusion between MVBs and lysosomes [32] . Our current observations ( Fig . 2C ) are in agreement with those findings , demonstrating that for CCHFV , Rab7A does not contribute to early endosome-MVB transport and therefore does not control CCHFV infection , which is consistent with previously reported data [13] . Additional factors controlling the traffic between early endosomes and MVBs remain to be identified . The formation of internal vesicles within MVB compartments requires class III PI3K , whose cellular role is to facilitate synthesis of PI3P lipid [25] , [42] , [43] . Protein sorting machinery , which selects cargo in early endosomes , is thought to directly bind early endosome-specific PI3P [66] , [67] and subsequently recruit ESCRT complexes to MVB membranes [68] . Inhibition of PI3K activity , therefore , results in formation of defective MVB compartments devoid of internal vesicles and thus missorted cargo . In the presence of PI3K inhibitor LY294002 , CCHFV infection was significantly reduced ( Fig . 3B ) , most likely due to the block in MVB biogenesis . In addition to its role in vesicle formation and membrane trafficking , PI3K pathway is known to regulate various cellular functions such as survival and proliferation , glucose transport , superoxide production , and motility through actin rearrangement [69] . There is mounting evidence that the PI3K pathway is often disregulated in human tumors [70] . To date , several promising PI3K inhibitors have entered human trials for cancer treatments [71] , [72] . Our current results that the PI3K pathway is also required for CCHFV infection could be exploited for development of new therapeutics to treat the CCHFV disease . One of the limiting factors in studying early steps in CCHFV infection has been the lack of a pseudotyped virus . Although pseudotype systems have been described for several bunyaviruses [73]–[76] , no such system was reported for CCHFV to date . Here , we reported a VSV core virus pseudotyped with CCHFV glycoprotein . Treatment of the pseudotyped virus with anti-Gc antibody or bafilomycin A ( Figs . 5B–C ) inhibited its infection , indicating that the entry was glycoprotein-dependent . The finding that neutralizing antibody blocked pseudotype infection also demonstrated that the pseudotype can be used in rapid diagnostic assays , circumventing the need for high-level biosafety containment and pathogenic virus stocks . The bunyavirus family consists of five genera with over 350 members [5] . Of those tested , each require low pH to productively infect host cells and so , require uptake into acidified endosomes [22] , [77]–[81] . CCHFV belongs to the Nairovirus genus , and its entry route is similar to that used by members of the Orthobunyavirus genus , particularly La Crosse and Oropouche viruses . La Crosse virus infection was shown to be inhibited by overexpression of DN Rab5 , but not DN Rab7 , leading to the conclusion that this virus undergoes fusion at early endosomes [77] , as was thought to occur for CCHFV [32] . While this might be the case , given our findings , MVBs may play a similar role in La Crosse virus infection ( Figs . 2A–B ) . For Oropouche virus , virions were not seen associated with early endosomes , but did localize to Rab7-positive endosomes [80] , indicating that the virus may bypass the early endosome compartment . However , the location of Oropouche virus particles in cells was only examined after 40 minutes . This seemingly different mechanism of entry may be explained by the rapid and/or transient movement of virions through early endosomes , which , for CCHFV , occurred as early as 15 minutes after incubation with cells . The finding that Oropouche virus was Rab7-associated does suggest trafficking to late endosomes; however , Rab7 is not ideal for identifying the exact endosomal compartment since it localizes to various organelles , including subsets of MVBs , late endosomes , and lysosomes [32] . It is , therefore , important to determine if either La Crosse or Oropouche virus requires the MVB for infection or if CCHFV has a unique need for this compartment . In contrast , Hantaan and UUkuniemi viruses , each belonging to the Hantavirus and Phlebovirus genera , do require trafficking through and function of late endosomes or lysosomes [22] , [79] . For Hantaan virus , virions were associated with Lamp1-positive endosomes , although functional significance of this association was not investigated [79] . A comprehensive study by Lozach et al . used a combination of microscopy as well as overexpression of DN and CA forms of Rab5 and Rab7 to track UUkuniemi virions through the endosomal network . Their findings convincingly demonstrate that UUkuniemi virus infection depends on Rab7 and requires virion localization to late endosomes or lysosomes [22] . Unfortunately , passage of virus particles through MVBs was not studied . These differences in entry mechanisms for viruses may reflect the broad diversity of viruses across the Bunyaviridae family . In conclusion , our work has identified a novel requirement for trafficking of CCHFV through MVBs and has shown that host proteins controlling MVB function are important host factors needed for CCHFV infection and entry . Our findings were substantiated through the production and use of a novel pseudotyped virus bearing the glycoprotein of CCHFV . This reagent will most certainly stimulate further studies on entry mechanism of the virus as well as serve as a safe diagnostic tool overcoming the need to cultivate wild-type , pathogenic virus . The knowledge acquired during the studies will help to design new strategies for therapeutic intervention against this pathogen .
Human adrenal gland carcinoma ( SW13; ATCC #CCL-105 ) cells were cultivated in Dulbecco's modified Eagle's medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) . 293FT ( Life Technologies , Carlsbad , CA ) and baby kidney hamster-derived BsrT7/5 cells [36] were cultivated in DMEM supplemented with 10% FBS and 0 . 5 mg/mL G418 ( Life Technologies , Carlsbad , CA ) . All cells were maintained at 37°C with 5% CO2 . Rabbit antibody to CCHFV N was generously provided by Ali Mirazimi ( Karolinska Institutet , Sweden ) , and mouse antibody to CCHFV N was provided by Connie Schmaljohn ( U . S . Army Medical Research Institute of Infectious Diseases , Washington , D . C . ) . The mouse antibody to CD63 , clone H5C6 , developed by J . Thomas August and James E . K . Hildreth ( Johns Hopkins University School of Medicine ) was obtained from the Developmental Studies Hybridoma Bank , created by the National Institute of Child Health and Human Development ( NICHD ) , and maintained at The University of Iowa , Department of Biology , Iowa City . Mouse antibodies to Tsg101 and rabbit antibodies to Vps24 , Vps4B , and PDCD6 ( referred to as Alix/Aip1 ) were from Abcam , Cambridge , MA . Other antibodies used here were mouse antibody to GAPDH ( Life Technologies , Carlsbad , CA ) , mouse antibody to EEA1 ( BD Biosciences , Franklin Lakes , NJ ) , mouse antibody to Lamp1 ( Santa Cruz Biotechnologies , Dallas , TX ) , and rabbit antibody to CCHFV Gc ( IBT Bioservices , Gaithersburg , MD ) . Dimethylsufoxide ( DMSO ) was from ATCC ( Manassas , VA ) ; 5- ( N-Ethyl-N-isopropyl ) amiloride ( EIPA ) was from Sigma ( St . Louis , MO ) ; LY294002 , U18666A , bafilomycin A , dynasore , nystatin , and chlorpromazine hydrochloride ( CPZ ) were from EMD Millipore ( Billerica , MA ) . All experiments with infectious CCHFV strain IbAr10200 were performed in the biosafety level 4 ( BSL-4 ) laboratory at the Texas Biomedical Research Institute ( San Antonio , TX ) . The virus was amplified in SW13 cells in DMEM containing 2% FBS for 5 days . To determine the titer of the virus stock , SW13 cells were incubated with 10-fold serial dilutions of the virus at 37°C for 1 h . After the virus was removed , the cells were overlaid with DMEM containing 2% FBS and 1 . 5% methyl cellulose ( Sigma , St . Louis , MO ) . Forty-eight hours later , cells were fixed in 10%-buffered formalin ( Sigma , St . Louis , MO ) for 24 hours . Then , the cells were stained with the anti-N antibody , and fluorescent foci were counted to determine the virus titer . To generate a CCHFV stock for gamma-irradiation , supernatants of SW13 cells infected with the virus for 5 days were clarified of debris , laid over a cushion of 20% sucrose in PBS , and centrifuged for 3 h at 25 , 000 rpm at 4°C . The pellet containing concentrated virus was resuspended in PBS and stored at −80°C . The sample was subjected to a single dose of 5 Mrad cobalt-60 gamma-irradiation at the BSL-4 laboratory at the University of Texas Medical Branch , Galveston , TX . The inactivation of the virus was confirmed by a plaque assay . Recombinant vesicular stomatitis virus ( VSV ) , containing a substitution of VSV glycoprotein G gene with a gene encoding firefly luciferase was generously provided by Sean Whelan ( Harvard Medical School , Boston , MA ) . The codon-optimized cDNA of CCHFV G and N ( strain IbAr10200 ) , and L ( strain Sudan ) were synthesized and cloned into pcDNA3 . 1 ( + ) vector ( Life Technologies , Carlsbad , CA ) by Epoch Life Science ( Missouri City , TX ) , producing pcDNA-G , pcDNA-N , and pcDNA-L , respectively . The G gene was subsequently amplified by PCR with a forward primer ( 5′-ttttggcaaa GAATTC ATG CAT ATC AGC CTC ATG TAC GCT ATC TTG-3′ ) and a reverse primer ( 5′- cgggggtaccCTCGAG CTA GCC TAT ATG TGT TTT TGT GCT AAA CAG CTC-3′ ) . The PCR product was cloned into the protein expression vector pCAGGS/MCS [82] , [83] using In-Fusion cloning technology ( Clontech , Mountain View , CA ) to generate pC-G . To obtain pT7-mKate2 , the cDNA of the red fluorescent protein mKate2 in the antisense orientation between the 5′ and 3′ terminal non-coding regions ( NCRs ) of the CCHFV M segment and flanked by the T7 RNA polymerase promoter and a ribozyme was synthesized by Epoch Life Science . The cDNA digested with ClaI and SalI was then subcloned into a vector backbone generated by excising the Ebolavirus minigenome from the p3E5E-Luc [84] ( a generous gift of Elke Muhlberger ( Boston University ) ) . To obtain pT7-Sseg , two-step PCR was performed . In the first step , culture supernatant of SW13 cells infected with CCHFV was used as a template for reverse transcription ( RT ) -PCR to amplify S segment with a forward ( 5′-TCT CAA AGA AAC ACG TGC CGC TTA C-3′ ) and a reverse ( 5′-TCT CAA AGA TAC CGT TGC CGC AC-3′ ) primers . A ribozyme cDNA was generated by PCR using pT7-mKate2 as a template and a forward ( 5′-GTA AGC GGC ACG TGT TTC TTT GAG A GGG TCG GCA TGG CAT CTC CAC-3′ ) and a reverse ( 5′-ACG TCC TCC TTC GGA TGC CC-3′ ) primers . In the second step , the S segment and ribozyme PCR products served as templates for a PCR reaction to obtain cDNA containing S segment sequence in negative orientation flanked by the T7 RNA polymerase promoter and a ribozyme . The primers were a forward primer containing a sequence of a T7 promoter ( 5′-TGC AGG GGG AT ATCG AT Ta ata cga ctc act ata G TCT CAA AGA TAC CGT TGC CGC AC-3′ ) and a reverse primer ( 5′-ATG CCT GCA GGT CGA C ACG TCC TCC TTC GGA TGC CC-3′ ) . The cDNA was cloned into a backbone generated by excising the Ebolavirus minigenome from the p3E5E-Luc between ClaI and SalI restriction sites . Cloning was performed using In-Fusion cloning technology . Four different clones were subjected to DNA sequencing to establish an S segment consensus sequence and to verify successful fusion of the virus segment to the T7 promoter and ribozyme . The consensus sequence was determined to be identical to the one with NCBI accession number NC_005302 . pBabe-βGal and pLenti-eGFP plasmids were described previously [85] , [86] . The dominant negative forms ( DN ) of Rab5A and Rab7A containing S34N and T22N substitutions [18] , [35] , respectively , were cloned into pLenti-eGFP plasmid as fusions to the C-terminus of eGFP , yielding pRab5A-DN and pRab7A-DN . The cloning was performed by Epoch Life Science , Houston , TX . The constitutively active form ( CA ) or Rab5A containing Q79L substitution [19] was reported previously [87] . siRNA duplexes targeting human HRS , Tsg101 , Vps22 , Vps24 , Vps4B , and Alix/AIP1 genes and AllStar non-silencing siRNA were purchased from Qiagen ( Germantown , MD ) . The siRNA sequences are available upon request . SW13 cells grown in 12-well plates were transfected with siRNA duplexes to a final concentration of 5 nM using RNAiMAX transfection reagent ( Life Technologies , Carlsbad , CA ) according to the manufacturer's protocol . Twenty-four h later , the transfection was repeated . Cells were incubated with the transfection mixtures for another 24 h . siRNA-transfected cells were lysed in RIPA buffer ( 50 mM Tris-Cl [pH 7 . 5] , 150 mM NaCl , 1% Triton X-100 , and 0 . 1% SDS ) . The lysates were kept on ice for 15 minutes and then clarified of debris by centrifugation . The lysates were incubated with SDS-PAGE sample buffer at 100°C for 10 minutes , and proteins were resolved on a 4%–20% SDS-PAGE gradient gel ( Bio-Rad Laboratories , Hercules , CA ) . The samples were transferred onto iBlot nitrocellulose membranes ( Life Technologies , Carlsbad , CA ) and blocked for 1 h at room temperature with a blocking buffer ( LI-COR Biosciences , Lincoln , NE ) . The blots were incubated with primary antibodies at 4°C overnight and then with anti-rabbit IRDye 800CW and anti-mouse IRDye 680LT ( LI-COR Biosciences , Lincoln , NE ) for 1 h at room temperature . Protein bands were visualized using Odyssey software ( LI-COR Biosciences , Lincoln , NE ) . BsrT7/5 cells were transfected with 0 . 25 µg of each pT7-mKate2 , pcDNA-N , and pcDNA-L using the Neon transfection system ( Life Technologies , Carlsbad , CA ) according to the manufacturer's protocol . The electroporated cells were plated into wells of 12-well dishes . After 24 h , cells were either infected with CCHFV strain IbAr10200 at multiplicity of infection ( MOI ) of 0 . 1 or left uninfected . Forty-eight h after infection , supernatants were added to SW13 cells at dilution of 1∶10 to assess the minigenome packaging . The SW13 cells were fixed in 10% formalin 24 h after addition of the recombinant virus . Cells nuclei were stained with Hoechst 33342 dye , and analyzed as described above . The number of mKate2-expressing cells infected with the recombinant virus was approximately 4% . To generate CCHFV G pseudotyped VSV encoding the firefly luciferase gene ( VSV-CCHFVG ) , 293FT cells grown in 100-mm dishes were transfected with either 15 µg of pBabe-βGal ( control ) or 5 µg of pC-G and 10 µg of pBabe-βGal using CaCl2 method . After 18 h , media was replaced , and the cells were inoculated with 1 ml of a previously prepared Venezuelan equine encephalitis virus glycoprotein pseudotyped VSV stock ( VSV-VEEVGP ) . After another 6 hours , the supernatants containing the virus inoculum were replaced with fresh media . The pseudotyped virus was collected 48 h after infection . Virus titers were determined in SW13 cells grown in 96-well plates using 5 times dilution . Twenty-four hours later , luciferase activity was measured using Steady-Glo luciferase assay buffer ( Promega , Madison , WI ) according to the supplier's protocol and a GloMax-96 microplate luminometer ( Promega , Madison , WI ) . Neutralization tests were performed by incubating VSV-CCHFVG or VSV-VEEVGP with a rabbit anti-Gc antibody to the antibody dilution of 1∶10 , 1∶50 , or 1∶250 . After incubation at room temperature for 30 min , the pseudotype-antibody mixtures were transferred onto SW13 cells grown in a 96-well plate . The luciferase activity was assessed 24 h later as described above . To test pH dependency of VSV-CCHFVG , SW13 cells grown in a 96-well plate were incubated with DMSO or bafilomycin A dissolved in DMSO to a final concentration of 20 nM . One h later , cells were infected with VSV-CCHFVG , and luciferase activity was measured 24 h later . Generation of VSV pseudotyped with either Ebolavirus glycoprotein GP or Lassa virus glycoprotein GP and encoding the firefly luciferase gene ( VSV-EBOVGP and VSV-LASVGP , respectively ) was described previously [88]–[90] . To test the effect of gene silencing on CCHFV infection , siRNA-treated SW13 cells were collected 24 h after second siRNA transfection . Fifteen thousand cells were plated into wells of the 96-well plate in triplicate to be infected with CCHFV-mKate2 , and the remaining cells were replated to be tested for gene silencing . Twenty-four hours later , virus was added to the cells at 10 times dilution , and the gene expression was verified by immunoblotting as described above . Infected cells were fixed in 10% buffered formalin 24 h later , for 24 h . Cell nuclei were stained with Hoechst 33342 dye ( Life Technologies , Carlsbad , CA ) . Cells were photographed using Nikon Ti-Eclipse microscope running high content analysis software ( Nikon , Tokyo , Japan ) . The numbers of cell nuclei and mKate2-expressing ( infected ) cells were counted using CellProfiler software ( Broad Institute , Boston , MA ) with parameters developed in our laboratory ( available upon request ) . The infection rate was calculated as the ratio of infected cells to cell nuclei . To assess the effect of pharmacological treatment on CCHFV-mKate2 infection , SW13 cells were plated into a 96-well plate at 15 , 000 cells per well . After 24 h , cells were incubated with one of the following: bafilomycin A ( to the final concentration of 10 nM ) , EIPA ( 10 µM ) , dynasore ( 200 µM ) , nystatin ( 100 µM ) , CPZ ( 10 µg/mL ) , or LY294002 ( 75 µM ) . The control was DMSO treatment . All treatments were performed in triplicate . One h later , cells were infected with CCHFV-mKate2 as described above . Cells were fixed with 10% formalin , stained with Hoechst 33342 dye , and analyzed as above . To test the effect of U18666A on virus infection , SW13 cells grown in 8-chamber μ-slides ( ibidi , Munich , Germany ) were treated in duplicate with U18666A to the final concentration of 30 µM or with H2O ( control ) . One hour later , one set of cells was infected with CCHFV for 24 h and then fixed in 10% formalin , permeabilized with 0 . 1% Triton X-100 in PBS for 10 minutes , blocked with 5% goat serum ( Life Technologies , Carlsbad , CA ) in PBS , and stained with CellMask blue dye to define cell boundaries ( Life Technologies , Carlsbad , CA ) , rabbit anti-N antibody to identify infected cells and mouse anti-CD63 antibody at 4°C overnight . The secondary antibodies were Alexa Fluor-conjugated anti-rabbit and anti-mouse antibodies ( Life Technologies , Carlsbad , CA ) . The block of cholesterol transport out of the MVBs in the U18666A-treated cells was confirmed by staining the second set of cells with anti-CD63 antibody followed by an Alexa Flour-conjugated secondary antibody , filipin III ( Thermo Fisher Scientific , Waltham , MA ) , and CellMask red dye ( Life Technologies , Carlsbad , CA ) . Z-stack immunofluorescence imaging was done on 20 cells in each sample . 3D image reconstruction was performed using Imaris software ( Bitplane , Zurich , Switzerland ) after image deconvolution by AutoQuant X3 software ( MediaCybernetics , Rockville , MD ) . The experiment was repeated three times . Numbers of cells and N-positive cells were counted using CellProfiler software . The relative infection efficiencies were calculated by dividing the number of infected cells by the number of the cells in that sample . To test the effect of CA Rab5A on virus infection , SW13 cells transfected with 0 . 1 µg of either pLenti-eGFP or the CA by electroporation were plated into 8-chamber μ-slides . Twenty-four h later , cells were incubated with CCHFV for 24 h , then fixed and stained with the HCS CellMask blue stain to define cell boundaries and a rabbit antibody to N to detect infected cells . Twenty eGFP-expressing cells in each sample were used to determine infection efficiency . The number of cells expressing both eGFP and N in each sample was divided over the total number of eGFP-positive cells in the sample to determine infection efficiency . The experiment was repeated three times . All immunofluorescence experiments were repeated three times . To test the colocalization between CCHFV and early endosomes , MVBs , or late endosomes/lysosomes , SW13 cells grown in 8-chamber μ-slides were incubated with the virus for indicated times at 37°C . Then , the samples were fixed , permeabilized , and stained with antibodies: ( i ) a rabbit antibody to N and a mouse antibody to EEA1 , ( ii ) a rabbit antibody to N and a mouse antibody to CD63 , ( iii ) a mouse antibody to N and a rabbit antibody to PDCD6 ( detecting Alix/Aip1 ) , or ( iv ) a rabbit antibody to N and a mouse antibody to Lamp1 at 4°C overnight . The secondary antibodies were Alexa Fluor-conjugated anti-rabbit and anti-mouse antibodies . Then , the cells were stained with the HCS CellMask blue stain to identify cells . The Z-stack immunofluorescence imaging , 3D reconstruction , and deconvolution were done on 20 cells in each sample as described above . The virion-endosome colocalization was computed using Imaris software . To assess whether the overexpression of the DN Rab5A or DN Rab7A affected the localization of virions to endosomes , SW13 cells transfected with 0 . 1 µg of pLenti-eGFP or a DN by electroporation were plated into wells of 8-chamber slides . After 24 h , cells were incubated with CCHFV for indicated time points . Subsequently , cells were fixed , stained , and analyzed as described above . To test the effect of bafilomycin A on virus internalization , SW13 cells grown in 8-chamber μ-slides were treated with bafilomycin A to a final concentration of 20 nM or with DMSO as a control . One hour later , cells were incubated with either infectious or gamma-irradiated CCHFV . After 24 h , samples were fixed in 10% formalin , permeabilized , and stained with CellMask blue dye to define cell boundaries , anti-N and anti-CD63 antibodies . Immunofluorescence imaging and 3D reconstruction were done on 20 cells in each sample as described above . The percentages of N found in MVBs were computed by Imaris software . To determine whether bafilomycin A treatment affected CCHFV replication , SW13 cells grown in three 35-mm dishes were treated with DMSO in duplicate or bafilomycin A to a final concentration of 20 nM . One h later , all dishes were inoculated with an equal amount of CCHFV . After 2 h , one set of DMSO-treated cells was subjected to RNA extraction using TRIzol reagent ( Life Technologies , Carlsbad , CA ) according to manufacturer's protocol . RNA isolation from the second set of DMSO-treated cells and bafilomycin A-treated cells took place 24 h after virus addition . Five hundred ng of extracted RNA was used to calculate CCHFV genome copies in the samples . Viral RNA levels were determined by a qRT-PCR ( TaqMan ) assay detecting sequences in the S segment of the genome using an ABI 7500 real-time PCR system ( Applied Biosystems , Foster City , CA ) . To obtain a standard curve to determine CCHFV genome equivalents , synthetic CCHFV S segment RNA was generated . pT7-Sseg was linearized with SalI ( New England Biolabs , Ipswich , MA ) and used as a template to synthesize RNA using MEGAscript T7 kit ( Life Technologies , Carlsbad , CA ) according to the manufacturer's protocol . The RNA was purified using RNAzol-Bee reagent ( Tel-Test , Friendswood , TX ) and resuspended in diethyl pyrocarbonate-treated water ( Life Technologies , Carlsbad , CA ) to 2×105 copies per µl . Then , serial 10-fold dilutions of the stock were used to create a linear regression of the standard curve . The CCHFV primer/probe sequences span from nucleotides 1086 to 1216 and were a forward primer ( 5′-CTT TGC CGA TGA TTC TTT CC-3′ ) , a reverse primer ( 5′-GAC TTA GTG TGT CCA GAT CC-3′ ) , and a FAM/TAMRA-labeled primer ( 5′-TTG GGC AGC ATC ATC AGG ATT GGC-3′ ) . The experiment was repeated twice in duplicate . | Crimean-Congo hemorrhagic fever virus ( CCHFV ) is the cause of a severe , often fatal disease in humans . While it has been demonstrated that CCHFV cell entry depends on clathrin-mediated endocytosis , low pH , and early endosomes , the identity of the endosomes where virus penetrates into cell cytoplasm to initiate genome replication is unknown . Here , we showed that CCHFV was transported through early endosomes to multivesicular bodies ( MVBs ) . We also showed that MVBs were likely the last organelle virus encountered before escaping into the cytoplasm . Our work has identified new cellular factors essential for CCHFV entry and potential novel targets for therapeutic intervention against this pathogen . | [
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] | 2014 | Crimean-Congo Hemorrhagic Fever Virus Entry into Host Cells Occurs through the Multivesicular Body and Requires ESCRT Regulators |
DnaA , the replication initiation protein in bacteria , is an AAA+ ATPase that binds and hydrolyzes ATP and exists in a heterogeneous population of ATP-DnaA and ADP-DnaA . DnaA binds cooperatively to the origin of replication and several other chromosomal regions , and functions as a transcription factor at some of these regions . We determined the binding properties of Bacillus subtilis DnaA to genomic DNA in vitro at single nucleotide resolution using in vitro DNA affinity purification and deep sequencing ( IDAP-Seq ) . We used these data to identify 269 binding regions , refine the consensus sequence of the DnaA binding site , and compare the relative affinity of binding regions for ATP-DnaA and ADP-DnaA . Most sites had a slightly higher affinity for ATP-DnaA than ADP-DnaA , but a few had a strong preference for binding ATP-DnaA . Of the 269 sites , only the eight strongest binding ones have been observed to bind DnaA in vivo , suggesting that other cellular factors or the amount of available DnaA in vivo restricts DnaA binding to these additional sites . Conversely , we found several chromosomal regions that were bound by DnaA in vivo but not in vitro , and that the nucleoid-associated protein Rok was required for binding in vivo . Our in vitro characterization of the inherent ability of DnaA to bind the genome at single nucleotide resolution provides a backdrop for interpreting data on in vivo binding and regulation of DnaA , and is an approach that should be adaptable to many other DNA binding proteins .
DnaA is the highly conserved replication initiation protein found in virtually all bacteria [reviewed in 1 , 2–6] . DnaA binds to multiple 9 bp "DnaA boxes" ( DnaA binding sites; consensus sequence 5'-TTATNCACA ) in the origin of chromosomal replication ( oriC ) . Once properly bound to sites in oriC , DnaA causes melting of an AT-rich region and recruitment of the replication machinery . DnaA also binds to DnaA boxes at other chromosomal regions , and in some cases functions as a transcription factor , activating some genes and repressing others . DnaA directly activates transcription of sda [7–11] , and appears to directly repress transcription of ywlC , vpr , and the yyzF-yydD , trmE-noc , and ywcI-sacT operons [8 , 9 , 12 , 13] . DnaA is a AAA+ ATPase that is present in cells as both ATP-DnaA and ADP-DnaA . Although both ATP-DnaA and ADP-DnaA bind DNA , where analyzed , ATP-DnaA is required for replication initiation [3 , 14–19] . For E . coli DnaA , there are some sites that appear to bind ATP-DnaA and ADP-DnaA equally well , and others that have a preference for ATP-DnaA [reviewed in 3] . The activity of E . coli DnaA is largely controlled by regulation of its ATPase activity and nucleotide exchange [reviewed in 1 , 3 , 20 , 21] . In contrast , the activity of Bacillus subtilis DnaA appears to be largely regulated by several proteins , all of which affect its ability to bind cooperatively to DNA [22–24] . We set out to analyze the binding properties of B . subtilis DnaA to target chromosomal sites , on a genomic scale , in vitro , in the absence of other proteins . We used in vitro DNA affinity purification and sequencing ( IDAP-Seq ) , an approach that is an in vitro analog of chromatin immunoprecipitation or affinity purification followed by deep sequencing , ChIP-Seq or ChAP-Seq , respectively . In IDAP-Seq , purified his-tagged protein ( DnaA-his ) is mixed with genomic DNA , the DNA bound to protein is isolated by affinity purification , and the bound DNA is analyzed by high throughput DNA sequencing . This approach has been used to analyze DNA binding by the transcriptional regulator CodY [25–27] . Using IDAP-Seq , we defined individual DnaA binding sites throughout the genome , and compared their affinity for ATP-DnaA and ADP-DnaA over a range of DnaA concentrations . We generated a position specific scoring matrix ( PSSM ) that can be used to predict DnaA binding sites with improved accuracy compared to a simple consensus sequence . The vast majority of sites bound in vitro have not been observed in vivo , suggesting that the amount of DnaA in vivo is limiting , or that other factors prevent binding at these sites under normal growth conditions . Conversely , we found some sites that were bound by DnaA in vivo , but that were not bound in vitro , indicating that at least one additional factor was involved in binding in vivo . We found that the nucleoid associated protein Rok was required for DnaA to bind to these chromosomal regions in vivo . Our results demonstrate that IDAP-Seq data can be used to understand and compare inherent binding properties of different forms of a given protein under defined in vitro conditions . In addition , comparison of IDAP-Seq data with data from in vivo analyses can provide insights into binding regions that require additional factors in vivo .
The overall goal of our experiments was to identify all regions in the B . subtilis genome capable of binding DnaA , and to compare the binding properties of ATP-DnaA and ADP-DnaA to these regions to gain a better understanding of how DnaA binding is regulated . We incubated various concentrations of purified functional C-terminal hexa-histidine tagged DnaA ( DnaA-his ) with either ATP or ADP , and mixed each nucleotide-bound form of DnaA-his with purified sheared genomic DNA from B . subtilis . The ATPase activity of DnaA was very low under these conditions , hydrolyzing 2 . 2 ± 0 . 6 moles of ATP per mole of DnaA per hr ( n = 6 ) . This rate of hydrolysis would cause a small ( ≤0 . 2% ) decrease in the concentration of ATP over the course of the incubations . Given the rapid rate of exchange between ATP and ADP [23] , we expect that after addition of ATP most of the DnaA will be in the ATP-bound form . Genomic DNA with a uniform copy number along the chromosome and nearly random shearing pattern was used in these experiments , facilitating quantitative analysis of the data ( see S1 Text ) . We isolated DnaA-his along with any bound DNA fragments , without crosslinking , using affinity resin for the hexa-histidine tag . We analyzed binding over a range of DnaA concentrations to compare binding at different chromosomal regions and to estimate apparent binding constants . The identity and amounts of genomic regions bound by DnaA were determined by deep sequencing ( IDAP-Seq ) . Using IDAP-seq , we identified the chromosomal regions that had increased binding by DnaA within the range of 55 nM to 4 . 1 μM DnaA . We found that the number of chromosomal regions bound and the amount of binding to individual regions increased with increasing concentrations of ATP-DnaA-his ( Fig 1 ) . There were no specific chromosomal regions recovered in control reactions with no added DnaA , as assessed by the distribution of sequencing reads over the genome ( Fig 1A ) . In contrast , there were eight chromosomal regions predominantly associated with 55 nM ATP-DnaA-his following affinity purification ( Fig 1B ) . These regions were the same as the major DnaA binding regions previously defined in vivo [8 , 9 , 12 , 13 , 28] . They have a greater number of DnaA boxes than the other regions detected in vitro that required higher concentrations of DnaA for binding . As the concentration of ATP-DnaA-his was increased ( 55 nM; 140 nM; 550 nM; 1 . 4 μM; 4 . 1 μM ) , binding to the eight predominant regions increased and appeared to become saturated ( Fig 1B–1F and S1 Fig , panels 1–8 ) . In addition , binding to many other regions was detected and increased with increasing concentrations of ATP-DnaA-his . Confirmation that binding was mediated by the DnaA-binding domain of DnaA was obtained for six of the regions , spanning a wide range of affinities , by performing a parallel assay with a mutant DnaA ( DnaA∆C-his ) that is missing the DNA binding domain ( S2 Fig ) . We identified 269 chromosomal regions that were bound by 1 . 4 μM ATP-DnaA-his ( S1 Fig and S1 Table ) . This list includes all the regions that were bound at lower concentrations of DnaA , and also those that had increased binding at 4 . 1 μM DnaA . There was an approximately 300-fold difference in the amount of DNA detected from the weakest bound regions compared to the strongest sites at 1 . 4 μM ATP-DnaA-his , the second highest DnaA concentration tested . There were many additional regions bound at 4 . 1 μM ATP-DnaA-his , the highest concentration tested , that were not detected at the lower concentrations ( Fig 1F ) . Because the amount of binding at these regions was low and was not detected at other concentrations of DnaA , they were not included in the list of binding regions ( S1 Table ) . The number of binding regions ( 269 ) determined in vitro is significantly greater than the previously known binding regions ( eight ) determined in vivo . Because several different analyses of in vivo binding did not detect these additional regions [8 , 9 , 12 , 13 , 28] , it seems unlikely that all , or even most , of these 269 regions are occupied by DnaA in vivo . The much larger number of regions bound by DnaA in vitro could be due to a combination factors , including the much higher sensitivity of the in vitro system , the possibility that the amount of DnaA in vivo is limiting , and the fact that DnaA binding is regulated in vivo . We used the IDAP-Seq data to visualize binding by DnaA at single nucleotide resolution ( Figs 2 and 3 and S1 ) . In these analyses , the number of sequence reads starting at a specific nucleotide position was determined , and the reads were extended and summed to generate a curve indicative of total binding . If a specific DNA sequence is required for binding , then no sequence reads should start in that region . At 1 . 4 μM ATP-DnaA-his , the binding patterns for the strongest binding regions with multiple DnaA boxes were complex ( Fig 2A–2H ) , often having plateaus and multiple peaks of read start sites . In contrast , other regions with fewer DnaA boxes typically had a single , well-defined peak on each strand ( Figs 2I–2L and 3A–3D ) . Analyses and visualization of the binding regions at single nucleotide resolution provided insights into the requirements and contributions of individual DnaA boxes . A characteristic almost symmetric pattern of sequence reads beginning on either side of an otherwise "bare" region was indicative of a simple binding region containing a single DnaA box ( Fig 3A and 3B ) . This footprint-like region defines the binding site and can be used to determine binding sites for uncharacterized proteins . Similarly , a larger bare region flanked by sequence reads on opposite strands was indicative of two binding sites , both of which appear to be required for DnaA to bind the region ( Fig 3C and 3D ) . In more complex regions ( e . g . , Fig 3E ) , some DnaA boxes ( numbered 1 and 2 ) appeared to make partial contributions to binding , as evidenced by an abrupt decrease in , but not a complete elimination of , reads at the junctions of the DnaA boxes . In contrast , DnaA boxes 3 and 4 appeared to be required for binding , since no sequence reads started in or between them . The strongest binding regions contain arrays of DnaA boxes , and had complex binding patterns ( Fig 2A–2H and 3F and 3G ) . In addition to DNA fragments that contained the complete array of DnaA boxes , fragments were also efficiently recovered that had one end within the array and therefore contained only a subset of the DnaA boxes . The requirement for specific DnaA boxes varied with the DnaA concentration . For example , in the sda promoter region , DnaA boxes 4 , 5 , 6 , and 7 ( Fig 3F ) were required for binding at the lowest concentration ( 55 nM ) of ATP-DnaA-his tested . However , at the highest ATP-DnaA-his concentration ( 4 . 1 μM ) , fragments were efficiently recovered as long as they contained either DnaA boxes 1 and 2 or DnaA boxes 6 and 7 ( Fig 3G ) . The finding that DnaA boxes 1 and 2 contribute to binding is consistent with in vivo results showing that these sites are important for full activation of transcription of sda by DnaA , and that a mutation in either of these individual DnaA boxes causes a reduction in sda expression [7] . The single nucleotide resolution afforded by IDAP-seq is somewhat reminiscent of the resolution obtained with DNA footprinting . Published footprinting data for DnaA binding to B . subtilis DNA is available for two sites: the dnaA promoter region , and the region upstream of the DUE [30] . About half of the DnaA boxes observed by footprinting of these regions were directly supported by our IDAP-seq data . For the remaining footprinted sites , it was not possible to determine whether or not they were bound in our assay . This is because the IDAP-seq method is more analogous to a single nucleotide truncation analysis than footprinting , and in regions that contain arrays of DnaA boxes ( including the dnaA promoter and the DUE ) , removal of one DnaA box from the end will not always give a robust change in DNA recovery if its contribution is small compared the remaining DnaA boxes . We used a subset of the binding data to establish a position-specific scoring matrix ( PSSM ) that predicted DnaA binding sites more effectively than a simple consensus sequence . When we searched for potential DnaA binding sites based on the consensus sequence 5'-TTATNCACA-3' [31] we found that restricting the search to one mismatch was overly stringent , whereas allowing two mismatches from the consensus resulted in an excessive number of predicted DnaA boxes throughout the genome . A PSSM was developed to more accurately predict the binding sites observed in our experiments . We derived a PSSM from 150 DnaA box sequences ( S2 Table ) that were observed to bind DnaA in our IDAP-Seq data . Whereas the PSSM ( Fig 4A and S3 Table ) was consistent with the previously determined consensus sequence , it provided a more sensitive measure of the extent to which mismatches are tolerated at each position . We predicted a total of 11 , 353 DnaA boxes over the whole genome using the PSSM , and in general these putative DnaA boxes were more closely correlated with binding than boxes predicted using the consensus sequence with up to two mismatches ( e . g . , Fig 4B–4E ) . In many instances , the PSSM identified functional DnaA boxes that had three mismatches from the consensus ( asterisks in Fig 4D and 4E ) . In contrast , using the consensus sequence and allowing three mismatches predicted one DnaA box every 17 bp of genomic sequence . The vast majority of the 269 regions bound by ATP-DnaA-his contained at least one DnaA box centered at the peak summit or two DnaA boxes flanking the peak summit ( S1 Fig and S4 Table ) . A total of 784 predicted DnaA boxes were found within 150 bp of the summits of these 269 binding regions . A Pearson’s correlation coefficient of 0 . 74 was observed between the amount of binding observed at each region and how well the DnaA boxes in that region matched the PSSM ( S4 Fig ) . Many additional predicted DnaA boxes were bound at 4 . 1 μM ATP-DnaA-his , and others might require yet higher DnaA concentrations to bind . In addition , there are almost certainly some predicted DnaA boxes that are not functional , either because of limitations in the PSSM itself , or due to that fact that the PSSM approach does not take into consideration other factors that could influence binding , including flanking sequences and the number , orientation , and spacing of nearby DnaA boxes . We used the IDAP-Seq data to estimate apparent dissociation constants for several of the 269 regions bound at 1 . 4 μM ATP-DnaA-his . We plotted the amount of DNA recovered as a function of ATP-DnaA-his concentration for each of the 269 binding regions ( Figs 5 and S1 ) . For each region the nucleotide position with the maximum amount of DNA ( peak summit ) was identified , and the relative number of DNA fragments that spanned that position was determined at each DnaA concentration ( Materials and Methods; S3 Fig ) . Genomic DNA ( ~300 μM of base pairs ) was used in the binding reactions , providing an excess of non-specific DNA for competition in binding to DnaA . For regions with high affinity , the amount of DNA recovered became saturated as the ATP-DnaA-his concentration was increased ( Fig 5A–5H ) . For regions with intermediate affinity , the amount of DNA recovered appeared to begin to saturate at the highest concentration of ATP-DnaA-his ( Fig 5I and 5J ) . For the remaining regions , the amount of DNA recovered increased with the concentration of ATP-DnaA-his , but did not reach saturation ( e . g . , Fig 5K and 5L ) . Evaluating relative binding for the weaker binding regions can be done by comparing the relative amount of DNA recovered at 1 . 4 or 4 . 1 μM DnaA ( S1 Table ) . DnaA binding to almost all regions was cooperative , consistent with the positive cooperative binding previously observed for B . subtilis DnaA [22–24 , 30] . The apparent binding constants determined by IDAP-seq for the eight high affinity binding sites ranged from 0 . 13–0 . 33 μM ( Table 1 , S1 Table ) , and were several-fold greater than those determined previously by gel mobility shift assays [22 , 23] . Although IDAP-seq measurements have inherently higher error owing to the complex experimental protocol , the higher Kd’s can be attributed , in large part , to washing the bound complexes in the IDAP experiments and the absence of caging effects from gel electrophoresis . In gel mobility shift assays , the complexes are loaded directly on a gel , where caging effects of the gel matrix stabilize binding . Other factors , including the heterogeneous nature of the DNA template for binding , the presence of multiple binding regions with similar affinities , and the excess of competitor DNA in the IDAP-Seq experiments , likely also contribute to the higher apparent Kd’s determined with IDAP-Seq compared to those determined by gel shift assays . These differences between IDAP-Seq and gel mobility shift assays likely also affect estimates of cooperativity . We found that the overall binding patterns for ADP-DnaA-his ( S5 Fig ) were similar to those for ATP-DnaA-his ( Fig 1 ) . At the lowest concentration of DnaA tested , the prominent binding regions were the same eight regions that were bound by ATP-DnaA-his , and the number of bound regions increased at higher concentrations of ADP-DnaA-his ( S5 Fig ) . The amount of binding to any specific region at a given concentration of DnaA was almost always greater with ATP-DnaA-his than with ADP-DnaA-his . This is seen by comparing the ratio of binding ( amount of DNA recovered ) by ATP-DnaA-his to that by ADP-DnaA-his ( Fig 6A ) . Two regions ( the yydA promoter region and the region in oriC between dnaA and dnaN ) appeared to have a small preference for ADP-DnaA-his over ATP-DnaA-his , but only at 1 . 4 μM DnaA ( Fig 6A and 6G ) . A few regions had a strong preference for ATP-DnaA-his ( Fig 6A ) . Among the eight high affinity regions , the most dramatic differences between ATP-DnaA-his and ADP-DnaA-his were observed in the sda promoter region and the region between the 3’ ends of gcp and ydiF ( Fig 6A and 6B and 6C ) . Approximately 50-fold more DNA from the sda promoter region was recovered with 55 nM ATP-DnaA-his than with 55 nM ADP-DnaA-his . For the region between gcp and ydiF , this difference was 16-fold . The differences between ATP- and ADP-DnaA-his diminished at higher DnaA concentrations as binding became saturated . Large differences between binding by ATP-DnaA-his and ADP-DnaA-his were also observed for weaker binding regions . For example , there was detectable binding to yhcN by ATP-DnaA-his at a concentration of 140 nM , whereas binding by ADP-DnaA-his was not detected until 550 nM ( Fig 6A and 6D ) . At 550 nM DnaA , there was 73-fold more yhcN DNA bound to ATP-DnaA-his compared to ADP-DnaA-his . Similarly , there was 24-fold more yhdF bound to 550 nM ATP-DnaA-his compared to ADP-DnaA-his ( Fig 6A and 6E ) . Although we cannot be certain that homogeneous DnaA-ATP or DnaA-ADP was present in the respective reactions , if heterogeneity did exist , it would cause an underestimate of the differences between DnaA-ATP and DnaA-ADP . The basis for some DnaA sites exhibiting much higher affinity for ATP-DnaA than ADP-DnaA is almost certainly due to a combination of factors , including the sequence , orientation and spacing of the DnaA boxes , and the sequences flanking the DnaA boxes . There are not enough regions to define the features that contribute to the large differences . Our in vitro data on DnaA binding provides a framework for interpreting in vivo DnaA ChIP results , and vice versa . We anticipated three general types of findings when comparing in vitro to in vivo binding by DnaA: 1 ) binding is detected both in vitro and in vivo; 2 ) binding is detected in vitro but not in vivo; and 3 ) binding is detected in vivo , but is not detected in vitro . Of the 269 binding regions identified in vitro at 1 . 4 μM ATP-DnaA-his , only the eight strongest binding regions have been readily detected in vivo [8 , 9 , 12 , 13] . The next strongest binding regions in vitro were within the open reading frames of codV ( encoding a homologue of the tyrosine recombinase XerC ) , and rplB ( encoding ribosomal protein L2 ) ( Table 1 ) . We estimated that the in vivo concentration of DnaA is ~1–2 . 5 μM in cells growing exponentially in minimal glucose medium at 30°C . The amount of binding at rplB in vitro at the 1 . 4 and 4 . 1 μM ATP-DnaA-his concentrations is 28–46% that observed for the eight sites that are readily observed in vivo . If no other factors affect binding , then this indicates that DnaA could bind rplB in a significant fraction of cells . Instead we found no detectable DnaA binding to rplB in vivo using ChIP-PCR . We suspect that there are factors in vivo that prevent DnaA from binding to the site within rplB . For example , since the binding site is within the rplB open reading frame , it is possible that transcription prevents stable association of DnaA with the site . Alternatively , the concentration of available DnaA might be limited by titration due to efficient binding at other regions [e . g . , 40] . It is also possible that there is some binding in vivo , but that it is below the limit of detection of the ChIP-PCR assay , or that binding occurs under biological conditions that we have not assayed . We used ChIP-PCR to measure DnaA binding in vivo at four regions that we observed to bind DnaA in preliminary in vivo ChIP-seq experiments . These regions had not been identified in previously reported in vivo ChIP experiments with DnaA [8 , 9 , 12 , 13] , perhaps due to lower sensitivity of the detection methods . These are all intergenic regions ( between: ywiB-sboA , yuzB-yutJ , yjcM-yjcN , and icsS-braB ) and contain promoters in one or both directions [41] . We found that DnaA was consistently associated with these regions in ChIP-PCR experiments ( n = 6; Table 2 ) , with mean fold enrichment values ranging from 4 . 5 ( iscS ) to 12 . 8 ( sboA ) , compared to 83-fold for the dnaA promoter , a control site that is readily detected in vivo [8 , 9 , 12 , 13 , 28] . Interestingly , none of these four regions bound DnaA in vitro in our IDAP-seq experiments , even at the highest concentration of DnaA tested . Furthermore , only the sboA region has a recognizable DnaA box near the in vivo binding site . The simple interpretation of these results is that there is a factor needed for binding in vivo that is not present in the purified in vitro binding reactions . Because three of these four regions bound by DnaA in vivo but not in vitro were previously found to be bound in vivo by the nucleoid-associated protein Rok [42] , we tested whether Rok might be required for DnaA binding at these regions in vivo . In a rok null mutant , there was much less association of DnaA with these regions compared to wild type cells ( Table 2 ) . DnaA protein levels are not substantially different in rok null mutant cells ( S6 Fig ) , indicating that the loss of binding was not due to a decreased amount of DnaA . Consistent with this , binding at the dnaA promoter , which has 12 DnaA boxes and binds DnaA robustly in vitro , was not significantly different between wild type and rok mutant cells ( Table 2 ) . These results indicate that Rok is required for association of DnaA with these chromosomal regions in vivo . The IDAP-Seq approach used here to study DNA binding by DnaA should be a useful for determining the inherent binding properties of many different proteins , and the effects of various ligands , such as the ATP and ADP comparison presented here . It should also be possible to determine the effects of mutations , phosphorylation , acetylation , and other modifications on DNA binding . The effects of regulatory proteins that modulate binding could also be evaluated , provided the two proteins do not have the same tag . In all cases , apparent binding constants can be determined and compared for sites throughout the entire genome . Experiments to date with DnaA and CodY [25–27] used a his-tagged version of the DNA binding protein , with DNA-protein complexes recovered by metal affinity chromatography . Other tags could potentially be used for purification of complexes . In preliminary experiments , we found that filter binding , which does not require a tag , can also be used to recover DNA-protein complexes . Antibodies could also be used to recover DNA-protein complexes with or without a tag . Our experiments were performed without crosslinking , but for weaker binding proteins , where initially bound fragments might be lost in wash steps , crosslinking protein to DNA could be used in a more standard ChIP-type experiment , either with immunoprecipitation , affinity purification , or filter binding of crosslinked protein-DNA complexes . Comparing in vitro studies of genomic binding using the IDAP-Seq method with more traditional in vivo ChIP experiments should provide valuable clues about how the activities of DNA binding proteins are modulated in cells .
B . subtilis DnaA with the amino acids AAALEHHHHHH added to the C-terminus of DnaA was purified from E . coli ( S1 Text ) . Final DnaA-his preparations were typically 98% pure . A similarly his-tagged DnaA ( with 12 instead of six histidines ) is functional in vivo [9] . Binding reactions ( in 250 μl ) were done with DnaA-his ( at concentrations of 0 , 55 nM , 140 nM , 550 nM , 1 . 4 μM , and 4 . 1 μM ) and sheared genomic DNA ( 0 . 2 mg/ml ) in 40 mM HEPES-KOH , pH 7 . 6 , 150 mM potassium glutamate , 2 . 5 mM ATP or ADP , 10 mM magnesium acetate , 0 . 2 mM DTT , 50 μg/ml BSA , 0 . 1 mM EDTA , 20% glycerol , and 4% sucrose for 30 min at room temperature . Genomic DNA was purified from a dnaBts mutant [29 , 43 , 44] . DnaA-his was bound with nucleotide by preincubating in storage buffer with 2 . 5 mM ATP or ADP on ice for two hours immediately before using in binding reactions , as described previously [23] . Each reaction was mixed with 100 μl Talon Co+ resin ( Clontech ) pre-equilibrated with equilibration/wash buffer ( 40 mM HEPES-KOH , pH 7 . 6 , 150 mM potassium glutamate , 2 . 5 mM ATP or ADP , 10 mM magnesium acetate , 50 μg/ml BSA , 20% glycerol ) and rotated for 30 min at room temperature . Each mixture was transferred to a Poly-Prep column ( Bio-Rad , Hercules , CA ) , and washed three times with 1 ml equilibration/wash buffer , with care taken to ensure that all washes were done under virtually identical conditions . Complexes of DnaA-his bound to DNA were eluted by adding 0 . 5 ml ChIP elution buffer ( 50 mM Tris-HCl , pH 8 . 0 , 10 mM EDTA , 1% SDS ) , capping the bottoms and covering the tops of the columns tightly with foil , and incubating at 65°C for 15 min . The eluate was collected , and the resin was washed twice with 200 μl ChIP elution buffer to recover all of the eluted DNA . The recovered DNA was purified using a QiaQuick PCR purification kit ( Qiagen ) . Sample preparation , including incorporation of a 3’ barcode , selection of 200–400 bp fragments ( after addition of adaptors and amplification ) , and single read sequencing ( 40 nt ) on an Illumina HiSeq were performed by the MIT BioMicro Center . Alignment of DNA fragments bound by DnaA-his to the genome of AG1839 ( a . k . a . , KPL69; GenBank accession number CP008698 ) [29] was performed using Bowtie [45] , with adjustments to compensate for the fact that the chromosome is circular . Peak calling on the 1 . 4 μM and 4 . 1 μM ATP-DnaA-his data was done using cisGenome v . 2 . 0 [46] , and in some cases PeakSplitter [47] , and visualized in the genome browser MochiView [48] for manual refinement ( see S1 Text for details ) . The genome position of the summit of each peak was determined using data from the 4 . 1 μM ATP-DnaA-his binding reaction , because the peaks ( especially the weaker ones ) were better defined at this DnaA concentration . Seq data are available at NCBI under accession SRX648534 . To determine the amount of DNA bound by DnaA-his for each chromosomal region , we determined the number of sequence reads across that region . Each sequence read ( mapped to the chromosome using Bowtie ) was computationally extended by the estimated average fragment length of 250 base pairs ( presented schematically in S3A and S3B Fig ) . The relative coverage at each bp along the chromosome was obtained by summing the number of fragments on both the positive and negative strands that are inferred to span that position ( S3C Fig ) . Custom R scripts were used for these steps . The resulting coverage map allowed different regions along the chromosome to be compared for any given sample . To compare individual loci under a variety of binding conditions ( e . g . , ATP v . ADP , or at different concentrations of DnaA ) , we normalized the number of sequence reads ( coverage map amplitudes ) to the total amount of DNA recovered in each reaction ( S1 Text , S3D–S3G Fig ) . The amount of DNA that was recovered in each sample increased with increasing amounts DnaA ( S3F Fig ) , due to 1 ) increases in background binding , 2 ) increases in binding at regions that have not yet reached saturation , and 3 ) binding at new weaker binding regions . Measurements of the maximum binding following normalization vs . DNA concentration gave data that could be fit to a binding curve ( S3H Fig ) . Apparent Kd’s were determined using Prism5 ( GraphPad Software ) . Data were fit to the equation y = ( Bmax ) ( xn ) / ( Kdn + xn ) , where Bmax is maximum binding , x is the DnaA-his concentration , y was the amount of binding observed , and n is the Hill constant . For each binding region , the position of the peak was determined in the 4 . 1 μM DnaA dataset , and the peak height at the same position was determined for the lower DnaA concentrations and used as the amount of binding . For binding regions that approached saturation , Bmax was fitted from the binding data . For several binding regions , Bmax could be determined for ATP- but not ADP-DnaA-his binding . In these cases , the Bmax determined for ATP-DnaA-his was used to fit the ADP-DnaA-his data . In all other instances , Bmax of 0 . 8 was used to determine an apparent Kd . DnaA boxes in the B . subtilis genome were annotated using the PSSM generated as part of this study ( S1 Text ) . This PSSM was used to search the genome sequence of AG1839 genome using RSAT [49] with a p-value cutoff of ≤ 0 . 0015 . Where overlapping DnaA boxes were detected , the one with the higher p-value was discarded . This collection of DnaA boxes was used in all figures and tables . A “DnaA Box Score” for the binding regions was calculated by summing the negative log of the P-value from the PSSM for each binding region . DnaA binding to specific chromosomal regions in vivo was determined by ChIP followed by quantitative PCR ( ChIP-PCR ) . Wild type ( AG174; genotype: trp , phe ) and rok null mutant {HM57; genotype: trp , phe , rok::pDG641rok ( mls ) } cells were grown at 37°C in LB medium . ( The rok null mutation is an integration of plasmid pDG641rok into rok by single crossover , disrupting the rok open reading frame . ) Cells in mid-exponential phase were treated with 1% formaldehyde for 20 min to crosslink protein and DNA . Crosslinking was quenched by adding glycine ( 0 . 22 M ) . Preparation of lysates and immunoprecipitations were done essentially as describe previously [50] . DnaA was immunoprecipitated with rabbit polyclonal antiserum and the DNA was recovered using a QiaQuick PCR purification kit ( Qiagen ) . Quantitative PCR was performed on a Roche LightCycler 480 , with reduced annealing ( 48°C ) , extension ( 68°C ) , and acquisition ( 63°C ) temperatures to compensate for the low melting temperatures of many of the loci being examined . Fold-enrichments were calculated as described in [51] , using nicK , a region in ICEBs1 [52] that does not bind DnaA , for normalization . The primer pairs used are listed in S5 Table . | DNA binding proteins are involved in many cellular processes . The ability of these proteins to bind DNA is often modulated , either directly or indirectly . We determined the binding properties of Bacillus subtilis DnaA to genomic DNA at single nucleotide resolution using in vitro DNA affinity purification and deep sequencing . DnaA is the replication initiator and transcription factor and a AAA+ ATPase found in virtually all bacteria . Like other AAA+ proteins , DnaA binds ATP or ADP , and the identity of the nucleotide influences protein activity . We found that most DNA binding regions had a slightly higher affinity for ATP-DnaA than ADP-DnaA , but that a few regions had a strong preference for binding ATP-DnaA . Although some chromosomal regions were bound by DnaA both in vitro and in vivo , we observed many differences . Notably , we found regions that were bound in vivo that were not detectably bound in vitro . Binding to these regions in vivo required the nucleoid associated protein Rok . Our findings highlight the importance of other factors in the cell that modify association of DnaA with specific chromosomal regions . The general approach , to date used with only a couple of proteins , should be readily adaptable to many other DNA binding proteins . | [
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] | [] | 2015 | In Vitro Whole Genome DNA Binding Analysis of the Bacterial Replication Initiator and Transcription Factor DnaA |
Although extensively studied , the structure , cellular origin and assembly mechanism of internal membranes during viral infection remain unclear . By combining diverse imaging techniques , including the novel Scanning-Transmission Electron Microscopy tomography , we elucidate the structural stages of membrane biogenesis during the assembly of the giant DNA virus Mimivirus . We show that this elaborate multistage process occurs at a well-defined zone localized at the periphery of large viral factories that are generated in the host cytoplasm . Membrane biogenesis is initiated by fusion of multiple vesicles , ∼70 nm in diameter , that apparently derive from the host ER network and enable continuous supply of lipid components to the membrane-assembly zone . The resulting multivesicular bodies subsequently rupture to form large open single-layered membrane sheets from which viral membranes are generated . Membrane generation is accompanied by the assembly of icosahedral viral capsids in a process involving the hypothetical major capsid protein L425 that acts as a scaffolding protein . The assembly model proposed here reveals how multiple Mimivirus progeny can be continuously and efficiently generated and underscores the similarity between the infection cycles of Mimivirus and Vaccinia virus . Moreover , the membrane biogenesis process indicated by our findings provides new insights into the pathways that might mediate assembly of internal viral membranes in general .
Nucleocytoplasmic large DNA viruses ( NCLDVs ) , which include Poxviridae , Phycodnaviridae , Iridoviridae , Asfarviridae and Mimiviridae [1] , replicate and assemble in cytoplasmic inclusions called viral factories . Formation of these elaborate structures that enable spatial and temporal coordination of viral assembly and effective recruitment of host factors , involves massive rearrangement of host cytoskeleton and membranes [2]–[5] . A critical process occurring in these factories is the assembly of inner viral membranes that are present in all NCLDVs . The origin of these membranes , their assembly as well as their number within NCLDV virions remain poorly understood . Early electron microscopy studies of Vaccinia virus , the prototype of Poxviridae , revealed that the immature Vaccinia form ( IV ) carries a single membrane layer [6] , [7] . A single membrane envelope is commonly acquired by viral budding into intracellular compartments or through plasma membranes . Since such processes were not observed during the assembly of IV particles , and as the initial viral membrane structures , dubbed crescents , did not demonstrate a continuity with host membranes , it was proposed that such crescents are generated by a de novo synthesis from lipid precursors and have open ends in the cytoplasm [6] . However , the notion of open membrane sheets that expand through de novo synthesis is at odds with the common wisdom that membranes are exclusively derived from pre-existing organelles [8] , and that open membrane edges are inherently unstable [9] . Subsequent structural studies motivated by this conundrum implied that crescents and IV spheres represent closed structures composed of two tightly apposed bilayers generated through wrapping of collapsed endoplasmic cisternae [8] , [10] , [11] . The idea that crescents originate from the endoplasmic reticulum ( ER ) was supported by the finding of an operative pathway from the ER to nascent viral membranes [12] , [13] . However , the two-membrane model was challenged by freeze-fracture electron microscopy studies , which demonstrated that IV membrane consists of a single bilayer stabilized by a protein coat [9] , [14] . Research on the membrane origin and structure in the African swine fever virus ( ASFV ) proceeded along a similar course . While initial studies indicated that ASFV virions contain a single membrane layer [15] , ensuing observations implied that this NCLDV member contains two internal membranes generated by wrapping of the viral core by collapsed ER cisternae [16]–[18] . Yet , recent investigation revealed that ASFV carries a single lipid bilayer [19] . Notably , another NCLDV member , the phycodnavirus PBCV-1 , was also reported to carry a single internal membrane bilayer [20] , [21] . If indeed a single membrane bilayer exists , it highlights the uncertainty concerning the pathway by which it is formed [5] , [22] , [23] . Intrigued by this ambiguity , we set to investigate the mode of membrane generation during the infection cycle of the amoeba-infecting NCLDV Mimivirus [24] , [25] . With a 1 . 2 Mbp dsDNA genome and a particle size of ∼750 nm , the Mimivirus and its relative Megavirus [26] , represent the largest viruses documented so far . Mimivirus is composed of a genome encapsulated by a protein core that is surrounded by membrane bilayers [27] , which underlie an icosahedral capsid . The capsid is , in turn , covered by closely packed 120 nm-long fibers that form a dense matrix [27]–[29] . The large size of the Mimivirus membrane layers , along with the fact that almost 1000 virus progeny are generated within each infected cell during a relatively short ( 12–14 hours ) infection cycle [24] , highlight questions concerning the source of lipid components required for the viral membranes as well as the mechanisms responsible for a precise and rapid assembly of these membranes . To investigate membrane assembly during Mimivirus infection , we used fluorescence microscopy , immunolabeling , freeze-fracture cryo-Scanning Electron Microscopy and Scanning-Transmission Electron Microscopy ( STEM ) tomography of cryo-preserved samples . STEM tomography is a novel technique that provides higher contrast than conventional electron tomography and enables data acquisition from thicker ( >250 nm ) samples [30] . Our studies reveal that at late stages of Mimivirus infection , ER-like cisternae are recruited to the periphery of the viral factory . Numerous vesicles that appear to bud out from these cisternae fuse into multivesicular structures that eventually rupture to generate open , single-membrane sheets reminiscent of those detected during Vaccinia assembly [31] . An angular vertex is subsequently assembled , leading to the formation of icosahedral capsids . These observations elucidate the process by which generation of multiple Mimivirus progeny can proceed continuously and efficiently . Moreover , our findings imply that this pathway may represent a common mechanism for the assembly of inner viral membranes as well as for the formation of membrane structures during fundamental cellular processes .
Since our studies of membrane biogenesis during Mimivirus infection were carried out using mainly STEM tomography , we analyzed the structure of mature intracellular Mimivirus virions using the same technique in order to enable direct comparison ( Fig . 1A–C; Movie S1 ) . Our observations corroborate results derived from single-particle analyses [27] by revealing the presence of two layers that surround the core wall ( layers 3 and 4 in Fig . 1B , C ) . However , our results are inconsistent with the notion that the outer layer ( layer 4 ) represents a membrane , as discussed below . We have previously shown that shortly following Mimivirus infection , replication of viral genomes that are released into the host cytoplasm , is initiated , leading to the formation of replication centers whose number per host cell correlates with the multiplicity of infection [32] . At ∼6 hours post infection ( PI ) , replication centers coalesce into a single viral factory in which Mimivirus progeny are generated . Fluorescence microscopy and TEM indicate a burst-like capsid formation at the periphery of the factory at 8 hours PI ( Fig . 1D–F ) . Previous studies [33] implied that the factory core is surrounded by a membrane assembly site ( Fig . 1G ) . This conjecture is corroborated by our STEM tomography studies , which demonstrate that this region consists of a highly elaborate membrane network , including multiple vesicles and membrane sheets ( Fig . 1H , I; Movie S2 ) . Our TEM sample preparation involves high-pressure-freezing followed by freeze substitution with acetone ( see Materials and Methods ) , a technique shown to be the method of choice for the preservation and resolution of membrane structures in studies of ASFV and Vaccinia infection cycles [19] , [31] . However , since this method involves exposure to organic solvents , we sought to further ascertain that membrane structures are accurately preserved . We thus used cryo-scanning electron microscopy to inspect membrane assembly zones in specimens prepared by freeze-fracture , a method that preserves samples in their native state as no organic solvents or chemical fixatives are used ( see Materials and Methods ) . Membrane structures detected by this technique , including sheets associated with assembling capsids and vesicles , were similar to those observed in samples prepared by high-pressure-freezing followed by freeze substitution ( Fig . S1 ) , thus validating our TEM studies . As indicated above , fluorescence and TEM studies reveal the presence of fully assembled icosahedral capsids at the periphery of viral factories at ∼8 hours PI . To obtain insights into earlier stages of capsid generation , STEM tomography analyses were conducted on thick ( 280–320 nm ) sections of infected cells at 7 . 5 hours PI . These analyses revealed membrane cisternae localized at close proximity to the factories ( Fig . 2A–D; Movies S3 , S4 ) . Notably , the cisternae do not enwrap the whole factory but rather are detected at discrete sites that consistently coincide with regions where angular structures are detected . This observation , along with the finding that neither cisternae nor angular structures are present in earlier PI times , imply a causal correlation between membrane cisternae and capsid assembly . In addition , cisternae are regularly associated with multiple uniformly sized ( ∼70 nm ) vesicles that appear to be budding from the cisternae . Whereas at 7 . 5 hours PI cisternae are detected at 50 to 100 nm from the edge of the factory core , at 8 hours PI , when partially and fully assembled icosahedral capsids already surround the entire viral factory , these membrane structures are observed at significantly larger distances ( ∼500 nm ) from the factory core , apparently excluded by newly assembling capsids ( Fig . 2E , F; Movies S5 , S6 ) . However , multiple ∼70 nm vesicles are present near the cisternae as well as within the inner , membrane assembly zone , thus supporting the notion that the vesicles are derived from the cisternae . Notably , this finding implies that these vesicles , which are capable of reaching the membrane assembly zone due to their small size , act as a vehicle that enables continuous supply of lipid components required for virion assembly . While the presence of membrane layers has been unequivocally demonstrated in all NCLDV , their source remains controversial . Our TEM studies demonstrate that the cisternae apposed to viral factories are occasionally studded with ribosomes ( Fig . 2D; Movie S4 ) , thus revealing a characteristic appearance of rough endoplasmic reticulum ( RER ) . The origin of the Mimivirus membranes was also investigated by using antibodies against common endoplasmic reticulum markers . These included protein disulfide isomerase ( PDI ) , a soluble protein residing in the ER lumen , and the KDEL retention peptide specifically labeling RER proteins . Substantial redistribution of these markers in infected host-cells is observed at 6 hours PI ( Fig . 3A , B ) . These observations , along with the RER-like appearance of the cisternae apposing the viral factories , infer that cisternae are derived from the host ER network , yet this conjecture needs to be further investigated . At 8 hours PI , massive generation of Mimivirus capsids and maturation of virion progeny occur concomitantly in the inner , membrane biogenesis zone , and at the outer capsid assembly and DNA packaging zone . STEM tomography reveals the presence of several substructures within the membrane biogenesis zone at this stage . In addition to multiple vesicles and angularly-shaped assemblies described above , two prominent substructures are regularly detected: multivesicular bodies and open membrane sheets . Multivesicular bodies comprise of multiple vesicles that reveal similar size and curvature characterizing free vesicles detected in this region as well as near the cisternae , in addition to larger tubular structures ( Fig . 4A–E; Movies S7 , S8 ) . However , these vesicles are interconnected and share their lumen . In addition , large open membrane sheets that are connected to vesicles and to tubular structures ( Fig . 4F–H; Movie S9 ) are regularly detected . Formation of multivesicular bodies and open membrane sheets is closely followed by the generation of angular structures ( Fig . 5A–D; Movies S10 , S11 ) that represent the precursors of icosahedral capsids . The emergence of angular morphologies is accompanied by the formation of a second layer on top of the membrane open sheets , that is , on the side pointing away from the factory core . This angular outer layer progressively evolves into icosahedral morphology , shaping the underlying membrane layer into the same geometry ( Fig . 5E–H; Movie S12 ) . We sought for a protein that might act as scaffold during Mimivirus membrane and capsid assembly . The Vaccinia D13 protein plays a critical role in Vaccinia assembly by generating a honeycomb scaffold on the convex side of open membrane sheets [9] , [14] , [22] , [31] , [34]–[36] . On the basis of a partial sequence similarity to D13L , we speculated that the Mimivirus hypothetical major capsid protein encoded by the L425 open reading frame [24] might act as such a scaffold , a conjecture supported by the recent modeling of L425 [34] . To evaluate this idea we raised antibodies against L425 in both mice and rabbits by using a mixture of three peptides derived from L425 that were estimated as particularly immunogenic . The resulting antibodies recognized a single ∼70 kDa band in lysates of both infected host cells and purified viruses ( Fig . S2 ) , thus confirming that these antibodies interact with L425 , whose calculated weight is 67 . 27 kDa . Immunolabeling with anti-L425 antibodies of both cryo-preserved ( Fig . 6A–D ) and chemically-fixed ( Fig . 6E–G ) sections of 8 hours PI cells , but not of any cell sections derived from earlier PI time points , resulted in clear labeling of angular structures , of assembling icosahedral morphologies as well as of fully assembled capsids ( Fig . 6 and Fig . S2 ) . Our findings imply that the inner Mimivirus membrane is derived from large open membrane sheets that are continuously generated through vesicle fusion and rupture . This process raises the question how is the final size of this inner membrane precisely constrained and determined ? Our high-resolution 3-dimensional STEM tomography studies reveal that throughout the process of capsid formation , long membrane ‘overhangs’ consisting of open sheets are connected to the inner membrane layer ( Fig . 7A–C; Movies S13 , S14 ) . Such surplus sheets appear to be trimmed at a late stage of capsid assembly , during which a 20 nm portal that enables subsequent genome entry and packaging [28] is generated ( Fig . 7D , E ) .
In large DNA viruses the origin of membrane layers , their numbers , as well as the mechanisms responsible for their assembly remain controversial [5] , [23] , [37]–[39] . The current leading view is that these viruses carry a single inner membrane bilayer [9] , [19] , [21] , [22] , raising the question how is such a single bilayer generated . Specifically , whereas formation of two membranes can be straightforwardly assigned to wrapping of collapsed ER cisternae , a single bilayer requires either single-layer membrane precursors or the loss of one ER membrane layer by yet unidentified mechanisms . Insights into these questions were recently provided by cryo-EM and electron tomography of Vaccinia-infected cells [31] , which revealed that Vaccinia crescent precursors are single membrane sheets generated through rupture of the host ER membrane network . On the basis of the observations reported here we suggest a structural model for the multiple stages of membrane biogenesis during Mimivirus infection cycle ( Fig . 8 ) . Generation of Mimivirus inner membrane is initiated at ∼7 . 5 hours PI by the recruitment of host cell membrane cisternae to Mimivirus factories ( Fig . 8A ) , which are formed in the host cytoplasm [25] , [28] , [32] . The idea that cisternae are actively recruited to the factory needs , however , to be further assessed as a passive pathway consisting of encounters of expanding cytoplasmic factories with host cisternae is plausible . Abundant uniformly sized ( ∼70 nm ) vesicles are regularly detected at close proximity to the cisternae ( Fig . 8A , B ) . We suggest that these vesicles are continuously budding from cellular cisternae that act as a reservoir for viral membrane components . As vesicles accumulate in the membrane assembly zone , they fuse into large multivesicular bodies , within which vesicles are interconnected and share a common lumen ( Fig . 8C ) . The idea that multivesicular bodies are generated by fusion of vesicles derived from host membrane cisternae is based on the observation that these bodies are closely surrounded by multiple vesicles . This notion is further supported by the finding that the size and curvature of the vesicular structures composing multivesicular bodies are identical to those characterizing free single vesicles . In addition to fused vesicular structures , a prominent feature revealed by multivesicular bodies is large open membrane sheets consisting of a single membrane bilayer ( Fig . 8D ) . These open sheets , which appear to form through rupture of the multivesicular bodies , continuously expand as additional vesicles fuse to the multivesicular complexes and subsequently rupture , as implied by the evident continuity between open sheets and the ∼70 nm vesicles . As is the case for membrane biogenesis in Vaccinia [31] , the mechanism that promotes rupture and the factors that stabilize the resulting open membrane sheets remain to be identified . Assembly of icosahedral capsids is initiated by the formation of a layer on top of the membrane open sheets that is accompanied by the emergence of prominent angular structures consistently pointing away from the viral factory ( Fig . 8E ) . These angular structures expand to form complete icosahedral capsids , shaping the underlying membrane layer into the same morphology ( Fig . 8F , G ) . Immunolabeling analyses indicate that the angular structures as well as mature icosahedral capsids include the hypothetical major Mimivirus capsid protein L425 . This protein reveals significant similarity to the Vaccinia D13 [34] , which acts as scaffold protein [9] , [14] . Yet , whereas D13 protein disassembles upon Vaccinia maturation [35] , our immunolabeling analyses reveal that L425 remains a constituent of mature Mimivirus virions , in agreement with previous reports [40] . Throughout the process of capsid formation , long membrane ‘overhangs’ , consisting of open sheets that are connected to the evolving inner membrane layer , are present ( Fig . 8G ) . We suggest that , by preventing premature closure of the icosahedral capsids , these overhangs , which are eventually trimmed , play a role in the generation and stabilization of a 20 nm portal through which packaging of the Mimivirus genome proceeds ( Fig . 8H ) . Significantly , in light of the notion that the first icosahedral vertex to be assembled is the DNA-release portal ( the stargate ) [28] , the model proposed here ( Fig . 8-H ) provides a direct interpretation to the observation that the DNA-packaging portal is generated at the opposite side to the stargate . Moreover , our membrane biogenesis and capsid assembly model highlights the dynamic nature of these processes that is essential for ongoing generation of multiple progeny virions . Specifically , as capsid assembly proceeds and new capsid layers are generated at the periphery of the viral factory , large host cisternae are excluded from the inner zone where membrane biogenesis takes place . In contrast , small vesicles are still capable of reaching the membrane assembly zone , thus allowing for continuous supply of lipid components ( Fig . 8I ) . Subsequent vesicle fusion into large multivesicular bodies at the inner membrane biogenesis zone and their eventual rupture enable formation of the large inner viral envelope ( >400 nm in diameter ) from the small ∼70 nm vesicles . Notably , the results reported here are inconsistent with the notion that Mimivirus virions include two internal membrane layers [27] . Rather , our observations imply that this layer represents a scaffolding proteinaceous shell and that the Mimivirus virion contains a single membrane layer , as apparently is the case for other NCLDV members such as Vaccinia , ASFV and PBCV-1 viruses ( see Introduction for more details ) . The proposed model should be viewed as an initial framework for highlighting underlying questions and defining future research directions . First and foremost is the origin of inner membrane layers that are present in all NCLDV virions . For Vaccinia membrane biogenesis , ER-Golgi intermediate compartment ( ERGIC ) membranes were suggested as a source of viral membranes [10] , [11] , [41] , but other studies implied that Vaccinia inner membrane derives from host ER [12] , [13] , [22] , [39] . ER network was also proposed as the source of the ASFV internal membrane [16]–[18] , [42] . Our findings , demonstrating that membrane cisternae accumulating near the factories are studded with ribosomes and that Mimivirus infection is accompanied by massive redistribution of ER markers , infer that Mimivirus membranes derive from host ER , but this conjecture remains to be further evaluated . A fundamental issue that needs to be elucidated concerns the proteins that , in addition to L425 , are involved in the assembly stages described here . Our observations reveal how multiple Mimivirus progeny can be continuously assembled at the periphery of viral factories . The assembly model depicted in Figure 8 underscores the notion that these factories can be considered as efficient ‘production lines’ where , at any given moment all stages of viral generation , including membrane biogenesis , capsid assembly and genome encapsidation , are occurring concomitantly . Moreover , previous reports underscored the similarity between the replication cycles of Vaccinia and Mimivirus by demonstrating that Mimivirus infection takes place entirely in the host cytoplasm [28] , [32] , as is the case for Vaccinia [43] , [44] . Our current findings extend the notion of a physiological similarity between Vaccinia and Mimivirus by demonstrating that membrane biogenesis in both viruses proceeds through the formation of open membrane sheets through rupture of vesicular structures . The question whether this pathway is shared by other viruses as well as by cellular processes that involve membrane assembly represents another fascinating research direction .
Acanthamoeba polyphaga ( AP ) and Mimivirus were obtained from Prof . D . Raoult ( U . Méditerranée , Marseille , France ) . AP Cells were grown in PYG medium . Infected AP cells at various post infection ( PI ) times were spun at 1 , 000 rpm for 5 minutes and 4–6 µl of condensed pellets were cryo-immobilized as reported [28] . Thin ( 60–80 nm ) sections were mounted onto 100–200 mesh copper grids and post stained with 2% uranyl acetate and Reinold's lead citrate . Samples were imaged in a FEI Tecnai T-12 TEM operated at a 120 kV . Images were recorded with an Eagle 2K×2K FEI CCD camera ( Eindhoven , the Netherlands ) . Thick sections ( 250–400 nm ) of embedded samples were transferred to 150-mesh copper grids decorated with 12 nm gold markers on both sides and coated with thin carbon film ( Edwards ) . Tomograms were acquired with FEI Tecnai TF20 TEM operated at 200 kV . Automatic sample tilting , focusing and image shift correction were performed with Xplore3D software ( FEI ) . Tomograms were acquired from −60° to +60° double-tilt series with 1° increments , with Gatan bright-field detector in the nanoprobe mode . 3D reconstructions were computed from tilt series using a weighted back-projection IMOD package . Tomograms were post processed either with a medium or a smoothing filter . Volume segmentation , visualization , and movies creation were conducted with Avizo 6 . 3 image processing package ( Visualization Science Group , Burlington , MA , USA ) . Segmentations were performed by automated as well as guided segmentation modes . Indirect immunofluorescence studies were performed as previously described [32] . Briefly , cells were seeded on glass coverslips , infected with Mimivirus particles at MOI of 10 and incubated for the indicated times before fixing and treating with various antibodies . Following incubation with Cy3-conjugated donkey anti-mouse IgG ( Jackson Immunoresearch ) , samples were counterstained with DAPI . Fluorescence images were obtained with a Deltavision system ( Applied Precision ) . Images were de-convoluted with the conservative SoftWorx package using high noise filtering . Lowicryl HM-20-embedded samples were freeze-substituted , slowly warmed to −30°C , infiltrated with increasing concentrations of HM-20 and polymerized at −30°C with UV light . Infected AP cells were sectioned ( 100–120 nm thick ) on formvar-coated nickel 200 mesh grids . Following treatment with blocking solution grids were incubated with a rabbit anti-L425 antibody . Grids were rinsed with PBS and incubated with 10-nm-gold conjugated goat anti-rabbit . Samples were visualized using an FEI Spirit Tecnai T-12 . For the Tokuyasu immunolabeling method , samples were prepared as previously reported [32] . Mouse and Rabbit anti-L425 antibodies were obtained by immunization with a mixture of three synthetic peptide sequences derived from the L425 sequence and chosen on the basis of their high immunogenic patterns . | With a particle size comparable to that of small bacteria and a 1 . 2 Mbp double-strand DNA genome that carries more than 1000 open reading frames , the amoeba-infecting Mimivirus , along with other recently identified members of the Mimiviridae family , are the largest and most complex viruses yet identified . The Mimivirus particle includes an internal membrane that underlies an icosahedral capsid . The assembly mechanism of internal membrane during Mimivirus infection remains unclear , as is the case for other viruses containing internal membranes . By using diverse imaging techniques , we showed that membrane biogenesis is an elaborate process that occurs at the periphery of viral factories generated at the host cytoplasm . This multistage process , which includes the formation of open membrane sheets , enables efficient and continuous assembly of multiple Mimivirus progeny . The membrane biogenesis process suggested here provides novel insights into the assembly of internal viral membranes in general . | [
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] | 2013 | Membrane Assembly during the Infection Cycle of the Giant Mimivirus |
Macrophage Scavenger Receptor A ( SR-A ) is a major non-opsonic receptor for Neisseria meningitidis on mononuclear phagocytes in vitro , and the surface proteins NMB0278 , NMB0667 , and NMB1220 have been identified as ligands for SR-A . In this study we ascertain the in vivo role of SR-A in the recognition of N . meningitidis MC58 ( serogroup B ) in a murine model of meningococcal septicaemia . We infected wild-type and SR-A−/− animals intraperitoneally with N . meningitidis MC58 and monitored their health over a period of 50 hours . We also determined the levels of bacteraemia in the blood and spleen , and measured levels of the pro-inflammatory cytokine interleukin-6 ( IL-6 ) . The health of SR-A−/− animals deteriorated more rapidly , and they showed a 33% reduction in survival compared to wild-type animals . SR-A−/− animals consistently exhibited higher levels of bacteraemia and increased levels of IL-6 , compared to wild-type animals . Subsequently , we constructed a bacterial mutant ( MC58-278-1220 ) lacking two of the SR-A ligands , NMB0278 and NMB1220 . Mutation of NMB0667 proved to be lethal . When mice were infected with the mutant bacteria MC58-278-1220 , no significant differences could be observed in the health , survival , bacteraemia , and cytokine production between wild-type and SR-A−/− animals . Overall , mutant bacteria appeared to cause less severe symptoms of septicaemia , and a competitive index assay showed that higher levels of wild-type bacteria were recovered when animals were infected with a 1∶1 ratio of wild-type MC58 and mutant MC58-278-1220 bacteria . These data represent the first report of the protective role of SR-A , a macrophage-restricted , non-opsonic receptor , in meningococcal septicaemia in vivo , and the importance of the recognition of bacterial protein ligands , rather than lipopolysaccharide .
The innate immune system is a first line of defence against invading pathogens and macrophages play an integral role in the innate immune defence against bacterial infection . This is based on the recognition of conserved microbial structures , termed pathogen-associated molecular patterns ( PAMPs ) , by a range of pattern recognition receptors ( PRRs ) . Macrophages ( Mφ ) express different classes of innate PRRs with diverse functions , including the phagocytic Scavenger receptors ( SRs ) [1] . One of the receptors belonging to this family is the class A scavenger receptor ( SR-A ) , which has been shown to recognise a range of polyanionic molecules [2] . SR-A is a trimeric type II transmembrane glycoprotein consisting of a cytoplasmic tail , transmembrane domain , spacer region , α-helical coiled coil domain , collagenous domain and C-terminal cysteine-rich domain . SR-A expression is mostly restricted to macrophages and is not found on polymorphonuclear neutrophils or monocytes [3] . Recently , the expression of SR-A was shown on mast cells [4] and specific sub-populations of bone marrow-derived dendritic cells ( DC ) and splenic DC [5] . Selected endothelial cells and smooth muscle cells within atherosclerotic plaques also express SR-A [6] . The Scavenger receptors play an important role in microbial recognition and clearance , and SR-A has been shown to bind both Gram-positive and Gram-negative bacteria [7] . Hampton and colleagues first proposed that SR-A might be involved in antimicrobial host defence , based on their observation that SR-A could bind lipid A , an integral part of lipopolysaccharide ( LPS ) [8] . Subsequent studies showed that SR-A also recognises the Gram-positive cell-wall component lipoteichoic acid ( LTA ) [9] . Furthermore , SR-A binds to different LTA structures with varying specificity depending on their exposed negative surface charge . Unmethylated bacterial CpG DNA , another major immunostimulatory microbial product , is also recognised by SR-A [10] . Using a range of Gram-positive organisms , Dunne and co-workers confirmed that both soluble and cell-associated forms of SR-A are not only able to bind bacterial components , but can also recognise intact live organisms [11] . SR-A has been shown to play a role in both infection and inflammation . In vivo studies with three Gram-positive organisms have shown that SR-A−/− mice are more susceptible to infection . SR-A−/− animals exhibited deficient clearance of bacteria from the liver and spleen in experimental Listeria monocytogenes infection [12] . SR-A−/− mice also showed increased susceptibility to Staphylococcus aureus and Streptococcus pneumoniae infection [13] , [14] . A possible anti-inflammatory host-protective role of SR-A was proposed by Haworth et al . , who observed that SR-A−/− mice formed normal granulomas in response to BCG ( Bacille Calmette-Guérin ) priming [15] . However , these animals were more susceptible to endotoxic shock as a result of increased pro-inflammatory cytokine secretion in response to additional lipopolysaccharide ( LPS ) challenge . In addition , SR-A has been shown to modulate chemokine levels in specific acute inflammatory conditions to ensure an inflammatory response of the appropriate magnitude [16] . Neisseria meningitidis is a Gram-negative obligate commensal bacterium that colonises the human nasopharynx , however when the bacterium crosses this barrier , it causes meningitis and rapid septicaemia , particularly in young children and teenagers . We have shown previously that uptake of N . meningitidis by macrophages is mediated almost exclusively via SR-A [17] . Interestingly , experiments employing an N . meningitidis lpxA mutant revealed that recognition of N . meningitidis by SR-A was independent of lipopolysaccharide , and we identified three bacterial surface protein ligands for SR-A , namely NMB0278 , NMB0667 and NMB1220 [18] . In this study we investigated the in vivo role of SR-A in inflammation in a murine meningococcal septicaemia model . We also ascertained the contribution of the identified surface protein ligands by constructing bacterial mutants in the SR-A ligands and examining the effects of a double mutant in vivo . We show that SR-A knock-out mice are more susceptible to septicaemia induced by N . meningitidis than wild-type mice , and that for double knock-out bacteria lacking two SR-A ligands , these effects are abrogated .
Unless otherwise stated , all chemicals were from Sigma ( Poole , United Kingdom ) . Acetylated low density lipoprotein ( AcLDL ) and Rhodamine Green X ( RdGnX ) were obtained from Molecular Probes ( Eugene , OR , USA ) . The TMB substrate reagent set was purchased from BD Biosciences Pharmingen ( San Diego , CA ) . All culture media were from Gibco ( Paisley , United Kingdom ) . The rat monoclonal anti-CD68 monoclonal antibody FA-11 was obtained from AbD Serotec ( Kidlington , UK ) . The rat monoclonal antibody against the 7/4 murine differentiation antigen was generated in this laboratory [19] . M5114 , the rat monoclonal antibody recognising murine MHC-II was obtained from R&D Systems ( Abingdon , UK ) . The Neisseria meningitidis strains used in this study are listed in Table 1 . All strains were grown overnight at 37°C on brain-heart infusion ( BHI ) medium ( Oxoid ) , supplemented with Levinthal's reagent ( 10% vol/vol ) and solidified with agar ( 1% [wt/vol]; Bioconnections ) , in an atmosphere of 5% CO2 . For selection of strains following transformation , kanamycin ( 75 µg ml−1 ) or erythromycin ( 6 µg ml−1 ) was added to the culture medium . Escherichia coli strain DH5α was used to propagate recombinant DNA constructs and was grown at 37°C on Luria-Bertani ( LB ) medium supplemented with kanamycin ( 50 µg ml−1 ) , erythromycin ( 300 µg ml−1 ) or ampicillin ( 50 µg ml−1 ) where appropriate . For fluorescent labelling , N . meningitidis were fixed with 70% ethanol and labelled with RdGnX according to the manufacturer's instructions . Recombinant DNA techniques were performed as described by Sambrook et al . [20] . Restriction endonuclease and DNA modifying enzymes were obtained from Boehringer Mannheim or New England Biolabs and used according to the manufacturers' instructions . Oligonucleotide primers were synthesised by Sigma-Genosys . Standard polymerase chain reaction ( PCR ) amplifications were performed in 50 µl reaction volumes ( final concentrations: 20 mM Tris-HCl , pH 8 . 4; 50 mM KCl; 2 . 5 mM MgCl2; 0 . 4 µM forward primer; 0 . 4 µM reverse primer; 0 . 4 mM dNTPs ) with 1 . 25 U Taq recombinant polymerase ( Invitrogen , Paisley , UK ) in a Master-Cycler ( Eppendorf ) gradient thermal cycler . Thirty cycles of PCR were performed , each consisting of 1 min denaturation at 94°C , 1 min annealing at typically 5°C below Tm and 1 min extension at 72°C , with a final prolonged extension of 10 min at 72°C . Chromosomal DNA was prepared from N . meningitidis strains as described previously [21] . A list of oligonucleotide primers used in this study is given in Table 2 . Outer membrane vesicles were prepared from N . meningitidis cells as described by Heckels and Williams et al [22] , [23] . Briefly , cells were harvested from confluent growth of bacteria on 40 BHI plates into 0 . 2 M lithium acetate ( 40 ml , pH 5 . 8 ) and extracted at 45°C in the presence of 2 mm glass beads ( 20 ml ) . Live bacteria were removed by centrifugation at 13 , 00 g , 20 min , the supernatant was then subjected to a repeat of this step . The outer membranes were recovered by centrifugation at 11 , 000 g , 4°C , 2 h and the resuspended in 200 µl dH2O . The protein concentration of the outer membranes was determined by performing a Lowry MicroAssay ( Sigma ) according to the manufacturer's instructions . 15 µg of total protein was diluted in dH2O and loaded in each well . Whole cell lysates were prepared from N . meningitidis strains grown overnight , by harvesting and resuspending cells in PBS and then adding the equivalent amount of dissociation buffer ( 125 mM Tris , pH 6 . 8 , 20% [v/v] glycerol , 3 . 9% [w/v] SDS , 10% β-mercaptoethanol , 0 . 04% [w/v] bromphenol blue ) . All samples were boiled at 100°C for 5 min . Samples were separated by tricine-sodium dodecyl sulphate-polyacrylamide gel electrophoresis ( T-SDS-PAGE ) using 16 . 5% gels run at 30 mA at 4°C for 18 hr [24] , and were visualised by staining with silver nitrate according to the manufacturer's instructions ( Amersham Biosciences ) . To mutate the N . meningitidis NMB0278 gene , the gene was first amplified by PCR from strain H44/76 chromosomal DNA with oligonucleotide primers 278-f/278-r and cloned into the plasmid pT7Blue ( Novagen ) . A kanamycin resistance ( kanR ) cassette was excised from pUC4-kan by digestion with HincII and inserted into the HincII site within the cloned NMB0278 gene . The resulting construct , pT7-278-kan was used to transform N . meningitidis strain MC58 as described previously [25] . Screening of transformants was performed by PCR using primers designed to bind within the kanR cassette and in the neighbouring gene to identify transformants containing a single , disrupted copy of NMB0278 . To mutate the N . meningitidis NMB0667 gene , the gene was first amplified by PCR from strain H44/76 chromosomal DNA with oligonucleotide primers 667-f/667-r and cloned into the plasmid pT7Blue ( Novagen ) . An erythromycin resistance cassette ( ermC ) was excised from pER2 [26] , by digestion with HincII and inserted into the SmaI site within the cloned NMB0667 gene . The resulting construct , pT7-667-ery , was used to transform N . meningitidis strain MC58 . Transformants were screened by PCR using primers designed to bind within the ermC cassette and in the neighbouring gene to identify a transformant containing a single , disrupted copy of NMB0667 . To mutate the gene NMB1220 , the 5′ and 3′ regions of the gene were first amplified by PCR from N . meningitidis strain MC58 chromosomal DNA , with oligonucleotide primers 1220-3f/1220-3r and 1220-5f/1220-5r , respectively , before cloning each product separately into pT7Blue , resulting in the plasmids pT7-1220-3 and pT7-1220-5 . The ermC cassette was amplified from pER2 [26] with oligonucleotide primers ery-eag-f and ery-eag-r , digested with EagI and inserted into the EagI site present within the cloned 3′ region of the NMB1220 gene in pT7-1220-3 to give the construct pT7-1220-3-ery . The cloned 3′ region of NMB1220 , interrupted with ermC , was excised from pT7-1220-3-ery with XbaI and BglII and inserted into the corresponding site within pT7-1220-5 . The resulting construct , pT7-1220-ery , was used to transform N . meningitidis strain MC58 . Transformants were screened by PCR using oligonucleotide primers 1220-f/1220-r designed to bind within NMB1220 to identify a transformant containing a single , disrupted copy of NMB1220 . Bacteria cultured on BHI plates were assayed in pooled human serum as described previously [27] . Bone marrow-derived macrophages ( BMMφ ) were prepared as described previously [7] . Mφ were routinely cultured in RPMI supplemented with 100 U/ml penicillin , 100 µg/ml streptomycin and 2 mM L-glutamine ( PSG ) , 10% foetal calf serum ( FCS ) and 15% L-cell conditioned medium . Bone marrow-derived macrophages were plated in 6-well bacteriological plastic dishes at a density of 1×106 Mφ per well 24 hours before use . Mφ were washed twice in PBS and then incubated in Opti-MEM medium ( Invitrogen , Paisley , UK ) containing fluorescently-labelled bacteria as specified . After incubation with bacteria , the culture medium was removed and the cells washed three times with PBS . Cells for flow cytometry were harvested with PBS containing 10 mM EDTA and 4 mg/ml lidocaine-HCl and fixed with 4% ( v/v ) formaldehyde in PBS . Fluorescence was analysed on a FACScan ( Becton Dickinson , Mountain View , CA ) using the FL-1 or FL-2 photomultiplier where appropriate and the results analysed with CellQuest software . Results are representative of at least 3 independent experiments . A murine intraperitoneal challenge model for bacterial clearance was employed [28] . C57BL/6J wild-type mice and a corresponding SR-A−/− knock-out mouse strain were used . SR-A−/− animals were developed and bred onto C57BL/6J background using standard molecular biology techniques [12] . All animals were bred and housed under specific pathogen-free conditions . Meningococcal strains were grown overnight at 37°C in 5% CO2 on BHI plates as described above . Muller Hinton broth ( 8 ml ) supplemented with 0 . 25% ( w/v ) glucose in a 50 ml tissue culture flask was inoculated with 1 . 2×109 cfu from the overnight growth resulting in an initial OD620 of ∼0 . 1 . The flask was incubated horizontally on a gently rocking platform at 37°C in 5% CO2 and bacteria were cultured to mid-logarithmic growth phase , defined as OD620 of ∼0 . 5 ( approximately 2 . 5 h ) . The bacteria were transferred to 1 . 5 ml tubes and harvested by centrifugation at 1900 g for 5 min and then resuspended in PBS . The bacterial suspensions were adjusted to the required concentration for inoculation in BHI broth . Bacterial doses of 1×105 cfu/mouse were injected intraperitoneally ( i . p . ) with human holo-transferrin ( Sigma , 10 mg/mouse ) in a total volume of 500 µl to groups of 6–8-week-old wild-type C57BL/6J and corresponding SR-A−/− knock-out inbred female mice . At the time of infection , the actual dose delivered to each group of mice was determined by serial dilution and replicate colony plating . At 18 h after the initial infection , mice were boosted i . p . with a further dose of human holo-transferrin ( 10 mg/mouse in 200 µl PBS ) . The health of the animals was monitored and scored at regular time points according to the symptoms presented as follows: Healthy = 5 , ruffled fur = 4 , sticky eyes = 3 , ruffled fur and sticky eyes = 2 , immobile = 1 . As soon as immobile mice were detected they were humanely killed . Scores were then collated and averaged for each group at the various time points [29]; ( A . Gorringe , personal communication ) . Survival curves were also plotted and statistical significance determined using the Log-rank ( Mantel Cox ) test . Blood samples from the tail vein ( 5 µl ) were taken at 20 h post-infection and serial dilutions plated to determine bacteraemia . All dilutions were made with PBS . At termination , blood was collected by cardiac puncture and spleens removed . Half of each spleen was fixed in 2% paraformaldehyde in HEPES-buffered isotonic saline for immunohistochemical analysis . The remaining spleen was homogenized and serial dilutions of spleen and blood were plated to determine bacteraemia . The remaining blood was separated by centrifugation and the plasma collected and frozen at −80°C for later use . All procedures involving animals were conducted according to the requirements of the United Kingdom Home Office Animals ( Scientific Procedures ) Acts , 1986 . Fixed tissues were transferred to a solution of 0 . 1 M sodium phosphate buffer containing 20% sucrose , placed in Tissue-Tek OCT compound ( VWR International Ltd . , Lutterworth , UK ) and snap-frozen in isopentane cooled by dry ice . Frozen sections were cut on a Leica cryostat ( 5 µm thick ) , collected onto 1 . 5% gelatinized slides , air dried for 1 hour and stored at −20°C . Sections were washed in 0 . 1% Triton X-100 and endogenous peroxidase activity was quenched by incubation in PBS containing 0 . 01 M glucose , 0 . 001 M sodium azide and 40 U glucose oxidase for 15 min at 37°C . 5% Normal rabbit serum was used as blocking agent for non-specific binding and avidin/biotin blocking agents ( Vector Laboratories Ltd . , Peterborough , UK ) were employed according to the manufacturer's instructions . Sections were incubated for 60 min in the respective primary antibodies or isotype-matched controls , washed and incubated for 30 min with the respective affinity purified biotinylated secondary antibodies . Finally , sections were washed and incubated with the avidin-biotin peroxidase complex ( ABC elite , Vector Laboratories Ltd . , Peterborough , UK ) for 30 min and staining visualised by incubation with 0 . 5 mg/ml diaminobenzidine ( Polysciences Inc . , Northampton , UK ) and hydrogen peroxide in 10 mM imidazole . Sections were counterstained with 0 . 1% methyl green ( Vector Laboratories Ltd . Peterborough , UK ) and mounted in DPX ( VWR International Ltd . , Lutterworth , UK ) . The concentration of interleukin-6 ( IL-6 ) in the plasma of infected mice was determined using an OptEIA Mouse IL-6 ELISA set ( BD Biosciences , San Diego ) according to the manufacturer's instructions . Groups of five 6–8-week-old female wild-type C57BL/6J and corresponding SR-A−/− animals were infected with 1×106 N . meningitidis MC58 ( wild-type ) +1×106 N . meningitidis MC58-278-1220 ( mutant ) i . p , along with 10 mg human holo-transferrin . The two bacterial strains were individually grown overnight as before . Serial dilutions of the inoculum were also plated onto both BHI medium and BHI medium supplemented with kanamycin ( which selects for MC58-278-1220 mutant bacteria ) , in order to verify the dose and ratio of wild-type to mutant bacteria . A second dose of 10 mg human holo-transferrin was injected i . p . at 18 h . The health of the animals was monitored as before . At termination , blood was collected by cardiac puncture and spleens removed . Spleens were homogenized and serial dilutions of blood and spleen samples were plated on BHI medium and BHI medium supplemented with kanamycin . Enumeration of wild-type bacteria and mutant bacteria allowed for the determination of the CI ratio between wild-type and mutant bacteria using the following formula: CI = ( wild-type output/mutant output ) / ( wild-type input/mutant input ) . The statistical significance of the results was determined using the paired student's t-test .
To investigate the importance of NMB0278 , NMB0667 and NMB1220 for recognition of N . meningitidis by SR-A , plasmids were constructed containing each gene interrupted by insertion of a kanamycin or erythromycin resistance cassette . The constructs pT7-278-kan and pT7-667-ery resulted from a single PCR product from NMB0278 and NMB0667 , respectively , cloned into pT7Blue and then interrupted with an antibiotic resistance cassette . It is interesting to note that when a similar approach was utilised with NMB1220 , the initial pT7-1220 construct proved to be highly unstable and consequently a two step approach of cloning the 5′ and 3′ regions of the gene together with some flanking DNA was undertaken , which proved to be successful . The plasmids pT7-278-kan , pT7-667-ery and pT7-12220-ery were transformed into N . meningitidis strain MC58 . The serogroup B genome sequence contains two homologues of NMB0278 , namely NMB0294 and NMB0407 . To ensure that only NMB0278 had been disrupted , specific oligonucleotide primers were designed to bind within the kanR cassette and in the neighbouring gene to identify transformants containing a single , disrupted copy of NMB0278 . This transformant was designated MC58-278 . The gene NMB0667 shows low levels of homology to a degenerate DNA methylase found elsewhere in the serogroup B genome ( NMB1223 ) , so primers designed to bind within the ermC cassette and in the neighbouring gene were utilised to identify transformants containing a single , disrupted copy of NMB0667 . A number of transformants were screened using different combinations of oligonucleotide primers . For each transformant containing an interrupted copy of NMB0667 , an intact copy of the gene was present in tandem , therefore we concluded that NMB0667 is an essential gene , and consequently we were unable to obtain a mutant neisserial strain deficient in this protein . Double mutants where both NMB1220 and NMB0278 had been interrupted were constructed by transforming MC58-1220 with chromosomal DNA from MC58-278 . The disruption of NMB0278 and NMB1220 was confirmed by the use of specific oligonucleotide primers as for the single mutants . This transformant was designated MC58-278-1220 . The growth of the MC58-278 , MC58-1220 and MC58-278-1220 in vitro was compared to that of the parental strain MC58 . The bacteria were grown in Muller-Hinton broth in the same manner as for the preparation of inoculum for the mouse infection studies , except that growth was followed over an 8 h period and the OD620 was measured throughout ( Figure 1A ) . All mutants exhibited growth curve patterns indistinguishable from the parent strain . Outer membranes were prepared from the mutants and parental strain following growth on BHI plates overnight and separated by T-SDS-PAGE ( Figure 1B ) . The resulting profiles show that no significant differences were observed in the protein and LPS profiles . A comparison of the parental strain MC58 and the mutant strains showed no difference in the killing effect in pooled normal human serum ( data not shown ) . In order to determine the distribution of these genes , a PCR screen was undertaken using primers specific not just for the gene under consideration , but also for its genomic location due to the homologous reading frames present for NMB0278 and NMB0667 . 107 strains were screened using the following sets of primers; 278-out-f/278-out-r , 667-f/667-r , 667-f2/667-r and 1220-f/1220-r . This collection of strains was highly diverse and included representatives of disease and carriage isolates , along with well characterised reference strains . With the exception of one invasive disease strain , all gave a PCR product of the expected size for each of the three genes ( refer to Table 3 ) . The one anomalous strain demonstrated a PCR product for NMB0667 and NMB1220 but not for NMB0278 . All three genes were determined to be present by this method in 7 N . gonorrhoeae isolates , however the distribution was found to vary considerably when other commensal species of Neisseria were analysed ( data not shown ) . To ascertain the in vitro macrophage uptake of wild-type bacteria compared to that of mutant bacteria , wild-type and SR-A−/− bone marrow-derived macrophages were incubated at 37°C for 2 h with ethanol-fixed fluorescently labelled N . meningitidis MC58 or the mutant bacteria with deletions in either NMB0278 , NMB1220 or both ( MC58-278 , MC58-1220 and MC58-278-1220 ) , respectively , at an MOI of 20∶1 ( Figure 2 ) . Association of bacteria with macrophages was measured by flow cytometry . All the bacterial strains were taken up by wild-type macrophages , whereas uptake was reduced by at least 70% in macrophages lacking SR-A . However , no differences could be detected in the association of the mutant bacteria with wild-type macrophages . This could be attributed to the fact that there are multiple ligands for SR-A on N . meningitidis [18] and that the gene encoding at least one known ligand , NMB0667 , could not be deleted . In addition , the strains still contained homologues for NMB0278 . Since no differences could be detected between wild-type and mutant bacteria in their interaction with SR-A in vitro , we set up an in vivo murine septicaemia model to investigate the role of SR-A in the clearance of N . meningitidis . First , we tested several bacterial doses in wild-type and SR-A−/− animals to determine the intraperitoneal ( i . p . ) dose required to establish bacteraemia in the blood and spleen , without causing rapid death of the animals , so that they could be monitored over time . From these experiments we selected a dose of 1×105 cfu/mouse ( data not shown ) . Groups of six age-matched female C57BL/6J wild-type and corresponding SR-A−/− knock-out mice were injected i . p . with 1×105 N . meningitidis MC58 cfu/mouse and 10 mg human holo-transferrin as a bacterial iron source . N . meningitidis requires iron for growth and is unable to sequester iron from murine transferrin [30] , [31] . A second dose of human holo-transferrin was administered i . p . at 18 h to maintain available iron levels in the blood . Animals were monitored regularly over a period of 48 h for symptoms of septicaemia . Each individual was assigned a health score at each time point , according to the severity of symptoms ( animals with a score of 5 were healthy , and a score of 1 was assigned when they were immobile , refer to materials and methods ) . Scores were then collated and averaged for the group , and the results plotted to provide a health curve ( Figure 3A ) . Although animals in both groups exhibited symptoms of septicaemia , wild-type animals remained healthier , particularly after the second injection of iron , which would support bacterial proliferation . Survival curves ( Figure 3B ) also show that all the SR-A−/− animals had died at 32 h , while 33% of the wild-type animals survived beyond 48 h and recovered to full health . Overall , SR-A−/− animals showed more rapid deterioration of health and died more quickly than did wild-type animals . This could be correlated with the observation that SR-A−/− animals had higher levels of bacteraemia in their blood at both 20 h and 48 h than did wild-type animals ( Figure 3C ) . Although there seemed to be a trend towards higher bacterial levels in the spleens of SR-A−/− animals , the differences in bacteraemia between the two strains were not statistically significant . We also measured levels of interleukin-6 ( IL-6 ) in plasma from blood collected at 48 h . SR-A−/− animals consistently showed significantly higher levels of the pro-inflammatory cytokine IL-6 than wild-type animals . Spleen sections were also analysed by immunohistochemistry with three antibodies , FA-11 ( an intracellular macrophage marker , staining macrosialin [CD68] ) , 7/4 Ag ( a neutrophil and monocyte marker ) and MHC-II ( an antibody recognising the major histocompatibility class II molecule , a marker expressed on resident dendritic cells and activated macrophages ) . FA-11 ( macrosialin ) is a pan-macrophage marker , indicating the macrophage infiltration into the spleen . Staining with MHC-II shows that the macrophages are activated . The 7/4 Ag staining shows the infiltration of activated monocytes and polymorphonuclear neutrophils ( Figure 4 ) . Therefore all the splenic samples showed a high number of infiltrating activated macrophages and neutrophils . Next , we tested the mutant bacteria lacking both SR-A ligands , NMB0278 and NMB1220 , for their ability to establish septicaemia in wild-type and SR-A−/− animals . Groups of eleven age-matched female C57BL/6J wild-type and corresponding SR-A−/− knock-out mice were injected i . p . with 1×105 N . meningitidis MC58-278-1220 cfu/mouse and 10 mg human holo-transferrin as before . Animals were monitored regularly , assigned health scores and their survival plotted ( Figure 5A and 5B ) . Animals in both groups exhibited symptoms of septicaemia , however differences observed between wild-type and SR-A−/− animals when infected with wild-type bacteria , were absent . Overall both mouse strains showed fewer symptoms of septicaemia and had a higher survival rate when infected with mutant MC58-278-1220 bacteria ( Figure 5A and 5B ) . No statistically significant differences were observed in the levels of bacteraemia in either the blood or the spleen between wild-type and SR-A−/− animals ( Figure 5C ) . IL-6 levels were also not statistically significantly different between wild-type and SR-A−/− animals and were lower overall than in animals infected with wild-type bacteria ( Figure 5D ) . Therefore the SR-A-mediated effects observed when mice were infected with wild-type bacteria were abrogated for mutant bacteria lacking two SR-A ligands . When MC58-278-1220 mutant bacteria were injected into wild-type and SR-A−/− mice , we observed not only the abrogation of the SR-A-mediated effect , but also that mutant bacteria seemed to cause less severe symptoms of septicaemia and animals had a higher survival rate . To test whether this was a bona fide observation , we employed a competition assay to determine whether wild-type bacteria would out-compete mutant bacteria in vivo . To obtain a bacterial count for wild-type and mutant bacteria in each case , we injected 1×106 wild-type MC58 and mutant MC58-278-1220 bacteria i . p . at a ratio of 1∶1 . The respective bacterial numbers in blood and spleen were determined by replicate plating of serial dilutions on BHI medium and BHI medium supplemented with kanamycin , which would select for mutant bacteria carrying the kanamycin resistance cassette used to disrupt the gene encoding NMB0278 . Table 4 shows the competitive indices in wild-type and SR-A−/− animals . A competitive index of 6 . 891 and 5 . 090 was obtained for bacterial counts from blood and spleen from wild-type animals , respectively . This indicates that more wild-type bacteria remained than did mutant bacteria . In SR-A−/− animals , a competitive index of 2 . 781 and 1 . 660 was obtained from blood and spleen , respectively .
In this study we evaluated the in vivo role of SR-A in meningococcal septicaemia induced by N . meningitidis MC58 ( serogroup B ) , and ascertained the role of the N . meningitidis surface proteins , previously identified to be ligands for SR-A [18] . The neisserial surface protein ligands were NMB0278 , NMB0667 and NMB1220 . NMB1220 has been shown to be surface expressed and similar experiments showed the surface expression of NMB0278 and NMB0667 [32] and personal communication ) . The function of these proteins is unknown , however they show some homology to proteins identified in other bacterial species . Sequence analysis suggests that NMB0278 has homology to E . coli DsbA , which functions in disulphide bond formation [33] . Interestingly , the DsbA protein of Haemophilus influenzae , another obligate human pathogen colonising the nasopharynx , has recently been shown to be a virulence factor [34] . The C-terminus of NMB0667 has 20% homology with the ZipA protein from E . coli , which is involved in septum formation during cell division [35] . NMB1220 belongs to the stomatin/Mec-2 protein family , which are oligomeric lipid raft-associated integral proteins that regulate the function of ion channels and transporters . We constructed deletion mutants in N . meningitidis MC58 for all three proteins , respectively , and also generated a double mutant lacking NMB0278 and NMB1220 . We employed several approaches to delete NMB0667 , however this mutation proved lethal , which may be linked to the possible role of NMB0667 in septum formation during cell division . All the mutant strains showed no deficiency in growth characteristics or LPS and protein profile . Through PCR analysis , we showed that the genes encoding these proteins are present in a wide variety of neisserial strains , including invasive disease and carriage strains . Closely related homologues are also present in other bacteria , making them ideal PAMPs ( pathogen-associated molecular patterns ) and targets for PRRs . It should however be noted that since the genes encoding these proteins are also present in non-pathogenic bacteria and commensal strains , the term “PAMPs” , though commonly used in this context , could be considered a misnomer . In vitro uptake of the mutant bacteria by bone marrow-derived macrophages from wild-type and SR-A−/− animals did not show any differences when compared to wild-type bacteria . This could be attributed to the fact that at least one other SR-A ligand , NMB0667 , was present , along with two NMB0278 homologues , which could mediate recognition and uptake . Therefore , we studied the in vivo role of SR-A in a murine model for meningococcal septicaemia . We injected N . meningitidis MC58 into wild-type C57BL/6J and corresponding SR-A−/− mice and monitored the manifestation of symptoms of septicaemia ( ruffled fur , sticky eyes ) , as well as the survival of the animals . The health of SR-A−/− animals consistently deteriorated more rapidly and there was a 33% difference in survival when compared to wild-type animals . Analysis of blood samples taken at 20 h post-infection and at termination showed that SR-A−/− animals had higher levels of bacteraemia and the pro-inflammatory cytokine , IL-6 . Induction of IL-6 is commonly associated with meningococcal septicaemia in humans [36] . Although not statistically significant , spleen samples also indicated higher bacteraemia for SR-A−/− animals , and splenic sections revealed infiltration of activated macrophages , monocytes and neutrophils . Therefore , in this model , SR-A played an important role in clearance of N . meningitidis MC58 . This is the first report of the in vivo importance of SR-A in a model using a Gram-negative pathogenic organism . Subsequently , we injected the mutant bacteria lacking both NMB0278 and NMB1220 at the same dose i . p . into wild-type and SR-A−/− mice and monitored them as before . Interestingly , the differences observed between the mouse strains when infecting with wild-type bacteria were abrogated for mutant bacteria lacking the two SR-A ligands , and overall less severe symptoms were observed . Furthermore , the levels of bacteraemia and IL-6 between wild-type and SR-A−/− animals did not differ significantly . Therefore the surface proteins NMB0278 and NMB1220 are at least partially implicated in the SR-A-mediated effects observed for wild-type bacteria . We previously showed that NMB0278 and NMB1220 are also Toll-like receptor ( TLR ) agonists , and that SR-A was required for full activation of TLR pathways ( Plüddemann et al . JII , in press ) . Although SR-A ligation does not directly mediate cytokine induction , the overall lower cytokine levels in animals infected with mutant bacteria could be linked to the absence of NMB0278 and NMB1220 . The competitive index assay confirmed that mutant bacteria were cleared more readily , proving that this observation was not due to inter-experimental variations . These data indicate a role for SR-A in clearance of N . meningitidis and development of symptoms of septicaemia . Thus far , the development and progression of septicaemia has mainly been linked to LPS , however these data indicate an additional role of neisserial surface protein recognition in this process . It is clear that the i . p . mouse challenge model described here does not represent the natural pathogenesis of neisserial disease , however it does model the overwhelming septicaemia that is characteristic of invasive meningococcal disease . Since SR-A is not expressed on polymorphonuclear neutrophils , our results signify an important role for macrophages and SR-A in the development and progression of meningococcal septicaemia . | Macrophages are innate immune cells that provide a first defence against infection . Several receptors on the surface of macrophages mediate recognition of invading pathogens , and one of these is the Macrophage Scavenger Receptor A ( SR-A ) . SR-A recognises Neisseria meningitidis , a bacterium that causes meningitis and septic shock , via proteins on the surface of the bacterium . In this study we investigated the interaction of SR-A with N . meningitidis in a mouse model for septic shock , by infecting mice with N . meningitidis and comparing a mouse strain expressing SR-A with one that does not . The health of mice not expressing SR-A deteriorated more rapidly and fewer animals survived compared to those expressing SR-A . Mice lacking SR-A had higher numbers of bacteria in their blood and also produced more cytokines that can cause septic shock . We also infected mice with bacteria that did not express two of the proteins recognised by SR-A . In this case , no differences in survival , levels of bacteria , or cytokines were detected between animals that expressed SR-A and those that did not . Therefore , we show that the macrophage receptor SR-A is protective in the development of septic shock induced by N . meningitidis . | [
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] | 2009 | The Macrophage Scavenger Receptor A Is Host-Protective in Experimental Meningococcal Septicaemia |
Females homozygous for a mutation in cellular island ( cei ) produce embryos with defects in cytokinesis during early development . Analysis of the cytoskeletal events associated with furrow formation reveal that these defects include a general delay in furrow initiation as well as a complete failure to form furrow-associated structures in distal regions of the blastodisc . A linkage mapping-based candidate gene approach , including transgenic rescue , shows that cei encodes the zebrafish Aurora B kinase homologue . Genetic complementation analysis between the cei mutation and aurB zygotic lethal mutations corroborate gene assignment and reveal a complex nature of the maternal-effect cei allele , which appears to preferentially affect a function important for cytokinesis in the early blastomeres . Surprisingly , in cei mutant embryos a short yet otherwise normal furrow forms in the center of the blastodisc . Furrow formation is absent throughout the width of the blastodisc in cei mutant embryos additionally mutant for futile cycle , which lack a spindle apparatus , showing that the residual furrow signal present in cei mutants is derived from the mitotic spindle . Our analysis suggests that partially redundant signals derived from the spindle and astral apparatus mediate furrow formation in medial and distal regions of the early embryonic blastomeres , respectively , possibly as a spatial specialization to achieve furrow formation in these large cells . In addition , our data also suggest a role for Cei/AurB function in the reorganization of the furrow-associated microtubules in both early cleavage- and somite-stage embryos . In accordance with the requirement for cei/aurB in furrow induction in the early cleavage embryo , germ plasm recruitment to the forming furrow is also affected in embryos lacking normal cei/aurB function .
Following fertilization , an increase in cell number through cell division characterizes the initiation of early embryonic development . Cell division itself , and specifically cytokinesis , the physical process that divides a cell into two daughter cells , remains incompletely understood . Early stages of cytokinesis involve the specification of the cleavage site midway between the spindle poles [1] , [2] . Recently , it has been proposed that signals from both astral and spindle microtubules act redundantly in furrow initiation [3]–[5] . In these studies , astral microtubules have been proposed to induce furrow initiation while a subsequent spindle midzone-derived signal further promotes furrow formation . The Aurora B kinase ( AurB ) is thought to be a crucial factor in multiple processes in cell division , including furrow formation during cytokinesis . AurB , together with other factors such as Incenp , Survivin and CSC-1 , is a component of the chromosomal passenger complex , which is localized to centrosomes prior to mitosis but becomes localized to centromeres in metaphase and to the spindle midzone after chromatid segregation in anaphase ( reviewed in [6] ) . Independent of its accumulation at the furrow via the spindle midzone , AurB is also delivered to the prospective cleavage site along astral microtubules [7] , [8] . Chromosomal passenger protein function has been implicated in the localization to the central spindle of centralspindlin , a complex comprising the kinesin subfamily member Mklp1 ( also known as ZEN-4 and Pavarotti ) and the Rho family GTPase-activating protein RacGAP ( also known as CYK-4 , RacGAP50C and MgcRacGAP; reviewed in [9] ) . Centralspindlin is thought to have a dual function in the initiation of cytokinesis . On one hand , the bundling activity of Mklp1 helps promote the stability of the midzone microtubule apparatus . On the other hand , RacGAP promote changes in actomyosin dynamics that result in the formation of the contractile ring and furrow constriction . In early zebrafish embryos , cytokinesis is associated with cytoskeletal rearrangements , one of which involves the formation of the contractile ring apparatus [10] . Furrow initiation is also associated with the assembly of the furrow microtubule array ( FMA ) , a structure that consists of microtubules originally organized parallel to each other and perpendicular to the plane of cleavage [10]–[13] . The FMA is thought to be functionally analogous to the bundles of midzone microtubules observed in other animal and plant systems [14] . During furrow maturation a second , myosin II-dependent phase of cytokinesis occurs which includes the movement of cortical cell adhesion junction components towards the furrow plane and the translocation of FMA tubules along the furrow plane towards the distal ends of the furrow [10] . In addition , during furrow maturation , localized exocytosis mediated by FMA tubules has been suggested to have a role in the formation of the new membrane septum between daughter cells [12] . In the animal embryo , the earliest cellular divisions are often coordinated with the segregation of localized maternal determinants that contribute to cell fate diversification . One of the earliest decisions commonly involves the specification of the germ line , via the acquisition of the germ plasm , a specialized cytoplasm that contains specific mRNA and protein products [15] . In zebrafish , the segregation of germ plasm components is intimately linked to the process of cytokinesis , as ultrastructurally defined germ plasm forms at the furrows of the first and second cleavage divisions [16] . Several mRNAs , such as those for the genes vasa [17] , dead end [18] , nanos [19] , daz-like [20] , bruno-like [20] , and askopos [21] , as well as Brul protein [22] , have been shown to be components of the zebrafish germ plasm . A subclass of germ plasm mRNAs , including vasa , dead end and nanos , is present in distinct aggregates at the blastodisc cortex during the first cell cycle [23] . These mRNAs undergo a complex segregation pattern immediately prior to and during furrow formation , including their pre-aggregation during the first cell cycle , their recruitment as rod-like structures at the incipient furrows , and the subsequent enrichment and compaction of the recruited germ plasm to the distal end of the maturing furrow [10] , [13] , [16] , [17] , [23] . The cellular mechanism involved in the recruitment of germ plasm aggregates during furrow formation remains poorly understood . Recent efforts have led to the isolation of recessive maternal-effect mutations in the zebrafish that affect a variety of early developmental processes , including the process of cytokinesis [24]–[28] . One of these mutations , in the gene cellular island ( cei ) was originally identified as essential for proper early cleavage divisions [25] . Here , we show that the cei maternal-effect mutation results in an aberrant allele of the zebrafish aurora B kinase ( aurB ) gene . Our data show that cei/aurB function is essential for furrow initiation in the blastomeres of the early embryo , and that different signals , mediated by spindle midzone and astral microtubules respectively , are important for the induction in medial vs . distal regions in the large cells of the early embryo . In addition , we show a role for AurB function in the reorganization of the microtubule apparatus at the furrow . Concordant with the requirement for cei/aurB in furrow induction , germ plasm recruitment to the cleavage furrows during the first two cell cycles is also affected in cei/aurB mutant embryos .
A mutation in the gene cellular island was originally isolated by its associated maternal-effect phenotype in the blastula stage zebrafish embryo . The initial analysis of this mutation showed that females carrying the cei mutation are viable and lack any obvious visible phenotype . However , all embryos from such mutant females , which we refer to as cei mutant embryos , are inviable , often exhibiting a mass or “island” of cells sitting atop an abnormally expanded syncytial region [25] . The expanded syncytium typically observed in cei mutant embryos is characteristic of early zebrafish embryos with defects in cell division [13] , [25] , [29] , [30] , which suggested that cei function is required for this process . In wild-type embryos , cells during the early cleavage stages divide by invagination of the membrane at the site of furrow formation ( shown for the first cell division in Figure 1A , arrowhead ) , which matures into an adhesive membrane septum during subsequent divisions ( arrowhead in Figure 1B shows the mature septum in the first cleavage furrow , at the 8-cell stage ) . Continuing cellular cleavage results in the normally cellularized blastula ( Figure 1C and 1D ) . cei mutant embryos typically lack the normal ingression of the forming furrow , showing instead a slight indentation where a furrow would normally develop ( arrowhead in Figure 1E ) . Consequently , cei mutants develop largely as syncytial embryos ( Figure 1F–1H ) . Labeling of 8-cell stage fixed embryos to detect ß-catenin , a component of cell adhesive junctions at the mature furrow [12] , and DNA corroborates the absence of adhesive membrane formation in cei mutant embryos , and shows that nuclear division proceeds normally ( Figure 1L–1N , compare to wild-type embryos in Figure 1I–1K ) . Thus , the cei mutation appears to interfere with furrow formation during cytokinesis . Although nuclear division appears normal in most cei mutant embryos ( Figure 1M , indistinguishable from wild-type in Figure 1J ) , a fraction of mutant embryos exhibit DNA bridges between daughter nuclei indicative of DNA segregation defects ( Figure 2B , compare to Figure 2A ) . Thus , the cei mutation interferes with furrow formation during cytokinesis and cei function may be additionally required for proper chromosome segregation . We noted that the severity of the maternal-effect cellularization defect varied in different females within families carrying the cei mutation . While some females showed a highly penetrant defect , in which all embryos lacked proper furrow formation in the first and subsequent cell cycles , clutches from other females showed much more variable defects ( Table 1; the severity of these defects has been classified according to the extent of cellularization in the 1 , 000 cell stage embryo , as shown in Figure 1O–1R ) . Genotyping of females using previously identified linked markers ( see Materials and Methods ) showed that the severity of the maternal-effect phenotype closely corresponds to the maternal genotype: females homozygous for the cei mutation produced strongly affected clutches in which furrows do not form in all or most embryos , while females heterozygous for the mutation produced clutches with cellularization defects varying from weak to undetectable ( Table 1 ) . Thus , the cei allele results in a highly penetrant recessive maternal-effect phenotype , as well as a partially dominant maternal-effect that leads to cellularization phenotypes of reduced penetrance . To better understand the basis of the cellularization defect observed in cei mutants , we visualized furrow-associated structures in wild-type and mutant embryos synchronized by in vitro fertilization . We first analyzed the microtubule-based cytoskeleton ( Figure 3A–3H ) . As previously described [12] , [13] , [23] , [31] , wild-type embryos exhibit a bipolar spindle and associated astral microtubules immediately prior to furrow formation ( 30 min postfertilization ( p . f . ) ; Figure 3A ) . During furrow initiation ( 33 min p . f . ) astral microtubules in wild-type embryos cover most of the blastodisc ( Figure 3B ) , leaving a distinct microtubule-free zone in the region corresponding to the initiating furrow ( arrowhead in Figure 3B′ ) . At 36 min p . f . , astral microtubules begin to form the FMA ( Figure 3C ) . The FMA persists during furrow maturation ( 51 min p . f . ; Figure 3D ) , which temporally overlaps the initiation of the second cell division cycle [10] , [12] , [13] . In cei mutant embryos , the bipolar spindle and associated asters appear to form normally and grow at a normal rate immediately prior to furrow formation ( 30 min p . f . , Figure 3E and 3F ) , although we can not rule out subtle changes in their structure or dynamics . However , mutant embryos show striking differences to wild-type beginning at furrow initiation . At 33 min p . f . , although microtubule asters in cei mutant embryos increase in length as in wild-type embryos , they do not yet form a distinct microtubule-free zone at the forming furrow ( Figure 3F ) . This lack of a microtubule-free region at the furrow is temporary , as a clearing of astral microtubules corresponding to the initiating furrow flanked by apparently normal FMA tubules appears at 36 min p . f . ( Figure 3G , arrowhead in Figure 3G′ ) . However , both the microtubule-free region corresponding to the initiating furrow and FMA tubules are completely absent in distal regions of the blastodisc . Furrows of subsequent cell cycles show similar defects ( Figure 3H and data not shown , see also Figure 4F ) . We also analyzed cei mutant embryos by labeling fixed embryos to detect f-actin , which becomes recruited to the forming furrow as part of the contractile ring apparatus [10] . Similar to the case of FMA formation , f-actin accumulation at the furrow only occurs in a shortened region centered in the middle of the blastodisc , and is absent in more distal regions ( Figure 3J , compare to Figure 3I ) . Thus , the rudimentary furrows formed in cei mutant embryos correspond to a shortened medially-located furrow and reflect a lack of furrow formation in the distal regions of the blastodisc . Further analysis of microtubules revealed that , in addition to the furrow initiation phenotype , cei mutants exhibit defects in FMA reorganization during furrow maturation ( Figure 4; [10] , [12] , [13] ) . In wild-type embryos , tubules of the FMA are arranged parallel to each other and perpendicular to the furrow when they are recruited to the forming furrow ( Figure 4A ) . During furrow maturation , tubules become enriched distally , acquiring a tilted angle with respect to the furrow itself , such that tubules abutting the furrow form V-shaped structures pointing towards the furrow distal end ( Figure 4B ) . At furrow completion , FMA tubules disassemble ( Figure 4C ) . In cei mutant embryos , FMA tubules become recruited with their normal conformation ( perpendicular to the furrow ) in the shortened medial region of the blastomere ( Figure 4D ) . However , these tubules fail to undergo the rearrangements and disassembly observed in wild-type embryos at later stages of furrow development ( Figure 4E and 4F ) , maintaining instead their original arrangement at a time when the FMA is fully disassembled in control wild-type embryos . This defect in FMA reorganization can also be observed in rare cei mutant embryos that exhibit a furrow of a normal length ( Figure 4G ) , suggesting that the absence of FMA reorganization in cei mutants is not a secondary consequence of the shortened furrow normally observed in these mutants . Our observations are consistent with a role for cei in cytoskeletal reorganization during furrow maturation . Linkage analysis of polymorphic DNA markers defined an approximately 16 cM region on chromosome 14 that contains the cellular island locus ( Figure S1A ) . A set of markers included within this region and located at position 2 . 30 cM in the MGH meiotic map were fully linked to the cei mutation in all 351 tested meioses . Analysis of the available zebrafish genomic databases revealed the presence of a serine/threonine kinase a ( stka ) gene with similarity to aurora kinases in the vicinity of these markers . Sequence comparison between zebrafish stka and other aurora kinase genes shows that stka is a likely homologue of aurora B kinase ( aurB; Figure S1B ) . Thus , we hereafter refer to zebrafish stka as zebrafish aurB . Sequencing of the aurB cDNA derived from mutant and wild-type embryos revealed a predicted amino acid change from a Valine to a Methionine at position 271 of the protein . The presence of a Valine at this position is absolutely conserved in all analyzed aurora B kinase homologues , including the fission yeast Schizosaccaromyces pombe , Arabidopsis , Caenorhabditis elegans , Drosophila and humans , but is not conserved in the more distantly related Polo like kinase 4 ( Figure S1C ) . This high level of amino acid conservation amongst Aurora kinase family genes suggests that a Valine at this position is crucial for their normal function . To confirm that cei encodes the zebrafish aurB homologue , we attempted to rescue cei mutants with a wild-type allele of aurB . We used Tol2-mediated transposition [32] to generate transgenic fish carrying the wild-type zebrafish aurB cDNA under the control of the Xenopus EF-1α promoter , which results in constitutive expression , including during oogenesis ( [33] , [34]; see Materials and Methods ) . Non-mosaic transgenic cei mutant females were identified by genotyping as described in the Materials and Methods and tested for cellularization defects in their progeny . The presence of the Tol-2/EF-1α-aurB transgene resulted in a significant rescue of the cei maternal-effect cellularization phenotype ( Figure 5 , Table 2 ) . For example , while sibling cei mutant females lacking the transgene never produced wild-type embryos , normally cellularized embryos are observed in clutches from 9 out of 15 females identified as carrying the Tol-2/EF1α-aurB transgene ( Figure 5B , compare to Figure 5A , Table 2 ) . Amongst these females , the frequency of rescue to normal cellularization is variable , but can be as high as 92% ( Table 2 , tg+#1 ) . The variable penetrance and expressivity of the rescue by the transgene may be due to differences in the number of transgene copies in the genome and/or positional effects resulting in different levels of transgene expression , since expression of transgenic constructs is known to be sensitive to positional effects ( [35]; our unpublished data ) . The function of wild-type aurB copies may also be counteracted by the antimorphic nature of the cei allele ( see below ) , additionally contributing to the observed variable rescue . Consistent with the rescue of the live phenotype by the transgene , ß-catenin accumulation is also restored at mature furrows of 8-cell stage embryos from cei homozygous , Tol-2/EF1α-aurB carrier females ( Figure 5D , compare to Figure 5C ) . Previous studies had identified two retroviral insertional mutations near the zebrafish aurora B kinase gene [36] . Homozygotes for both of these insertions show a brain necrosis phenotype detectable as early as 24 hours p . f . ( [36]; Figure 6B , compare to Figure 6A ) . We tested one of these mutations , originally named hi1045 , and determined by genomic sequence analysis that the retroviral insertion results in a premature stop codon that leads to the truncation of most of the kinase domain of the protein ( Figure S2 ) . Thus , this mutation is a likely null allele of aurora B kinase , which we denote aurBhi1045 . We also confirmed that a reduction in zygotic aurB function by antisense morpholino-conjugated oligonucleotide ( MO ) -mediated knock down [37] results in brain necrosis defects similar to those observed in embryos homozygous for the insertional mutations ( Figure 6C ) . To investigate if the brain necrosis phenotype in aurBhi1045 homozygote and aurB morphant embryos was caused by defects in cytokinesis , we labeled these embryos to detect nuclei and cell membranes ( Figure 7 ) . This analysis showed that , while cells in the developing wild-type brain appear organized in a regular lattice ( Figure 7A′ ) cells in the developing brains of aurBhi1045 homozygotes and aurB morphants show regions lacking cellular membranes and which contain high numbers of compact and brightly staining nuclei , which are typically clustered in pairs ( Figure 7B′ and 7C′ ) . Embryos with reduced aurB function also show defects in the enveloping layer , where a significant number of cells were binucleated or contained multilobular nuclei ( Figure 7B″ and 7C″ , compare to Figure 7A″ ) . aurBhi1045 homozygous mutant embryos also can show nuclei in close apposition which appear to lack an intervening cell membrane ( Figure 7E , compare to Figure 7D ) , presumably daughter cells which have failed cytokinesis . These observations are consistent with the idea that embryos lacking zygotic aurB function exhibit defects in cell division during later stages of embryogenesis , and with a similar function for maternal aurB in the pre-midblastula embryo . The pattern and morphology of nuclei in embryos lacking zygotic aurB function suggested that , in these embryos , cells that have failed proper cytokinesis undergo cell death . We confirmed this by labeling live embryos with the apoptosis marker dye acridine orange [38] . aurBhi1045 homozygotes show an increase in acridine orange labeling throughout their body , particularly in the brain region ( Figure S3B , compare to Figure S3A ) . We also tested whether inhibition of caspase activity , which has been shown to be required for cell apoptosis in zebrafish embryos [39] , could reduce the brain necrosis phenotype of aurBhi1045 homozygotes . Exposure to the general caspase inhibitor Boc-Asp ( OMe ) -fluoromethyl ketone ( Boc-D-FMK; [40] ) , results in a significant alleviation of the brain necrosis phenotype in aurBhi1045 homozygous embryos , as well as a reversal of the cell apoptosis phenotype as revealed by acridine orange labeling ( Figure S3D , Figure S3D′ , compare to Figure S3C , Figure S3C′ ) . Our data indicate that cells that fail to divide due to lack of cei/aurB function subsequently undergo cell apoptosis . To provide additional evidence that cei encodes aurB , and to further probe the genetic nature of the cei allele , we tested the cei maternal-effect allele and the aurBhi1045 insertional allele in genetic complementation assays . Embryos from crosses between parents carrying these two mutations appear normal at 24 hours p . f . and do not show the overt signs of brain necrosis observed in aurBhi1045 homozygous and morphant embryos . However , at day 5 p . f . , such intercrosses result in inviable embryos in Mendelian proportions consistent with the lethality of cei/aurBhi1045 transheterozygotes ( Table 3 ) . These inviable embryos showed defects such as a lack of swim bladder inflation , a protruding mouth and edema in the yolk region ( Figure 6E , compare to Figure 6D ) . Genotyping of individual embryos showed that cei/aurBhi1045 transheterozygotes are inviable at 5 days p . f . in almost all cases ( Table 3 ) . Thus , the cei maternal-effect allele and the aurB insertional mutation fail to complement each other , as expected if they affect the same genetic locus . Introduction of the Tol-2/EF1α-aurB transgene rescued the late zygotic lethality associated with cei/aurBhi1045 transheterozygotes ( Figure 6F , Table 3 ) , confirming that this lethality is caused by insufficient zygotic aurB function . The phenotypes exhibited by cei/aurBhi1045 transheterozygotes are similar to those often caused by late embryonic lethal mutations [41] or exposure to toxic agents ( e . g . [42] ) , suggesting that they may constitute a common phenotypic endpoint for defects in a variety of late developmental pathways . The precise nature of the underlying cause of the lethality of cei/aurBhi1045 transheterozygotes remains to be investigated . The observations that the phenotype in cei/aurBhi1045 transheterozygotes is not as severe as that present in embryos homozygous for the aurB insertional alleles , and that cei/cei homozygotes are viable , suggested that the cei allele retains some wild-type function that contributes to zygotic development . We further tested this possibility by expression of Cei/AurB products in aurBhi1045 homozygotes through mRNA injection at the one-cell stage . Expression of products corresponding to either the wild-type or the maternal-effect cei alleles significantly alleviates the brain necrosis defects of aurBhi1045 homozygotes ( Figure S4B , Figure S4C; compare to Figure S3A ) . In contrast , injection of mRNA coding for a mutated zebrafish cei/aurB product engineered to mimic a known kinase-dead , dominant negative AurB protein ( AurBK-R; [43] ) results in a brain necrosis defect stronger than that observed in aurBhi1045 homozygotes ( Figure S4D ) . Together with the complementation analysis , these results suggest that the maternal-effect cei/aurB allele encodes a partial loss-of-function product that can support cell division at late stages of development . In spite of the partial function retained by the cei maternal-effect allele , heterozygosity for this allele , but not for the aurB insertional ( null ) alleles , results in a dominant maternal-effect phenotype ( Table 1 ) . This suggests that under some circumstances the cei allele has defects that are more severe than those of a loss-of-function allele . It is possible that the maternal-effect cei allele exhibits a complex genetic behavior , acting as a dominant-negative ( antimorphic ) allele with respect to its maternal function , involved in early embryonic cytokinesis , and as a partial loss-of-function ( hypomorphic ) allele with respect to its function at later stages of embryonic development ( see Discussion ) . Further confirmation of the role of Cei/AurB in furrow initiation was obtained by exposure to the AurB inhibitor ZM2 [44] . Wild-type embryos treated with ZM2 during early development failed to undergo furrow contraction , forming instead rudimentary indentations similar to those observed in embryos from females homozygous for the cei mutation ( Figure S5 ) . The FMA showed a similar pattern of defects in ZM2-treated wild-type embryos and untreated cei mutants , specifically the short , centrally located furrows ( Figure S5B″ ) . In addition , a fraction of ZM2-treated embryos exhibited a complete absence of furrowing ( Figure S5B′ ) , although we are unable to distinguish whether these defects represent a delay in furrow initiation or a complete failure in furrow formation . Regardless of this uncertainty , these observations are consistent with a requirement of AurB for furrow induction . This pharmacological evidence provides further support for the idea that cei/aurB functions in furrow initiation in the zebrafish embryo . As in the case of cei mutant embryos , ZM2-treated embryos showed DNA bridges between daughter nuclei ( Figure 2D ) , indicative of DNA segregation defects . In situ hybridization showed the presence of uniformly distributed cei/aurB mRNA in the early embryo prior to the activation of the zygotic genome at the mid-blastula transition ( 512- to 1000-cell stage; [45] , [46] ) , indicative of its maternal origin ( Figure S6A , compare to labeling with sense probe in Figure S6B ) . Expression of cei/aurB is reduced immediately prior to gastrulation ( Figure S6C ) , presumably reflecting degradation of maternal mRNA and a lower level of zygotic transcription . During gastrulation ( Figure S6D ) and at the tail-bud stage ( Figure S6E ) , the relative levels of cei/aurB expression appear to correlate with an increase in cell number , suggesting that zygotic cei/aurB expression is ubiquitous . In the 24-hour embryo , significantly increased expression can be detected in the central nervous system ( Figure S6F ) . This may reflect a higher functional requirement for aur B function in this region due to a higher rate of cell division [47] , and is consistent with the brain necrosis phenotype caused by the reduction of zygotic aurB function . Thus , cei/aurB mRNA expression appears to be largely ubiquitous , reflecting an initial large supply of maternal transcript which , when depleted , is substituted by lower levels of zygotic transcript to support ongoing cell division during embryonic development . To visualize the subcellular location of Cei/AurB protein in the embryo , we generated an antibody against an N-terminal region of the protein , which differs in length and sequence amongst the various aurora kinase family members ( reviewed in [48] ) . Immunofluorescence analysis shows that Cei/AurB protein localizes to the forming asters and spindles during prometaphase and metaphase ( Figure 8A–8H ) . Astral microtubule and spindle localization remains detectable during anaphase ( Figure 8I–8L ) , although at this stage there appears to be a reduction of Cei/AurB protein at the spindle . During telophase ( Figure 8M–8P ) , coincident with furrow initiation and FMA formation , Cei/AurB protein begins to accumulate at the furrow , where it forms short filaments arranged perpendicular to the plane of the furrow ( arrows in Figure 8N′ ) . As the furrow undergoes maturation during cytokinesis ( Figure 8Q–8S ) , Cei/AurB can be observed in a punctate pattern along the plane of the furrow . Upon closer examination , this punctate pattern represents a collection of short filaments , as before arranged perpendicular to the furrow but now with an apparent greater labeling intensity ( arrows in Figure 8R′ ) , as well as larger aggregates ( asterisks in Figure 8R′ ) . Because FMA tubules are thought to be derived from astral microtubules ( compare Figure 8I and 8M ) , this localization pattern is consistent with an association of the Cei/AurB protein with plus ends of astral microtubules , as described in other systems [7] , [8] . Importantly , a comparison with the microtubule localization pattern indicates that the sites of Cei protein localization correspond to sites of greater microtubule bundling ( Figure 8Q′–8S′ ) . Moreover , the intensity and size of the Cei/AurB signals appears to correlate with the apparent number of microtubules undergoing bundling . Levels of furrow associated Cei/AurB become reduced at later stages of cytokinesis , when furrows are nearing their completion ( data not shown ) . These observations are consistent with a role for AurB in furrow initiation and maturation . The zygotic lethality associated with the cei/aurB null phenotype indicates a role for zygotically derived Cei/AurB protein in later stages of development . Therefore , we also analyzed Cei/AurB localization in embryos at the 15 somite stage ( 16 hours p . f . ; Figure 8T–8AE ) . We analyzed embryos derived from heterozygotes of the presumptive null insertional aurB mutation aurBhi1045 , such that the 25% of the progeny corresponding to the zygotically homozygous aurBhi1045 ( aurBhi1045/aurBhi1045 ) mutants could act as a control for the specificity of the antibody . As mentioned above ( see also Figure 7 ) , homozygous aurBhi1045 mutant embryos typically exhibit abnormal DNA morphology , such as highly condensed nuclei characteristic of apoptotic cells , which allow them to be distinguished from wild-type ( +/+ or aurBhi1045/+ ) embryos . Colabeling with an anti-α-tubulin antibody allowed visualization of the microtubule apparatus . In wild-type embryos , Cei/AurB protein localized to microtubule-based structures reminiscent of midbodies which were present at regions of cell-cell contact between presumed daughter cells at telophase ( arrowheads in Figure 8T , 8U , and 8W ) . Such structures were still observed in aurBhi1045 homozygotes , although the levels of Cei/AurB were either strongly reduced or absent ( arrowheads in Figure 8X , 8Y , 8AA; Figure 8AB , 8AC , 8AE ) . Intriguingly , although in wild-type embryos these midbody-like structures are highly compact ( arrowheads in Figure 8T ) , in homozygous mutant embryos a significant fraction of midbody-like structures were splayed in a noticeably less compact arrangement ( asterisk in Figure 8AB ) : 33% midbodies had a splayed morphology in mutants ( n = 75 midbodies , analyzed in 8 embryos ) , compared to 3 . 5% in sibling embryos ( n = 121 , analyzed in 16 embryos ) . These experiments suggest that zygotically-derived Cei/AurB protein specifically localizes to the midbody in cleaving cells of the later embryo and are consistent with a zygotic function of this protein in cytokinesis and midbody organization . As in early embryos with reduced AurB function , DNA bridges can also be observed in zygotically mutant embryos ( arrowhead in Figure 8Z ) , indicating a role for zygotic Cei/AurB function in DNA segregation in the later embryo . We also determined the localization of Cei/AurB protein in maternally mutant cei embryos . In these embryos , Cei/AurB protein exhibits an apparently normal astral and spindle localization ( data not shown ) and accumulates , as in wild-type embryos , at the ends of FMA tubules in the shortened furrow ( Figure S7A–S7C ) . Thus , the shortened furrows that form under conditions of reduced cei function are able to recruit Cei protein to its normal site of localization . This experiment also shows that , in spite of its presumed dominant negative character , the maternally mutant Cei/AurB product undergoes an apparently normal subcellular localization . Previous studies suggest that germ plasm granules present in the zebrafish oocyte cortex undergo a process of aggregation during the first cell cycle , dependent on the alignment of a cytoskeletal network to which they are bound [23] . In a wild-type embryo , aggregation occurs concomitant with furrow formation , such that a collection of larger aggregates , composed of collected smaller granules , becomes recruited to the forming furrow in an elongated rod-like structure ( Figure 9A and 9A′ ) . Because the cortex of the wild-type fertilized zygote contains a granule-free zone at its animal-most region , germ plasm recruitment occurs in the approximately 2/3 distal-most regions of the blastodisc ( [23]; Figure 9A and 9A′ ) . This rod-like structure later undergoes further aggregation as it forms a compact mass at the distal end of the maturing furrow ( [13] , [17] , [23] , [49]; Figure 9C and 9C′ ) . Because the distal furrow region where the germ plasm normally becomes recruited is precisely the region most sensitive to the loss of cei/aurB function , we expected to observe defects in germ plasm recruitment in cei/aurB mutant embryos . To detect germ plasm recruitment in the early zebrafish , we carried out fluorescent in situ hybridization labeling of wild-type and cei/aurB mutant embryos to detect vasa mRNA , a component of the zebrafish germ plasm ( Figure 9 ) . This technique allows detecting individual cortical germ plasm granules as they aggregate during the first cell cycle ( [23] – similar results , albeit with a reduced resolution , have been obtained using the standard color substrates , data not shown ) . In distal regions of the furrow , cei/aurB mutant embryos exhibited a reduction in germ plasm recruitment , often showing partially aggregated germ plasm granules that do not form well-defined rod-like structures ( Figure 9B , 9B′ , 9D , and 9D′ ) . Interestingly , germ plasm granules were often seen recruited as pairs of large aggregates in medial regions of the furrow and flanking the shortened furrow-like structure that forms in these mutants ( Figure 9D″ and data not shown ) . These experiments indicate that germ plasm recruitment depends on cei/aurB function , possibly because cei/aurB function is important for the organization of the cytoskeleton to provide a stable germ plasm anchoring structure . Moreover , this anchoring structure appears to be present in the shortened medial furrows that do form in cei/aurB mutants . The presence of medially located , shortened furrows in cei mutant embryos was intriguing , especially because such structures appeared otherwise relatively normal . This was particularly evident in the case of the FMA , where the length of the recruited microtubules themselves is similar to that of FMA tubules in wild-type embryos . Moreover , in cei mutants the length of FMA tubules is similar along the span of the truncated furrow , arguing that a sharp functional threshold may exist above which furrow structures form normally ( in medial regions ) and below which furrow structures do not develop ( in distal regions ) . We wondered why a shortened furrow forms in the medial region of the blastodisc in cei mutant embryos . Given previous work in other systems indicating redundant astral- and mitotic spindle-derived signals in furrow initiation [3] , [7] , [8] , one possible explanation for the shortened , medially located furrow is induction by the mitotic spindle in the absence of astral , cei-dependent signals . An alternative explanation is that astral microtubule density is higher in the medial region due to aster overlap , which results in an above-threshold AurB activity allowing furrow induction in medial regions . In order to discern between these two possibilities , we asked whether the shortened furrow that develops in cei mutants depends on a mitotic spindle-derived signal . For this purpose , we took advantage of another zebrafish maternal mutant , of the gene futile cycle ( fue ) , which lacks mitotic spindles ( in addition to having pronuclear fusion defects; [31] ) . In spite of these defects , fue mutant embryos undergo a relatively normal cell cleavage pattern , presumably driven by the normal cycle of centrosome duplication and aster formation [31] . Females maternally homozygous for both cei and fue mutations were generated through genetic crosses and identified through genotyping of flanking linked polymorphic DNA markers . Embryos from these females , produced through crosses to wild-type males , did not show any sign of furrow formation ( not shown ) . Because such embryos could not be distinguished from normal , unfertilized eggs , we labeled fixed samples to detect sperm-derived structures such as the male pronucleus and the sperm-dependent centrosome . Fixed double mutant embryos were labeled to detect pronuclei with a DNA stain , centrosomes with an anti-γ-tubulin antibody , and microtubules with an anti-α-tubulin antibody ( Figure 10 ) . Imaging of double mutant embryos revealed the presence of two pronuclei and dividing centrosomes , demonstrating that these embryos had been fertilized and were undergoing centrosomal duplication cycles ( Figure 10F and 10G ) . However , in spite of a normal centrosome duplication pattern , furrow associated structures , such as the FMA , were completely lacking in double mutant embryos ( Figure 10E , compare to Figure 10A ) . These results suggest that the shortened furrows observed in cei mutant embryos are induced by a spindle-derived signal . Double labeling experiments show that , in fue single mutant embryos , both FMA formation and Cei/AurB protein localization to the furrow appear normal and occur throughout the span of the blastodisc ( Figure S7D–S7F ) , and that Cei/AurB protein localizes to the forming asters at earlier stages of the cell cycle ( data not shown ) . This is consistent with Cei/AurB protein being solely provided by astral microtubules in these mutant embryos , which lack a spindle apparatus . Together , our results provide further support for models where furrow induction depends on redundant signals derived from the aster and spindle microtubules . Moreover , our data indicate that in large cells such as in the early zebrafish embryo , these redundant structures may have distinct roles in medial vs . distal regions of the cell . Specifically , the maternal-effect cei mutation affects furrow initiation in distal region of the blastodisc , while furrow initiation in medial regions may depend on redundant astral and midzone-derived signals .
It is remarkable that embryos from cei mutant females typically display a shortened furrow-like structure in the medial region of the blastodisc , but a complete lack of furrowing in more distal regions . Interestingly , Cei/AurB protein is found throughout the length of the furrow of the early embryo , and exposure to the AurB inhibitor ZM2 can result in a complete absence of furrow induction . Thus , our observations suggest that AurB function is important throughout the length of the furrow , but that the medial region of the furrow is more resilient to a partial loss of AurB activity ( as in the case of the cei mutation ) than distal regions . Because the region of maximum overlap of astral microtubules is at the center of the forming furrow , one explanation for the spatially limited furrow in cei mutants is an increased density of astral microtubule ends , and consequently astral-derived signals , in the center of the blastodisc . An alternative explanation for the spatially restricted furrow induction phenotype is that medial furrow regions , which may be influenced by the centrally located mitotic spindle , are induced by redundant mechanisms mediated by both astral and spindle microtubules . We discriminated between these two possibilities by examining furrow formation in cei mutants in a background also mutant for futile cycle , which additionally lack mitotic spindles but have normal astral microtubules . In cei; fue double mutants , the cell cycle proceeds normally , as reflected by the pattern of centrosome duplication , but furrow initiation is completely abolished both in distal and medial regions of the blastodisc . Thus , our data supports previous findings that spindle and astral microtubules act together to induce furrows in the C . elegans embryo [3] , [4] and in HeLa cells [5] , and shows that a similar redundancy occurs in the early zebrafish embryo . Our analysis shows for the first time that these signals are spatially dedicated: the spindle-derived signal ( s ) having an influence only in medial regions of the blastomere , while astral-derived signal ( s ) are essential for furrow initiation in more distal regions ( Figure 11 ) . It is possible that this dual mechanism arose in order to form a furrow throughout the span of the large blastomeres of the early vertebrate embryo . Spatial differences in the molecular machinery may also be important to generate asymmetries important for embryonic development , for example , in the segregation of localized determinants to specific locations of the zygote . While our results indicate that Cei/AurB protein is essential for the astral-mediated furrow-inducing signal , they do not rule out a role for Cei/AurB as a mediator of a spindle-derived signal . Indeed , both the spindle localization of Cei protein and drug inhibition experiments suggest that this protein may also be at least partially involved in mediating a spindle-derived furrowing activity . Further analysis will be required to determine the precise molecular nature of these two sets of partially redundant signals . The unusual genetic behavior of the maternal-effect cei mutation , in comparison to that of null insertional alleles , is intriguing . On one hand , the cei mutant allele appears to retain some aspects of wild-type function . For example , the aurB null phenotype is zygotic lethality involving brain necrosis detectable at 24 hours p . f . , but embryos homozygous for the cei mutant allele ( derived from cei/+ heterozygous parents ) are viable and can reach adulthood . Similarly , transheterozygotes for the cei maternal-effect mutation and null alleles do not exhibit early brain necrosis and survive until day 5 p . f . In addition , expression of the product corresponding to the maternal mutant cei allele , as is also the case with the wild-type allele , is able to ameliorate the zygotic brain necrosis defect caused by homozygosity for a null cei/aurB allele . Thus , multiple lines of evidence indicate that the cei maternal-effect allele retains sufficient wild-type function to partially support cell division during zygotic development . On the other hand , maternal heterozygosity for the cei mutation , but not for the aurB insertional alleles , results in a significant dominant effect in cytokinesis in the early zygote . Although we can not rule out the possibility that this contrasting genetic behavior is due to genetic background differences , these results suggest that , with regards to a maternal-effect , the cei allele may have a dominant negative character . This apparent dominant negative effect can be mimicked by treatment with a small molecule AurB inhibitor , indicating that the underlying cause of the defect is the inhibition of endogenous AurB function . Together , these data suggest that the mutation in the cei maternal-effect allele may specifically interfere with aurB function and cytokinesis during the early cleavage divisions while largely retaining normal aurB function during later embryonic development . This finding suggests possible mechanistic differences in furrow formation pathways between large blastomeres in the early embryo and smaller cells at later stages . Potential bases for this differential functional requirement may originate on specific constraints for cell division in the early zygote , for example an increased reliance on astral-derived signals for furrow induction in the larger early blastomeres , differences in cell cycle length , or a different architecture of the furrow associated microtubule cytoskeleton ( FMA vs . midbody ) during furrow maturation . Regardless of potential differences in its function in early and late embryonic development , cei/aurB function appears to have a crucial role in cytokinesis in both early and late embryos . The observation that the first defects seen in zygotic null aurB mutants occur in the brain region may reflect the fact that this region contains the most actively dividing cells in the developing embryo . Increased rates of cell division would in turn lead to faster depletion of maternally provided protein supplies , as previously suggested for other general cell cycle genes [47] . One of the manifestations of this phenotype is cell death in the brain region . We show that this cell death is associated with cells typically arranged in pairs and which exhibit DNA morphologies characteristic of apoptotic cells . Our observations in zebrafish are consistent with previous reports that inhibition of aurB function results in cell death [44] . The extensive cell death caused by loss of zygotic aurB function in these null mutants contrasts with the lack of any such effects after aberrant cytokinesis during the cleavage stages in cei mutant embryos . It has been proposed that early zebrafish embryonic cleavage divisions lack cell cycle check points [39] , [50] , [51] , which may explain the ability of the early embryo to continue nuclear division in the absence of cytokinesis without entering the apoptotic program . Thus , cells in early and late embryos may differ not only in their precise mechanisms of cytokinesis but also in the cellular response to failures in these mechanisms . In wild-type zebrafish embryos , furrow formation and maturation is accompanied by striking cytoskeletal rearrangements , involving the reorganization of the actin and microtubule-based cytoskeleton and the formation of cell adhesion junctions [10] , [12] . Some events associated with early furrow formation , such as the formation of the FMA , occur normally in the partial furrows observed in cei mutants . However , subsequent events associated with furrow maturation do not occur normally in these mutants . The FMA , for example , does not undergo the tilting , distal enrichment and eventual disassembly characteristic of wild-type embryos , and instead remains as a stabilized structure containing parallel microtubules . Two observations suggest that the FMA reorganization defect in cei mutants is not simply a consequence of the shortened , medially located furrows . First , this cytoskeletal reorganization defect occurs even in embryos showing a weak effect where the furrow encompasses the entire blastomere . Secondly , FMA tubules can become locally reorganized even in short and medially located stretches of a furrow , as in the case of nebel mutant embryos [13] . Thus , our observations are consistent with a role for cei/aurB function in cytoskeletal reorganization during furrow maturation . Such a role is also supported by our observations that , during later embryonic development , mid-body like structures in embryos with reduced AurB function often exhibit a splayed phenotype . It is possible that both the lack of FMA reorganization in early blastomeres and the splayed midbody phenotype in later cells are caused by reduced microtubule bundling . In support for this idea , we have found that Cei/AurB protein normally colocalizes in patches and short segments perpendicular to the cleavage plane along the maturing furrow , and that these localization domains coincide with the tips of bundling FMA tubules . The idea that Cei/AurB mediates microtubule bundling is consistent with studies that show a role for the Chromosomal Passenger Complex proteins in spindle formation and microtubule bundling during the initiation of cytokinesis [52]–[55] . To our knowledge , this is the first evidence that suggests a role for AurB in microtubule reorganization at later stages of furrow formation , important for furrow maturation and completion . In this respect , the large cytoskeletal rearrangements present in the early zebrafish embryo may provide a useful system to study this function . AurB is known to regulate the activity of microtubule bundling factors such as Mklp1 [56] , [57] , and Mklp1 is required for cytokinesis in the early zebrafish embryo [58] . Further research , including live imaging and ultrastructural analysis of the microtubule network , will address and attempt to fully validate a role of zebrafish cei/aurB and other factors such as Mklp1 in microtubule bundling . Consistent with the lack of distal furrows in cei mutant embryos , germ plasm granules exhibit reduced aggregation in these regions . Instead , germ plasm aggregates accumulate in paired structures flanking the medially located shortened FMA . Germ plasm recruitment at the edges of the shortened furrow in cei/aurB mutants , but not in more distal regions , suggests that furrow formation signals promote the establishment or stabilization of anchors for germ plasm recruitment ( Figure 11 ) . Of interest , the shortened spindle-dependent furrow present in cei mutants appears to be as effective as a wild-type , full-span furrow with regards to germ plasm recruitment , suggesting that induction by either spindle- or astral-dependent signals results in similar furrow architectures and/or functions . In addition to a role for cei/aurB function in furrow initiation , and therefore germ plasm recruitment , our findings suggest a role for this gene in cytoskeletal rearrangements during furrow maturation , namely the tilting and distal enrichment of FMA tubules . As this FMA reorganization is associated with the translocation of germ plasm to the distal ends of the furrow and its higher-level aggregation in these regions [10] , cei/aurB function may also be important for this later step in germ plasm segregation . In summary , we show that a maternal-effect allele in cellular island is caused by a mutation in the zebrafish aurora B kinase homologue . Functional analysis of this gene indicates that aurB is essential for various functions involved in cell division in the early embryo , including furrow formation and germ plasm recruitment , and is also required for cell division during later stages of embryogenesis . We further show that a dual system , involving astral- and spindle-derived signals and mediated at least in part through cei/aurB function , ensures furrow formation throughout the length of the large blastomeres of the early embryo . Finally , we provide evidence that supports a role for aurB in microtubule reorganization during late stages of cytokinesis .
Wild-type stocks were the standard AB . Fish and embryos were raised and maintained under standard conditions at 28 . 5°C [59] . Fish carrying the cei allele ( ceip63cd ) were genotyped by using the flanking linked markers z10673 and z51215 or direct sequencing of the PCR fragment of genomic DNA amplified using the following primers: 5′-GCATCCCAACATCCTTCGCTTCTAC-3′ and 5′-AGTAGCAGTGCGCTGATCGTCAAAG-3′ to detect the mutation site . In vitro fertilization was carried out as previously described [24] . Females doubly homozygous for the cei/aurB and fue mutations were produced by crossing cei homozygous males to heterozygous fue females . Linked markers were used to identify double heterozygotes from this original cross and these individuals were then mated to produce full homozygous double mutants . Genetic identity of the cei; fue mutants was confirmed using RFLP markers corresponding to the polymorphic bases responsible for each mutant phenotype . All animals were handled in strict accordance with good animal practice as defined by the relevant national and/or local animal welfare bodies , and all animal work was approved by the appropriate committee ( University of Wisconsin - Madison assurance number A3368-01 ) . Males heterozygous or homozygous for the cei mutation were crossed to wild-type WIK females to generate F1 families , which were incrossed to obtain homozygous F2 fish [60] . The early cell cleavage phenotype of F3 embryos allowed determination of the genotype of F2 females with respect to the cea mutation , which was compared to the segregation of flanking SSLP markers . Two fragments of aurB cDNA covering the entire AurB coding region were amplified from one-cell stage cei mutant embryos by RT-PCR using the following restriction enzyme recognition sequence attached primer pairs: N-terminal fragment: 5′-ggaattcCGAAACACACACACACACACG-3′and 5′-gggtcgacGTTCTCCTCTGTATCCCAGC-3′; C-terminal fragment: 5′-ggaattcAGAAGGTGATCCACAGAGAC-3′ and 5′-gggtcgacAGGTGTGTGTATATGCCAGG-3′ . These fragments were cloned into the EcoR1/Sal1 digested pBluescript SK ( + ) vector and sequenced . To confirm linkage between the cei mutation and the mutation in aurB , we amplified a partial sequence of aurB containing the mutation region by PCR using the primers described in the Genetics stocks and methods subsection . Sequencing of the aurBhi1045 allele was carried out using genomic DNA from the insertional line as specified in [36] . For the detection of tubulins and ß-catenin , dechorionated embryos were fixed and labeled as previously described [23] using microtubule fix buffer and the following primary antibodies: anti-α-tubulin ( Sigma , monoclonal B5-1-2 , 1∶2500 ) , anti-γ-tubulin ( Sigma , monoclonal GTU-88 , 1∶2000; Sigma , rabbit polyclonal , 1∶2000 ) , and anti-ß-catenin ( Sigma , rabbit polyclonal , 1∶1000 ) . The primary antibodies were recognized using Alexa 488- or Cy3-conjugated secondary antibodies ( Molecular Probes , Jackson Immuno Research Laboratories ) . Staining of f-actin was determined using Alexa-488 phalloidin ( Molecular Probes ) as in [10] . Subsequently , embryos were labeled for DNA using DAPI ( 0 . 5 µg/ml in PBS ) for 10 minutes at room temperature or propidium iodide ( described in [13] ) . In situ hybridizations were carried out as described previously [61] using vasa [17] or cei/aurB RNA probes . The cei/aurB antisense probe was generated by the EcoR1 digestion of pBS-N terminal-aurB ( see Positional cloning subsection ) with T7 polymerase . Anti-Cei/AurB was generated by immunizing rabbits against a KLH-conjugated peptide containing the first 29 amino acids of zebrafish AurB ( Harlan Laboratories ) . Preabsorbed antibody was used on embryos fixed with microtubule fix at a 1∶100 dilution . An acridine orange ( Sigma ) stock solution was made at 4 mg/ml in water and dechorionated embryos were exposed to 0 . 4 mg/ml in embryonic medium for one hour . Embryos were subsequently washed extensively with embryonic medium prior to imaging . Live and fluorescently labeled single embryos were imaged using a Zeiss Axioplan2 fluorescent microscope and Open Lab imaging software . Images of embryos labeled using in situ hybridization and groups of live embryos were acquired using a Leica-FLIII and a color camera ( Diagnostic Instruments Spot Insight ) . Confocal microscopy was carried out using a Zeiss LSM 510 confocal microscope and the acquired images were processed using Image J software . ZM2 ( ZM44739 , Tocris Bioscience ) was dissolved in DMSO at a concentration of 20 mM . Dechorionated embryos were exposed to 400 µM ZM2 diluted in embryonic medium starting at 25 min after fertilization until fixation at the indicated stage . The general caspase inhibitor Boc-Asp ( OMe ) -fluoromethyl ketone ( Boc-D-FMK; Sigma ) was dissolved in DMSO at a concentration of 20 mM , and dechorionated embryos were exposed to 400 µM Boc-D-FMK in embryonic medium beginning at 17 hours p . f . until indicated . For drug exposure experiments , control embryos were exposed to a similar concentration of carrier solvent ( DMSO ) . AurB morphant embryos were generated by microinjection at the one-cell stage of 0 . 5 ng MOs of the following sequence: 5′ CGGTTTTCTTTATTCTGCATGGCG 3′ ( GeneTools ) . For overexpression of wild-type and maternal-effect cei allele , cDNAs corresponding to these two alleles were cloned into pCS2 . The AurB ( K-R ) expression vector was generated by substituting in the wild-type allele a lysine ( AAG ) at amino acid position 82 by an arginine ( AGG ) through PCR-based directed mutagenesis , to recreate a kinase dead dominant negative mutation [43] . In vitro transcribed mRNA was prepared and injected at a concentration of 0 . 5 ug/ul as previously described [61] . The full-length wild type cei/aurB cDNA was cloned into the pT2KXIGDin vector under the expression of the EF1α promoter [34] . DNA for the resulting construct , Tol-2/EF-1α-aurB , together with Tol2-transposase , was injected into embryos derived from crosses between zygotically cei homozygous males and heterozygous females to produce individuals that were carriers for both the mutation and the transgene . In these injections , 25 pg of plasmid DNA was injected into one-cell stage embryos together with 50 pg of in vitro transcribed Tol2 transposase mRNA [62] . Founder individuals carrying the transgene were identified by PCR-based genotyping and were intercrossed to generate homozygous cei mutant females that are Tol-2/EF1α-aurB non-mosaic carriers . The presence of the transgene in transgenic fish was detected by PCR using following primers: ( 5′-GAAGAAGGTGATCCACAGAGAC-3′ and 5′-AAACACTCGTAGCACAGCACAC-3′ ) . | The molecular details driving the splitting of cells in two during cell division , known as cytokinesis , remain incompletely understood , as is the coordination of this process with events that pattern the early animal embryo . The dearth of our knowledge in this subject is particularly evident in the case of vertebrate embryonic development . This is in large part because of challenges associated with the identification and characterization in vertebrate systems of the responsible genes , which are expressed during oogenesis . We have carried out genetic screens to identify in an unbiased manner maternal-effect genes required for early zebrafish development . Here we report the molecular genetic analysis of one such gene , cellular island . We show that cellular island encodes the chromosomal passenger complex protein Aurora B kinase and that its function is essential for furrow induction and maturation in the zebrafish embryo . Genetic analysis involving mutations in this gene and a maternal-effect gene required for spindle formation shows the presence of spatial and temporal specializations in furrow induction signals and cellular island/aurora B kinase function in the early embryo . | [
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] | 2009 | The Maternal-Effect Gene cellular island Encodes Aurora B Kinase and Is Essential for Furrow Formation in the Early Zebrafish Embryo |
Rabies is a serious yet neglected public health threat in resource-limited communities in Africa , where the virus is maintained in populations of owned , free-roaming domestic dogs . Rabies elimination can be achieved through the mass vaccination of dogs , but maintaining the critical threshold of vaccination coverage for herd immunity in these populations is hampered by their rapid turnover . Knowledge of the population dynamics of free-roaming dog populations can inform effective planning and implementation of mass dog vaccination campaigns to control rabies . We implemented a health and demographic surveillance system in dogs that monitored the entire owned dog population within a defined geographic area in a community in Mpumalanga Province , South Africa . We quantified demographic rates over a 24-month period , from 1st January 2012 through 1st January 2014 , and assessed their implications for rabies control by simulating the decline in vaccination coverage over time . During this period , the population declined by 10% . Annual population growth rates were +18 . 6% in 2012 and -24 . 5% in 2013 . Crude annual birth rates ( per 1 , 000 dog-years of observation ) were 451 in 2012 and 313 in 2013 . Crude annual death rates were 406 in 2012 and 568 in 2013 . Females suffered a significantly higher mortality rate in 2013 than males ( mortality rate ratio [MRR] = 1 . 54 , 95% CI = 1 . 28–1 . 85 ) . In the age class 0–3 months , the mortality rate of dogs vaccinated against rabies was significantly lower than that of unvaccinated dogs ( 2012: MRR = 0 . 11 , 95% CI = 0 . 05–0 . 21; 2013: MRR = 0 . 31 , 95% CI = 0 . 11–0 . 69 ) . The results of the simulation showed that achieving a 70% vaccination coverage during annual campaigns would maintain coverage above the critical threshold for at least 12 months . Our findings provide an evidence base for the World Health Organization’s empirically-derived target of 70% vaccination coverage during annual campaigns . Achieving this will be effective even in highly dynamic populations with extremely high growth rates and rapid turnover . This increases confidence in the feasibility of dog rabies elimination in Africa through mass vaccination .
Rabies is a serious yet neglected public health threat in resource-limited communities in sub-Saharan Africa [1] . In these settings , the virus that causes this deadly disease is largely maintained in populations of free-roaming domestic dogs , and is transmitted to people through bites or other contact with the saliva of infectious rabid dogs . Rabies in dog populations ( and consequently in humans ) can be controlled and in certain circumstances eliminated through the mass vaccination of dogs against the virus [2] . The control of an infectious disease through vaccination relies on vaccinating a sufficient proportion of the host population to effect herd immunity: the phenomenon whereby the risk of infection among susceptible individuals in a population is reduced by the presence of immune individuals [3] . Thus , if a threshold proportion of individuals in a population are immune , the incidence of infection in that population will decline , eventually to zero [3] . This critical vaccination threshold is a function of the basic reproductive number R0; that is , the number of secondary cases of infection generated by a typical infectious individual in an otherwise fully susceptible population [4] . Hampson et al . [5] estimated R0 for outbreaks of rabies in domestic dog populations around the world . From their estimates ( R0 < 2 ) , they calculated the critical vaccination threshold for rabies to be lower than 40% in the populations reviewed . Thus , theory and empirical evidence predicts that outbreaks of rabies in dogs can be controlled if at least 40% of the population is immune at any time . However , achieving this goal in free-roaming dog populations in resource-limited communities is hampered by the rapid turnover of these populations , compounded by the lack of affordable and accessible veterinary services . In these areas , mass dog vaccination against rabies is usually implemented by the state or other agencies in annual or less frequent campaigns , of relatively short duration . Between campaigns , the proportion of immune individuals in the population declines as vaccinated dogs die and susceptible dogs enter the population through birth or migration . To maintain population immunity above the critical threshold in the period between campaigns requires that a larger proportion of the dog population be vaccinated during campaigns [5] . The actual target vaccination coverage to be achieved during campaigns is thus dependent on the demographic rates of the dog population , as well as the interval between campaigns and the duration of vaccine-induced immunity . The World Health Organization ( WHO ) recommends that , to achieve control and eventual elimination of dog rabies , programmes must ensure that mass dog vaccination campaigns achieve a vaccination coverage of at least 70% of the population in a given area , and that such campaigns recur , usually annually [6] . The figure of 70% is an empirically-derived consensus , stemming from work on the control of dog rabies in New York State during the 1940s [7] . It is assumed that this coverage , achieved during a campaign of relatively short duration , is sufficient to maintain the population immunity above the critical threshold for at least 12 months , despite dog population turnover due to births , deaths and migrations during this period [6] . To date , little work has been done to test this assumption using real data on demographic rates from free-roaming dog populations in rabies-affected communities . Using demographic characteristics for a cohort of owned dogs over a 12-month period in northwest Tanzania , retrospectively collected through household questionnaires , Hampson et al . [5] estimate that a target vaccination coverage of 60% is sufficient to avoid coverage falling below the critical threshold of 40% between annual campaigns . Using prospective cohort studies in four populations of owned , free-roaming dogs in South African and Bali , Indonesia , Morters et al . [8] estimate that 60–70% coverage is sufficient for the same purpose . Knowledge of the population dynamics of free-roaming dog populations , particularly the core demographic rates of birth , death and migration , may therefore help to inform effective planning and implementation of mass dog vaccination campaigns to control rabies in resource-limited communities , and to design strategies for the eventual elimination of dog rabies and associated human deaths . Knowledge of these rates , and their interplay with population vaccination coverage levels , may also improve understanding of the possible contribution of humane dog population management to rabies control efforts [9 , 10] . Despite the ubiquity of free-roaming dogs in sub-Saharan Africa , little is known about the demographic rates of these populations , or the factors that affect them . Studies that have provided estimates of demographic parameters of these populations have largely relied on cross-sectional household questionnaire surveys of dog owners [5 , 11–13] . These analyses make certain assumptions which may not hold true , such as stable age- and sex-distributions or consistency of demographic rates over time . In addition , human-mediated migration of domestic dogs may play an important role in population dynamics and rabies epidemiology [11 , 12 , 14–18] , yet few studies have examined the contribution of migration to population turnover . A number of studies of free-roaming dog populations in communities in Africa have revealed that , despite appearances , there is little evidence for the presence of large numbers of unowned dogs in these populations [11 , 12 , 16–19] . Adequate demographic surveillance of dog populations is therefore possible through on-going monitoring of owned dogs within households [8] . Here , we report data from a demographic surveillance system covering all owned dogs in a rabies-affected , resource-limited community in South Africa . Data span a 24-month period , from 1st January 2012 through 1st January 2014 . The aim of the study was to quantify demographic parameters in this population of dogs , particularly the core demographic rates of births , deaths and migrations , and to assess the implications of dog population dynamics for rabies control through mass vaccination .
The data collection method used in our study follows the model of health and demographic systems in human public health . A health and demographic system ( HDSS ) monitors all individuals , households and residential units in a defined geographic area , known as a demographic surveillance area ( DSA ) ( www . indepth-network . org ) . HDSSs are used in the field of public health , to meet the need for reliable population-based data on health in many low- and middle-income countries where there is limited registration of vital events , including births , deaths ( by age and sex ) , and medical causes of death [20] . The overall objective of these HDSS sites is to establish a reliable information base to help policy-makers set health priorities and allocate resources more efficiently . Following an initial census of the defined population in which all residential units and occupants are enumerated , longitudinal measurement of demographic and health variables is undertaken through repeated visits at regular intervals to all residential units within the DSA . We applied this model to create a health and demographic surveillance system in dogs ( HDSS-Dogs ) in a population of owned , largely free-roaming dogs in a resource-limited community in South Africa . The aim of the HDSS-Dogs is to provide long-term , reliable , population-based data for evidence-based approaches to the control and elimination of dog rabies , and for humane dog population management in resource-limited communities . The DSA of the HDSS-Dogs ( Fig 1 ) was arbitrarily defined prior to the start of the study , making use of natural and man-made features recognisable on the ground by field teams . The DSA encompasses Hluvukani settlement ( S 24°39’; E 31°20’ ) , which includes parts of two administrative areas ( Eglington and Clare A villages ) in Bushbuckridge Local Municipality , Mpumalanga Province , South Africa . The total human population of Bushbuckridge Municipality in 2011 was 541 , 249 , with a growth rate of 0 . 79% from 2001–2011 [21] . Over two thirds of the population aged 20 years and older had not completed secondary school . The unemployment rate in Bushbuckridge in 2011 was 52 . 6% , substantially higher than the national rate of 29 . 8% . The majority of the population ( 96% ) lives in formal housing , with a mean household size of 4 . 0 persons . One fifth of households do not have access to piped water , and fewer than 10% to refuse removal services . The mean annual household income in 2011 was ZAR 36 , 569 ( about US$ 5 , 000 ) , less than half of the mean annual income for the province as a whole [21] . In Hluvukani , families live in houses on separate stands ( a stand is a plot or parcel of land ) . Stands are permanently identified by municipal stand numbers that are unique within each administrative area . Stands without municipal numbers were assigned a unique number by the study team . All stands in the DSA are georeferenced as part of the study . There are no private veterinary services in the study area . The provincial state veterinary services have strengthened regular dog rabies vaccination campaigns since the disease re-emerged in Bushbuckridge in 2008 , after a long period of apparent absence [22] . In addition to the veterinary services provided by the state , the animal health needs of the community in Hluvukani and the surrounding areas are also met at a subsidised rate by the Hluvukani Animal Clinic , located in the centre of Hluvukani and run by the Faculty of Veterinary Science of the University of Pretoria ( UP ) . The majority of dogs in the community have the morphological appearance of the Africanis landrace [23] , although there is some phenotypic evidence of interbreeding with western breeds . An initial census of the dog population was conducted from July through October , 2011 . This census was combined with a house-to-house rabies vaccination campaign in conjunction with the provincial veterinary services and the Faculty of Veterinary Science , UP . To uniquely and permanently identify individual dogs , microchips ( BackHome BioTec , Virbac RSA ) were subcutaneously implanted into dogs present at the start of the study , and into those dogs that entered the population during the study period . Dogs that could not be handled to implant a microchip were assigned a unique identification code . Dogs were also identified by name and appearance . All dogs enrolled in the study were photographed . Following the census ( Round 1 ) , five follow-up rounds ( Rounds 2–6 ) were conducted from December 2011 through May 2014 , resulting in all households being visited approximately every six months during this period . All households in the DSA were visited during each round . All owned dogs were recorded at each visit , as were the demographic events that occurred in the period between visits , including births , deaths , and migrations into and out of households . Data including sex , age and rabies vaccination status were collected during the census for all dogs and at each round for new dogs . For vaccination history , we used owners’ reports . Although vaccination certificates are issued by the veterinary services , not all owners consistently keep such certificates . Vaccination data of the veterinary services are aggregated at a local administrative level , and are not always readily available for individual dogs . Dogs vaccinated at any point in the preceding 36 months were considered vaccinated [24 , 25] . Variables with time units ( e . g . age , or time since entry or exit of a dog ) were estimated by the owners . Owners were asked to give a lower and upper estimate , in the time unit of their choice ( days , weeks , months , years ) , reflecting the precision of their estimate . The date of the event was assigned as the midpoint of the estimated range , and the range of the estimate converted to days . All ‘residence episodes’ of individual dogs in households were tracked and aggregated to produce the denominator of dog-time in the population . Residence episodes within households begin with birth or in-migration ( e . g . purchase or receipt of a new dog ) , and terminate with death or out-migration ( e . g . sale or gifting of dog to another household ) . Data from 1st January 2012 through 1st January 2014 are presented here . Data are presented in 3-month periods ( annual quarters , abbreviated Q ) . Point data are provided for the first day of each quarter . Mortality rates were determined as the total number of deaths in a defined population during a specified period , divided by the total number of dog-years lived in the same sub-population over the same period . The subpopulations were characterized by three variables: sex ( male or female ) , age class ( 0–3 months , 4–11 months , 12–23 months , 24–35 months , ≥36 months ) , and rabies vaccination status ( unvaccinated or vaccinated ) . Time periods were 2012 and 2013 . If dogs changed subpopulations over time , they were split in different records; each record is independent as it describes the dog in one or other specific subpopulation . To model mortality rates in the subpopulations across the two periods , we fitted a Poisson regression model in R [26] . For each record , the number of dog-days was calculated and the log ( dog-days ) included in the regression as an offset . The four variables ( sex , age class , vaccination status and year ) as well as all possible interactions ( two- , three- and four-way ) were included in a maximal model . Model simplification was done by stepwise removal of non-significant variables from the maximal model , starting with the highest-order interactions , and examining the resulting change in deviance of the model . Variables whose removal did not result in a significant change in deviance ( p>0 . 05 ) were dropped from the model . Mortality rate ratios ( MRR ) and confidence intervals were calculated from the final minimal adequate model . To assess whether a 70% vaccination coverage achieved during annual campaigns is sufficient to maintain population immunity above the critical threshold of 40% for a 12-month period , we simulated two hypothetical vaccination campaigns , one on 1st January 2012 and another on 1st January 2013 . We randomly assigned a positive vaccination status to 70% of all dogs present in the population on those dates . The number of these vaccinated dogs still present in the population 12 months later was divided by the total number of dogs in the population on that date , to give the vaccination coverage one year later . The process of random assignment was repeated 1 , 000 times to produce Monte Carlo estimates of vaccination coverage . Similarly , we assessed the minimum proportion of dogs to be vaccinated during campaigns on the 1st January 2012 and on the 1st January 2013 required to ensure a 40% coverage in the population 12 months after the respective dates . The study was approved by the University of Pretoria Animal Ethics Committee ( protocol no . V033-11 ) . Written informed consent was obtained from dog owners to participate in the study . The protocol adhered to the specifications in the South African National Standard ( SANS 10386–2008 ) : “The Care and Use of Animals for Scientific Purposes” .
The area of the DSA is 10 . 4 km2 . There are a total of 2 , 373 stands in the DSA , including 68 empty or non-residential stands ( Fig 1 ) . Stands occupy an area of 4 . 6 km2 . The total number of households in the DSA recorded during Round 6 was 2 , 116 . A number of households occupy more than one stand . As residence episodes of households within the DSA were not tracked for this study , we present household-level data for Round 6 only . The number of occupants in these households was 9 , 652 , with a mean household size of 4 . 6 ( range: 1–27 ) . The mean number of dogs per household in Round 6 was 0 . 36 ( range 0–9 ) , and the number of dogs per 100 people in the DSA was 7 . 9 . The percentage of dog-owning households ( DOHHs ) was 17% . The proportion of surgically-sterilized dogs in the population was very low ( 1–1 . 5% ) . We recorded the number of new households ( taken occupancy within the previous 12 months ) in the DSA during Round 6 . Of the 2 , 116 households , only eight were new , with missing data from a further eleven households . Table 1 shows the demographic characteristics of the owned dog population present in the DSA on the first day of each quarter , from 1st January 2012 to 1st January 2014 . The population of owned dogs declined by 10% over the period of the study , but this overall decline masks a substantial fluctuation ( Fig 2 ) . Annual population growth rate ( as a percentage of the population at the start of the period ) was +18 . 6% in 2012 and -24 . 5% in 2013 . The total number of dog-years in the population was 915 in 2012 and 821 in 2013 . Crude annual birth rates were 451 puppies born per 1 , 000 dog-years of observation ( dyo ) in 2012 and 313 per 1 , 000 dyo in 2013 . Crude annual death rates were 406 per 1 , 000 dyo in 2012 and 568 per 1 , 000 dyo in 2013 . Crude birth and death rates by quarter are shown in Fig 2 . The rate of natural increase of the population ( birth rate minus death rate ) was +4 . 5% in 2012 and -25 . 5% in 2013 . The net migration rate , measured as the total number of in-migrations to households minus the total number of out-migrations from households , was 12 . 3% in 2012 and -2 . 1% in 2013 . Data were recorded for 1 , 093 household entry events and 1 , 173 exit events ( Fig 3 ) . Most dogs entered households through birth ( 61% ) or as gifts ( 31% ) , and exited through death ( 71% ) or being given away ( 21% ) . Owner-reported causes of death by quarter are shown in Fig 4 . Of the exits and entries , a small proportion were dogs that were bought and sold . Over the course of the study , 63 dogs were purchased while only 5 were sold , suggesting that the majority of dogs purchased were from outside the study area . The median purchase price for dogs was ZAR 30 , about US$ 5 ( n = 60 , range: ZAR 5 to ZAR 4 , 500 ) . The sex ratio of dogs migrating in to the population was skewed towards males ( 1 . 79 males per female; data on characteristics of external migrants was collected in Rounds 5 & 6 only ) . During this period , the sex ratio of dogs entering households from outside the study area ( external in-migrants , n = 25 ) did not differ significantly from those of dogs entering households from within the study area ( internal in-migrants , n = 184 ) ( 1 . 79 vs . 1 . 78; Fisher’s exact test p-value = 1 ) . Mortality rates by sex , age group and vaccination status are shown in Table 2 . There was no evidence of overdispersion of the regression model ( residual deviance 4453 on 4590 degrees of freedom; goodness-of-fit test p-value = 0 . 9 ) . Reducing the number of levels for the age class variable from five to three ( 0–3 months , 4–11 months and ≥12 months ) did not cause a significant increase in deviance of the model ( p = 0 . 09 ) , and simplified interpretation of the model outputs; age class was therefore reduced to three levels . The initial model revealed a significant three-way interaction between sex , age class and year . To aid interpretation of this interaction , we split the data into two sets by year ( 2012 and 2013 ) and modelled these separately . The adjusted mortality rate ratios ( MRRs ) are presented in Table 3 . In 2012 , there was no significant difference in mortality rates between the sexes , but in 2013 , females suffered a significantly higher mortality rate ( MRR = 1 . 54 , 95% CI = 1 . 28–1 . 85 ) . Sex-specific mortality rates by quarter are shown in S1 Fig . In both 2012 and 2013 , there was a significant two-way interaction between age class and vaccination status ( Tables 3 and 4 ) . Among unvaccinated dogs , mortality rates were significantly lower in the 4–11 months and ≥12 months age classes when compared to the 0–3 months age class across both years , but this effect of age on mortality rates was not seen among vaccinated dogs in either year ( Table 4 ) . In the age class 0–3 months , the mortality rate of vaccinated dogs was significantly lower than that of unvaccinated dogs ( 2012: MRR = 0 . 11 , 95% CI = 0 . 05–0 . 21; 2013: MRR = 0 . 31 , 95% CI = 0 . 11–0 . 69 ) . Vaccination coverage ( based on owner-reported vaccination history of 520 dogs for which this information was available ) was 33% before the start of the house-to-house vaccination campaign in Round 1 . After the campaign , this increased to 78% . Based on owner reports of individual dog vaccination history ( and assuming a duration of protection of three years ) , vaccination coverage remained well above the threshold level of 40% until a second vaccination campaign in 2013 ( Fig 5a ) . The results of the simulation of vaccination campaigns reaching 70% of the dog population on the 1st January 2012 and the 1st January 2013 are shown in Fig 5b and 5c . Despite the high turnover and substantial growth of the population in 2012 , the simulated coverage remained above the threshold of 40% for that year . The decline in the population in 2013 slowed the rate of decrease of vaccination coverage from the 2012 campaign , such that coverage only dropped below the threshold level around 18 months after the campaign ( Fig 5b ) . A second simulated campaign in January 2013 kept coverage well above the threshold for that year ( Fig 5c ) . To ensure a 40% coverage in the population 12 months after vaccination , the minimum vaccination coverage needed for the campaigns was 61% in 2012 and 52% in 2013 . The above simulation assumes that vaccination coverage is randomly distributed in the dog population . We tested for heterogeneity in actual vaccination coverage across sexes and age groups , using owner-reported vaccination data as on 1st January 2012 ( coverage = 66% ) . We found no association between sex and vaccination status ( Χ2 = 1 . 02 , d . f . = 1 , p-value = 0 . 31 ) , but a strong association between age and vaccination status ( Χ2 = 71 . 88 , d . f . = 4 , p-value < 0 . 0001 ) , with significantly fewer dogs vaccinated in the 0–3 and 4–11 month age groups than in the oldest age group ( ≥ 12 months ) .
We studied the dynamics of an owned , free-roaming dog population over a period of 24 months . We show that this is a highly dynamic population , with rapid turnover and significant heterogeneity in demographic rates over time and across segments of the population . Despite this , routinely achieving 70% vaccination coverage during mass dog vaccination campaigns conducted every 12 months will be sufficient to maintain coverage above the critical threshold of 40% , even during periods of rapid growth and high turnover . The population declined by 10% over the course of the study . Previous estimates of growth rates of owned dog populations in sub-Saharan Africa predict steady high growth rates of between 7–10% [5 , 11–13] , but these estimates , derived from retrospective data based on owner recall and collected during household surveys , may not capture the highly dynamic nature of these populations . Moreover , methods used to derive demographic rates from retrospective data collected during cross-sectional surveys may rely on assumptions whose validity is questioned by our findings , such as stable age- and sex-distributions or consistency of demographic rates over time . By contrast , Morters et al . [8] , who undertook a longitudinal study of two populations of owned dogs in resource-limited communities in Johannesburg , South Africa using methodologies similar to ours , observed no population growth in one site and an overall decline in the other site , over a three-year period . Together , these longitudinal studies demonstrate that , while owned dog populations are certainly capable of rapid growth , sustained growth in a given area is not a general phenomenon . The mortality rate in this population of dogs was very high over the study period , particularly in puppies aged 0–3 months . Hampson et al . [5] recorded a similarly high mortality rate ( 450 deaths per 1 , 000 population ) in dogs older than 3 months in owned , free-roaming dogs in northwest Tanzania . By comparison , the crude death rate of dogs in U . S . households in 1996 was estimated as 79 per 1 , 000 population [27] , and 39 per 1 , 000 dog-years in insured Swedish dogs from 1995 to 2000 ( [28]; this figure excludes puppies and dogs older than 10 years ) . High mortality rates in the first year of life in free-roaming dogs in resource-limited communities have been reported elsewhere ( [11–13 , 29] ) . Over half of all deaths in our study were reported by owners to be due to disease or parasites , while 21% were due to unknown causes . Only a relatively low proportion of deaths ( 7% ) were reportedly caused deliberately by owners or others; however , as Morters et al . ( 2014 ) argue , killing of unwanted dogs by owners may be underreported . If it is accepted that human demand rather than environmental resources determines the ‘carrying capacity’ of owned dogs in a given area ( as demonstrated by [8] ) , it can be hypothesized that , in the absence of affordable options for humane population management , killing of dogs will increase as the population grows and demand becomes satiated . Continued observation of the study population through a growth phase may shed further light on this and other mechanisms that regulate population growth . Mortality rates by age class were highest in the 0–3 month group , and significantly lower in subsequent age classes . Notably , rabies vaccination removed the effect of age on mortality rates , due to its association with significantly reduced mortality rates in the 0–3 month age group . Plausible explanations for this association include i ) specific protective immunological effects of the vaccine against rabies in this age group , ii ) nonspecific protective immunological effects of the vaccine against other infections ( heterologous immunity ) , and iii ) confounding effect of other interventions by owners who have their puppies vaccinated against rabies , compared with those who don’t . It is highly unlikely that the reduction in mortality is due to the specific protective effect of rabies vaccination , given the low incidence of the disease in the population during the periods in question ( 2012/2013 ) , particularly among the age group concerned [30] . Another explanation might be that dogs that are vaccinated against rabies are simultaneously vaccinated against other infections such as canine distemper or parvovirus , or are more likely to receive therapeutic interventions such as endo- or ectoparasite treatment . The reduction in mortality in the rabies-vaccinated puppies may therefore be as a result of the specific protective or therapeutic effects of associated interventions . Although the overall level of vaccination against diseases other than rabies is assumed to be extremely low , it remains plausible that some owners of young puppies may seek veterinary care at Hluvukani Animal Clinic . Such care might include vaccinations and other healthcare interventions that could significantly increase the survival rates of these puppies . However , cursory examination of clinic records and discussions with the clinician in charge suggest that veterinary health-seeking behaviour among the population within the DSA is not sufficiently advanced to account for this as an explanation . During vaccination campaigns , the local state veterinary services only administer rabies vaccine to dogs ( including those in the 0–3 month age class ) , and no other routine vaccination or healthcare intervention is given . This leaves the intriguing possibility that the reduction in mortality in the 0–3 month age group associated with rabies vaccination is due to a non-specific protective effect of the vaccine . There is strong evidence from human HDSS sites that vaccines have substantial nonspecific effects in children in high-mortality regions [31]; for example , in randomized trials tuberculosis and measles vaccines are associated with a substantial reduction in child mortality , which cannot be explained by prevention of the target disease [32] . Further studies in dogs ( observational studies in which the details and timings of vaccinations and other healthcare interventions are carefully recorded , or randomised controlled trials ) , are needed to determine if rabies vaccine does in fact induce a protective nonspecific immune response sufficient to reduce puppy mortality . Such a finding would have implications for the use of rabies vaccine in this age group ( particularly in light of a recent field study showing that rabies vaccine is effective in this age group [33] ) . The population sex ratio was strongly skewed towards males ( around 1 . 4 males per female dog in 2012 ) , and became increasingly so during 2013 ( increasing from 1 . 5 to 1 . 8 males per female ) . Male-skewed sex ratios are a consistent feature reported in other studies of the demographics of owned dog populations in sub-Saharan Africa [5 , 8 , 11–13 , 19 , 34 , 35] . This is attributed to a preference of owners for male dogs for guarding of households and livestock , and the reduced nuisance factor of males compared to adult females ( e . g . oestrus behaviour , unwanted puppies ) ; however , few studies have directly examined the demographic mechanisms that give rise to this male skew . Preference for male dogs in an owned population implies either decreased retention of female dogs ( through higher mortality rates and/or out-migration rates ) or increased recruitment of male dogs ( through higher in-migration rates or male-skewed birth rates ) . While Kitala et al . [13] found uniformly lower survival rates for females , other studies in male-skewed populations found no significant differences in survival rates between the sexes [5 , 12] . Our study shows that sex-specific mortality rates vary over time , with a significantly higher mortality rate in females compared to males in 2013 . This may explain the increase in the sex ratio during that year . ( Although the sex ratio of external in-migrants was also male-skewed , the number of external in-migrants was too small to affect the overall population sex ratio ) . These results highlight the need for longitudinal studies of dog demographics , as contributory factors to population structure will change over time . A conspicuous feature of the mortality rates in this population is the spike in mortality in the second quarter of 2013 ( Q6; Fig 2 ) . Although not definitively determined , observations by the authors suggest that a distemper epidemic occurred in the dog population at this time ( a retrospective serological study is underway to investigate this hypothesis ) . Females appear to have suffered a disproportionately greater increase in mortality rates during this period ( S1 Fig ) . The birth rate in this population was very high ( 313–451 per 1 , 000 dog-years ) , although not sufficient to compensate for the high mortality rates during the latter part of the study period , resulting in the overall natural decline in the population . Hampson et al . [5] report a similar high annual birth rate ( 530 dogs born per 1 , 000 ) for a population of owned , free-roaming dogs in northwest Tanzania . By contrast , New et al . [27] estimated a crude birth rate four times lower ( 114 dogs born per 1 , 000 ) for owned dogs in the United States . Other studies provide proxy measures for birth rates in free-roaming dog populations . Reece et al . [36] report that 48% of roaming adult females became pregnant in any given year from 1995 through 2006 in Jaipur , India . Kitala et al [13] recorded 249 puppies born to a cohort of 305 dogs ( 128 females and 192 males ) over a one-year period in Machakos District , Kenya in 1992–1993 , equating to an annual birth rate of 816 dogs born per 1 , 000 population . The dynamics of this dog population are strongly seasonal , driven by seasonality in birth rates ( peaking April–June ) and subsequent mortalities and migration of puppies . Seasonality of breeding in dog populations is not consistently reported . Reece et al . [36] and Totton et al . [37] report seasonal oestrus and pregnancy in two populations of free-roaming dogs in India , while Butler and Bingham [11] deduced a peak in births in June–August in Zimbabwe , neighbouring South Africa to the north . Conversely , Morters et al [8] reported no significant difference in the proportion of dogs pregnant by month in their study populations in Johannesburg , some 350 km south-west of our study area . Seasonality of reproduction , combined with differences in mortality rates across segments of the population , may have implications for the cost-effectiveness of vaccination campaigns conducted at different time periods . Our simulations show that , despite the highly dynamic nature of this population , achieving 61% vaccination coverage during an annual campaign of relatively short duration will be sufficient to maintain coverage above the critical threshold of 40% , even in the face of rapid growth and high turnover , as was the case in 2012 . This is consistent with the predictions of Hampson et al . [5] and Morters et al . [8] from populations of owned , free-roaming dogs in resource-limited communities elsewhere . The predictions from our simulation are conservative , in that they assume that all in-migrating dogs are unvaccinated , and that no supplementary vaccination occurs in the period between campaigns . This may explain the higher-than-predicted estimates seen in the owner-reported vaccination coverage ( Fig 5a ) . Furthermore , the simulation assumed random vaccination of 70% of the dog population present . Because proportionately more puppies were considered vaccinated in our simulation than in reality , and because of the disproportionately higher mortality rate in this age group , our estimates should again be seen as conservative compared to the real-world situation in which a higher proportion of the vaccinated dogs fall within older , more stable age groups . Furthermore , the simulation does not take account of the unanticipated finding in our study , that vaccinated puppies have a significantly lower mortality rate than unvaccinated puppies; this also makes our predictions more conservative . Future refinements of the simulation should take account of heterogeneity in vaccination coverage and demographic rates ( particularly mortality rates ) across segments of the dog population . Although allowance should be made for the fact that not all dogs who receive the vaccine will develop a protective immune response , the proportion of non-responders is likely small: recent field studies have shown that the vast majority of dogs ( >90% ) seroconvert to the vaccine , regardless of health status [38] . Overall , the findings of our study are consistent with WHO recommendations that , to achieve control and eventual elimination of dog rabies , programmes must ensure that mass dog vaccination campaigns achieve a vaccination coverage of at least 70% of the population in a given area , and that such campaigns recur , usually annually [6] . Meeting this target ideally requires an accurate estimate of the total dog population in a given area . Obtaining such an estimate is complicated by the highly dynamic nature of dog populations , as evidenced by this study . Estimates based on the number of dogs per household , or per 100 people , should therefore only be used to obtain a rough estimate of dog numbers for planning purposes . Novel , low-cost , robust methods are needed to provide accurate estimates of dog numbers . One such approach may be to engage community members to complete a census of owned dogs immediately ahead of a vaccination campaign . Such an exercise could also be used to raise awareness among dog owners of the upcoming campaign . This approach would be in line with that of the community-directed interventions that have proven successful in the control of other neglected tropical diseases , in which health interventions are undertaken at the community level under the direction of the community itself [39] . This approach could be extended to include planning of the vaccination campaign itself by communities , in partnership with local veterinary services , to ensure maximum vaccination coverage . The incorporation of a simple dog census/household survey into the dog rabies vaccination campaign , as practised in the study area , also offers a direct assessment of the achieved coverage . Our results show that effective rabies control is possible without adjunct dog population control measures , such as fertility control though sterilization or contraception [10 , 40] . One potential benefit of adjunct sterilisation programmes to rabies control could be to reduce population turnover rates and so help sustain vaccination coverage between campaigns , possibly extending the period between campaigns . Extending the period between campaigns ( for example , from 12 to 24 months ) could result in significant savings in operational costs and reduced ‘vaccinator fatigue’ ( a major factor in reduced campaign effectiveness over time; [41] ) , thereby improving the long-term cost-effectiveness of rabies eradication programmes; however , further cost-benefit studies are needed to weigh this up against the increased cost and time needed for sterilization programmes . Furthermore , the assumption that reducing birth rates through sterilization programmes will result in lower turnover in owned dog populations must be carefully examined . If mortality rates remain high in the face of lowered birth rates , demand for dogs may soon exceed supply , and new dogs may be sourced from outside the population . If not vaccinated , these dogs will contribute to the turnover of the population and offset the benefits of reduced recruitment of unvaccinated puppies . In addition , increased human-mediated in-migration of dogs may foreseeably increase the rate of incursion of rabies [15 , 42 , 43] , complicating eradication efforts . The focus of adjunct population management measures should be to help create stable , healthy , vaccinated populations of dogs; this may require the identification and inclusion of cost-effective interventions to reduce mortality rates as well as birth rates . Such efforts should not detract from the primary goal for rabies control , which is to achieve at least 70% vaccination coverage of the dog population during campaigns . In conclusion , we emphasise that mass dog vaccination campaigns which reach 70% of the population will be effective in bringing rabies under control and can contribute to rabies elimination , even in populations undergoing extremely high growth rates and rapid turnover . The results of this study demonstrate that demographic surveillance of an entire owned , free-roaming dog population in a resource-limited community in a rabies-affected area is feasible and provides reliable , accurate data that are needed for decision-making . In much the same way that the INDEPTH network has provided reliable population-based data on human health in low-resourced areas [20] , we feel there is value in establishing a network of health and demographic surveillance sites where similar methodologies are applied in owned dog populations in resource-limited communities , to provide a platform for evidence-based policies for rabies control and humane dog population management . | Rabies is a deadly disease caused by a virus that in Africa is maintained in populations of owned , free-roaming domestic dogs . Rabies can be controlled by mass vaccination , by ensuring that a certain proportion of the dog population is immune to the disease . Maintaining this proportion of immune animals creates herd immunity , reducing the spread of disease even among non-immune individuals , eventually leading to its elimination from the population . Maintaining herd immunity to rabies in free-roaming dog populations can be challenging , particularly in communities that lack regular access to veterinary services . In these communities , mass vaccination is usually implemented in annual campaigns , of relatively short duration . Between campaigns , the proportion of immune individuals in the population declines , often dropping below the critical threshold as vaccinated dogs die and susceptible dogs enter the population through birth or migration . We measured these rates of birth , death and migration in a typical population of free-roaming dogs in South Africa , and showed that vaccinating 70% of the population during annual campaigns would be sufficient to maintain herd immunity to rabies in the period between campaigns . This is achievable even in populations that have high turnover and are growing rapidly—the most challenging circumstances to maintaining herd immunity . These findings increase confidence in the feasibility of eliminating dog rabies from Africa through mass vaccination . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Population Dynamics of Owned, Free-Roaming Dogs: Implications for Rabies Control |
Fusarium Head Blight ( FHB ) is the number one floral disease of cereals and poses a serious health hazard by contaminating grain with the harmful mycotoxin deoxynivalenol ( DON ) . Fungi adapt to fluctuations in their environment , coordinating development and metabolism accordingly . G-protein coupled receptors ( GPCRs ) communicate changes in the environment to intracellular G-proteins that direct the appropriate biological response , suggesting that fungal GPCR signalling may be key to virulence . Here we describe the expansion of non-classical GPCRs in the FHB causing pathogen , Fusarium graminearum , and show that class X receptors are highly expressed during wheat infection . We identify class X receptors that are required for FHB disease on wheat , and show that the absence of a GPCR can cause an enhanced host response that restricts the progression of infection . Specific receptor sub-domains are required for virulence . These non-classical receptors physically interact with intracellular G-proteins and are therefore bona fide GPCRs . Disrupting a class X receptor is shown to dysregulate the transcriptional coordination of virulence traits during infection . This amounts to enhanced wheat defensive responses , including chitinase and plant cell wall biosynthesis , resulting in apoplastic and vascular occlusions that impede infection . Our results show that GPCR signalling is important to FHB disease establishment .
Wheat is prone to FHB disease when warm moist weather coincides with Fusarium graminearum spores arriving during crop anthesis . Germinating fungal spores produce hyphae that invade the inner surface of the floral tissues , with or without the production of complex infection structures [1] . The trichothecene ( TRI ) genes responsible for deoxynivalenol ( DON ) biosynthesis are highly expressed within these infection structures [1] . Once within the plant , invasive hyphae grow throughout the wheat head . Infection first spreads via symptomless colonisation of the apoplast , between live plant cells [2] , during which the TRI genes are again highly expressed [3 , 4] . After the establishment of infection , the pathogen promotes the colonisation and deconstruction of dead plant cells , causing the visible bleached appearance characteristic of FHB disease [2] . DON is required for the establishment and progression of wheat infection . In DON’s absence , wheat cells mounts a defensive response that confines infection [5] . Other biologically active secreted molecules contribute to virulence [6] , including the Fgl1 lipase that inhibits callose deposition and facilitates vasculature colonisation [7 , 8] , the iron scavenging triacetyl fusarinine C siderophore [9–11] , and carbohydrate-active enzymes that deconstruct plant cell walls and induce host cell death [2 , 4 , 12–15] . These virulence traits are spatially and temporally coordinated during infection [4] , suggesting that the pathogen is responding to micro-environmental changes whilst inside the host . G-protein signalling regulates fungal development , DON production and virulence in F . graminearum , where five G-proteins and seven RGS ( repressors of G-protein signalling ) differentially regulate vegetative growth , sexual reproduction , cell wall composition , DON production and virulence [16 , 17] . Components of the downstream cAMP-Protein Kinase A ( PKA ) pathway , including the adenylate cyclase and the major PKA catalytic subunit , have a broad impact on growth , sporulation , DON production , the formation of infection structures and virulence [18 , 19] . Further downstream , the terminal Map1 mitogen-activated kinase ( MAPK ) of the pheromone responsive/filamentous growth pathway regulates growth , sexual development , hydrolytic enzyme secretion ( including Fgl1 ) and virulence [20–22] . The Map1 pathway-specific FgSte12 transcription factor also influences hydrolytic enzyme secretion and virulence [23] . The cell wall integrity MAPK pathway influences growth , sexual development , DON production , and virulence , whilst the osmotic stress response MAPK pathway impacts upon sexual development , DON production , and virulence [24 , 25] . The well-characterised contributions of the G-protein , cAMP-PKA and MAPK pathways to virulence suggest an important role for unknown upstream GPCR signalling events in sensing host-derived ligands and promoting infection . Here we describe the expansion of non-classical GPCRs in F . graminearum , and show that class X receptors are highly expressed during wheat infection . We identify class X receptors that are required for FHB disease on wheat . These non-classical receptors are shown to physically interact with intracellular G-proteins . Disrupting a class X receptor is shown to dysregulate the transcriptional coordination of virulence traits during infection . This amounts to enhanced wheat defensive responses , including chitinase and plant cell wall biosynthesis , resulting in apoplastic and vascular occlusions that impede rachis infection . Our results show that GPCR signalling is important to FHB disease establishment .
The F . graminearum genome encodes 123 putative GPCRs containing 7- transmembrane domains [26] . Based on sequence homology and structural similarity , the 123 GPCRs can be sub-divided into 10 classes ( Fig 1A ) [26 , 27] . In F . graminearum this includes the class I and II sex pheromone receptors , a class III carbon receptor , two class IV nitrogen receptors , five class V cAMP-like receptors , a class VI RGS domain-containing receptor , a class VII MG00532-like receptor , two class VIII mPR-like receptors , three class IX opsin receptors and 106 class X PTH11-like receptors . Similarly , 61 . 5% of classical ( classes I-V and IX ) and 66 . 3% of non-classical ( classes VI-VIII and X ) GPCRs resided in chromosomal regions associated with high frequency recombination and virulence ( Fig 1B ) [28] . The number of putative GPCRs in F . graminearum is expanded in comparison to other model non-pathogenic and pathogenic ascomycete yeasts and filamentous fungi ( Fig 1C ) , primarily due to the increased number of class X receptors . No tandem duplications of PTH11-like receptors are reported [29] . These PTH11-like receptors are restricted to the filamentous Pezizomycotina subphylum of Ascomycota , and are more prevalent in fungi which interact with live or dead plants [27 , 29] . Among the 106 F . graminearum PTH11-like receptors , 8 possess an extracellular cysteine-rich CFEM domain ( PF05730 ) , common in fungal cell membrane proteins [30] . The expansion of non-classical receptors in F . graminearum and their location within genomic evolutionary hotspots , suggests that these receptors may be important for virulence . Quantifying the transcriptional regulation of the F . graminearum GPCR encoding genes during either axenic culture or the progression of wheat infection [4] revealed that the classical class I-V receptors were not highly expressed during plant infection . In contrast the non-classical class X receptors were highly expressed , particularly during the initial phase of symptomless infection ( Fig 1D ) . The FGRRES_03151 receptor had the highest fold induction ( ranging from 80 to 130-fold ) throughout wheat infection , while the FGRRES_07792 receptor had the highest absolute level of expression , which represented an 8 . 4-fold induction , during the later phase of symptomatic infection . However , the CFEM-containing PTH11-like receptor , FGRRES_16221 , showed the second highest fold induction ( 123-fold ) particularly during the establishment of symptomless infection ( S1 Fig ) . This is reminiscent of the expression of PTH11-like receptors in other fungal phytopathogens and saprophytes during either plant infection or growth on complex plant-derived carbon sources [29] . These transcriptional profiles suggest that non-classical class X receptors may be involved in wheat infection . Two independent null mutants were generated for each receptor . This included 7 classical class I-V receptors , 19 class X receptors with the highest fold transcriptional induction , or absolute expression , during wheat infection , and 7 class X PTH11-like receptors that contained the extracellular CFEM domain . The absence of individual class I-V receptors had no impact on virulence . In contrast , mutants of two class X receptors ( FGRRES_07792 and FGRRES_16536 ) and three PTH11-like CFEM-containing class X receptors ( FGRRES_16221 , FGRRES_02155 and FGRRES_07839 ) showed reduced FHB causing abilities on wheat ( S2 Fig ) , highlighting the potential importance of this receptor class to disease . Two of the receptor mutants that showed reduced virulence were FGRRES_07792 , which had the highest absolute level of expression during symptomatic infection , and FGRRES_16221 , which had the highest transcriptional induction during symptomless infection . Subsequently these two receptors were selected for further investigation . The progression of FHB symptoms on wheat was monitored for 15 days . Disease progression of the FGRRES_07792 and FGRRES_16221 mutants consistently lagged behind that of the parental PH-1 strain , ultimately reducing the final number of diseased spikelets ( Fig 1E–1G ) . The FGRRES_07792 and FGRRES_16221 mutants also showed reduced virulence on the floral tissue of non-host plant Arabidopsis thaliana ( S3 Fig ) . Reduced wheat disease symptoms correlated with a reduction in fungal burden , which was most pronounced for the FGRRES_16221 mutants ( Fig 1H ) . DON was detected despite the reduced disease symptoms produced by the FGRRES_07792 and FGRRES_16221 mutants . DON accumulation was reduced in wheat heads infected by the FGRRES_07792 and FGRRES_16221 mutants ( Fig 1I ) . However , normalisation of DON levels according to fungal burden revealed the FGRRES_16221 mutant produced more DON per fungal unit . Therefore , the FGRRES_07792 and FGRRES_16221 receptors are required for full virulence on wheat , but are not essential for DON production . The FGRRES_07792 and FGRRES_16221 receptors did not influence fungal growth on nutrient-rich or nutrient-poor media ( S4A Fig ) . Additionally , these receptors did not influence growth on a range of plant-derived carbon sources , including simple saccharides fructose , xylose and cellobiose , plus complex polysaccharides , carboxymethyl-cellulose , inulin , pectin and xylan ( S4B Fig ) . This suggests that the absence of these receptors does not significantly alter the pathogen’s capacity to deconstruct and/or utilise complex plant-derived carbon . This contrasts the function of PTH11-like receptors in saprophytes N . crassa and T . reesei , which contribute to lignocellulose utilisation [31 , 32] . The FGRRES_07792 and FGRRES_16221 receptors did not influence the pathogen’s ability to undergo homothallic perithecial development and the subsequent release of ascospores ( S4C Fig ) . The absence of in vitro growth and sexual development phenotypes suggests that the FGRRES_07792 and FGRRES_16221 receptors primarily function during interactions with the wheat head , in accordance with their elevated plant infection expression profiles . Orthologues of the FGRRES_07792 and FGRRES_16221 were identified across 436 fungal genomes , representing the 13 different taxonomic classes and subphyla within Dikarya ( Fig 2A ) . FGRRES_07792 and FGRRES_16221 orthologues were restricted to Pezizomycotina , excluding the Lecanoromycetes and Xylonomycetes . Additionally , FGRRES_07792 had no orthologues among the Leotiomycetes . Within Pezizomycotina , FGRRES_16221 showed the greater number of orthologues . Among the eight F . graminearum PTH11-like receptors with a CFEM domain , FGRRES_16221 showed the highest similarity to the founding member of the class X receptors , PTH11 from M . oryzae [33] . Both FGRRES_16221 and MoPTH11 are predicted to possess N-terminal signal peptides and an extracellular CFEM domain , seven transmembrane domains and a C-terminal cytoplasmic tail . In F . graminearum , these eight PTH11-like receptors with a CFEM domain showed the conservation of the eight cysteine residues , and seven receptors possessed an aspartic acid residue conserved in heme-binding CFEM proteins that is not present in MoPTH11 [34] ( Fig 2C ) . Class X receptors in F . graminearum are putatively classified as GPCRs [26 , 27] . The yeast split ubiquitin assay was used to determine if these non-classical receptors were G-protein interactors . The classical Ste2 and Ste3 sex pheromone receptors , plus the non-classical FGRRES_07792 and FGRRES_16221 receptors ( bait ) were fused with the C-terminal ubiquitin ( Cub ) fragment and the LexA-VP16 reporter . The three F . graminearum Gα-proteins ( prey: GzGPA1 , GzGPA2 and GzGPA3 ) and the Alg5 membrane protein ( non-GPCR interacting protein ) were fused with the N-terminal ubiquitin ( NubG ) fragment . Reconstitution of ubiquitin , as the result of a receptor-Gα-protein interaction at the cell membrane , released the LexA-VP16 reporter to promote growth on selective media . Yeast strains individually carrying receptors or Gα-proteins , or the receptors plus Alg5 , did not grow on selective media , excluding the possibility of auto-activation or non-specific interactions . Yeast strains harbouring the classical pheromone receptors , or the non-classical FGRRES_07792 and FGRRES_16221 receptors , in conjunction with any of the three Gα-proteins grew on selective media ( Fig 2D; S5 Fig ) . This shows that when overexpressed in a heterologous system , both classical and non-classical receptors have the capacity to interact with multiple Gα-proteins at the cell membrane , and proves that the class X receptors , FGRRES_07792 and FGRRES_16221 , are G-protein interactors . However , it remains unknown if that FGRRES_07792 and FGRRES_16221 are activators or repressors of G-protein signalling . The CFEM domains found in a subset of class X receptors are proposed to function in the recognition of , and adhesion to , the host , while the cytoplasmic carboxyl-terminal domain could interact with G-proteins [30 , 35] . The PTH11-CFEM domain in M . oryzae is required for appressorium development and pathogenicity [36] . To elucidate the contribution of specific sub-domains to virulence , F . graminearum strains harbouring three different types of FGRRES_16221 receptor truncations were generated ( Fig 3A ) . These included strains lacking the CFEM domain ( ΔCFEM ) or the cytoplasmic tail ( ΔCT ) , in addition to a strain possessing the membrane tethered CFEM domain , but lacking the majority of the receptor ( Fig 3A ) . The FGRRES_16221 truncations were driven by the native promoter and therefore their transcriptional regulation should be unaffected . All of the FGRRES_16221 truncations caused reduced virulence ( Fig 3B and 3C ) . Therefore , both the extracellular CFEM domain and the cytoplasmic tail contribute to receptor function and virulence , while the presence of the CFEM domain alone is not sufficient to cause disease . Interestingly , each truncation had a more severe impact on the establishment of FHB than the absence of the entire receptor . This suggests that the lack of this receptor triggered a compensatory mechanism , which was not activated in the fungal strains carrying receptor truncations . Finally , complementation of the two FGRRES_16221 null mutants with the native FGRRES_16221 gene restored virulence to parental PH-1 levels ( Fig 3B and 3C ) . Collectively , this data confirms that FGRRES_16221 and the CFEM domain are required for the establishment of FHB on wheat . The individual absence of the FGRRES_07792 and FGRRES_16221 receptors caused a reduction in FHB symptoms and fungal burden , but why infection progress was impaired remained unclear . The initial colonisation of the surface of the wheat floret was assessed by scanning electron microscopy at 2-days post infection ( dpi ) . This revealed a reduction in the colonisation of the floral tissues in the absence of either receptor ( Fig 4 ) . Nonetheless , the mutants lacking individual receptors developed penetration structures on the inner-surface of the palea , resulting in subcuticular infection . However , fewer runner hyphae provided connections between infection structures , and less fungal biomass was observed in comparison to the parental PH-1 strain . This is distinct to the function of PTH11 in M . oryzae , which is required for appressoria formation and host penetration [33] . Therefore , FGRRES_07792 and FGRRES_16221 both appear to contribute to the effectiveness of initial floral surface colonisation , but not wheat penetration . Assessment of wheat disease progression below the point of infection confirmed that the absence of the FGRRES_16221 receptor caused a delay in the development of FHB symptoms ( Fig 5 ) . After 9 dpi the rachis ahead of the last visibly diseased spikelet appeared dark brown , a characteristic not observed during PH-1 infection . This is reminiscent of the barrier zones confining infection by the F . graminearum Δtri5 ( a DON non-producer ) and Δfgl1 ( an extracellular lipase deficient ) strains [5 , 8] . Importantly , TRI5 expression is highly induced during , and required for , rachis colonisation [37] , while FGL1 inhibits callose formation and promotes rachis colonisation [7] . The rachis node represents a route for fungal infection to progress into the neighbouring spikelets and beyond into the next rachis internode . Within the third rachis node after 9 dpi , the parental PH-1 strain had colonised all wheat cell-types , causing widespread cell death and the destruction of the vasculature ( Fig 6 ) . No host defensive responses were observed during infection by the parental PH-1 strain . In contrast , in response to infection by the FGRRES_16221 mutant , apoplastic occlusions were abundant throughout the tissues , between live , metabolically active and reinforced wheat cells ( Fig 6 ) . These host defences appear to restrict the spread of infection , causing the accumulation of hyphae within the apoplast behind the defensive barrier . Histological examination of sequential rachis internodes , below the respective rachis nodes , also revealed the delayed progression of infection , and reduced fungal burden , by the FGRRES_16221 mutant ( Fig 7 ) . After 9 dpi , the parental PH-1 strain had inter- and intra-cellularly colonised all wheat cell-types , causing widespread cell death and the destruction of the vasculature . However , infection by the FGRRES_16221 mutant did not progress beyond the 3rd rachis internode , where a mass of fungal hyphae appeared to have accumulated in , and be restricted to , the vasculature ( Fig 7 ) . This vascular infection represented the only infection beyond the apoplastic occlusions observed in the 3rd rachis node preceding this tissue . Furthermore , ahead of infection by the FGRRES_16221 mutant , occlusions were observed in the xylem vessels of the 5th rachis internode , which is reminiscent of the increased vascular callose depositions in the rachis ahead of Δfgl1 infection [7] . RNA-sequencing was used to evaluate transcriptional differences between the F . graminearum parental PH-1 and FGRRES_16221 mutant ( Δ16221_3 ) strains in axenic culture ( 72 h in yeast peptone dextrose; YPD ) and during the establishment and progression of wheat infection at 3 and 7 dpi . The inoculated wheat spikelets ( SP ) and sequential rachis segments below the point of inoculation were harvested ( S9 Fig ) . Pairs of rachis segments , which were phenotypically similar in the parental PH-1 infection , were combined , representing the transcriptionally distinct fully symptomatic ( R1-2 ) , intermediate ( R3-4 ) and symptomless ( R5-6 ) infection phases [2 , 4] . The ratio of wheat-to-fungal transcripts was used as a measure of differences in fungal burden , confirming the reduced progression of infection by the FGRRES_16221 mutant ( Δ16221_3 ) ( Fig 8A ) . Pairwise analyses between PH-1 and Δ16221_3 infected wheat identified differentially expressed genes ( DEGs ) , overrepresented gene ontologies ( GO terms ) , and the modulation of genes specifically involved in G-protein signalling and virulence . In F . graminearum , few DEGs and no overrepresented GO terms were identified during axenic culture , or the early establishment of infection at 3dpi , supporting the concept that FGRRESS_16221 functions during the progression of infection . At 7 dpi significantly more DEGs were identified in the spikelet and first rachis internodes ( Fig 8B; S1 File ) . Genes with higher expression in Δ16221_3 corresponded to an overrepresentation of the isoprenoid pathway and downstream virulence traits , including trichothecene and sterol biosynthesis both known to be important to virulence [5 , 38] ( Fig 8C ) . DEGs resided within 65 of the 68 predicted secondary metabolite gene clusters [39] . The expression of many clusters , including those required for DON , remained high in Δ16221_3 behind the infection front , which contrasted the initially higher but then sharp decline in expression observed in PH-1 ( S6 Fig ) . This was reflected in the elevated DON accumulation in wheat per fungal unit . Siderophore biosynthesis , which also requires intermediates of the isoprenoid pathway and contributes to virulence [10] , showed altered expression during infection . Accordingly , the absence of FGRRES_16221 impacted on fungal growth in the presence of the iron chelator 2–2’-dipyridyl and therefore fungal iron homeostasis ( S7 Fig ) . This implies that FGRRES_16221 , which contains the putative iron-binding CFEM domain motif , may influence the biosynthesis of toxic and non-toxic secondary metabolites involved in virulence . The expression of 41 putative secreted effectors [12 , 40] was altered in Δ16221_3 , including the FGL1 lipase , which inhibits host callose formation to promote infection [7] ( Fig 8C ) . Accordingly , in the absence of FGRRES_16221 , lipase secretion was reduced when grown on wheat germ oil ( S8 Fig ) . This suggests that FGRRES_16221 influences lipase secretion and wheat lipid utilisation . Plant cell wall degrading xylanases and galactosidases showed reduced expression at the Δ16221_3 infection front , but ultimately resulted in elevated expression . Finally , during the progression of spikelet infection from 3 and 7 dpi , PH-1 modulated the expression of 3734 genes , while Δ16221_3 only altered the expression of 363 genes . Therefore , in the absence of FGRRES_16221 the transcription of known and putative virulence factors is dysregulated and fails to reflect the correct transition from symptomless-to-symptomatic infection as observed in the parental PH-1 strain . However , it remains unknown whether FGRRES_16221-mediated G-protein signalling directly , or indirectly , influences the regulation of these metabolite or proteinaceous virulence factors . Fungal GPCRs do not commonly directly regulate the transcription of G-protein , cAMP-PKA and MAPK signalling components . However , the indirect impact of the absence of FGRRES_16221 on the expression of genes involved in potential down-stream signalling pathways were inspected . This included other GPCRs , G-proteins , cAMP-PKA and MAPK signalling . In the absence of FGRRES_16221 , other class X GPCRs , the Gα and β-proteins , GzGpa2 and GzGpb1 , RGS ( repressors of G-protein signalling ) , plus the filamentous growth Map1 MAPK and associated Ste12 transcription factor were differentially regulated in comparison to those in the parental PH-1 strain . The differential MAP1 and STE12 expression patterns were reminiscent of the differential regulation of trichothecene and sterol biosynthetic genes during Δ16221_3 infections of wheat ( S2 File ) . This suggests that the absence of FGRRES_16221 may have an indirect influence on the transcriptional regulation of components of the G-protein signalling and the Map1-Ste12 pathways during wheat infection , pathways known to regulate invasive growth , plus DON and Fgl1 production [5 , 41 , 42] . Additionally , in Δ16221_3 there was an up-regulation of components of the cell wall stress MAPK pathway in the 1st rachis internode during infection , reflecting the increased exposure of Δ16221_3 to an enhanced plant defensive response , as observed in the histological examination of rachis infection ( Figs 6 and 7 ) . The previously described RNA-sequencing study simultaneously permitted the evaluation of the wheat host transcriptional response to infection by the F . graminearum parental PH-1 and FGRRES_16221 mutant ( Δ16221_3 ) strains at 3 and 7 dpi . In wheat , limited differences were observed during the establishment of spikelet infection at 3 dpi or in the non-infected rachis ahead of infection at 7dpi . However , significant transcriptional difference occurred in the spikelet and infected rachis at 7 dpi ( Fig 8B; S3 File ) . Overrepresented GO terms among these wheat DEGs included the elevated expression of genes involved in the response to fungal infection , superoxide metabolism and chitinases ( Fig 8D ) , representing the enhanced immune response to Δ16221_3 infection . In contrast , PH-1 infection showed a greater capacity to repress the expression of genes involved in plant cell wall polysaccharide , carotenoid and metalloexopeptidase biosynthesis , in addition to ER-to-golgi transport ( Fig 8D ) , processes central to plant defence . Collectively , this reflects wheat’s enhanced defensive response to Δ16221_3 infection , resulting in the occlusions of the apoplast and vasculature that impede rachis infection , potentially caused by the defective regulation of fungal virulence traits in the absence of the FGRRES_16221 receptor ( Fig 8E ) .
The expansion of class X receptors in plant interacting Pezizomycota [27] , and the identification of multiple class X receptors that contribute to FHB , reflects their function in pathogenesis . The first functionally characterised class X receptor , PTH11 in M . oryzae , senses hydrophobic plant surfaces , regulating appressoria development and host penetration [33] . FGRRES_16621-mediated signalling however , contributes to floral colonisation , but is not essential for host penetration . FGRRES_16621 is highly expressed at the advancing infection front , promoting the establishment of symptomless infection without activating host defences . Infection in the absence of FGRRES_16221 leads to rachis browning , elevated antifungal chitinases and plant polysaccharide biosynthetic gene expression , plus the appearance of apoplastic and vascular occlusions behind which intercellular hyphae accumulate . This shows the importance of the rachis to host defences and the outcome of F . graminearum infection . An inability to secrete DON results in a floral lesion surrounded by a brown halo that confines infection to the spikelet [5] . Whereas the disruption of Fgl1 lipase secretion results in browning of the rachis and vascular callose depositions that impede infection [7 , 8] . This is despite the Fgl1 mutant exhibiting enhanced DON production [40] . Therefore , within the rachis , where TRI gene expression is at its highest [37] , the secretion of DON and the Fgl1 effector are both required for infection to progress throughout the wheat head [5 , 7] . Additionally , the disruption of the capacity to secrete iron scavenging siderophores , triacetyl fusarinine C and malonichrome , increased sensitivity to reactive oxygen species and iron-depletion , stresses encountered during plant infection , resulting in reduced virulence on wheat [9–11] . The absence of FGRRES_16221 also caused elevated DON production and the browning of the rachis during wheat infection , while lipase secretion during growth on wheat germ oil was reduced , reminiscent of the Fgl1 mutant , and sensitivity to iron-depletion was increased . FGRRES_16221 disruption impacted on fungal transcription during the progression of rachis infection , resulting in the dysregulation of DON , siderophore and Fgl1 biosynthesis , in addition to other secondary metabolites and effector proteins putatively associated with virulence . How FGRRES_16221-mediated signalling directly , or indirectly , influences the biosynthesis of these secreted virulence traits remains unknown . Nonetheless , this disruption impedes the progression of rachis infection , due to the loss of symptomless infection and the activation of an enhanced host response . The elevated transcriptional induction of the isoprenoid pathway , ergosterol biosynthesis and cell wall stress signalling in the FGRRES_16221 deficient hyphae accumulated behind apoplastic and vascular occlusions , may reflect a fungal response to the hostile environment , resulting in the observed increase in DON production . Extracellular CFEM domains are present in a subset of class X receptors and are proposed to function in host recognition , signal transduction , adhesion and virulence [30 , 33 , 36 , 43] . In F . graminearum , the CFEM domain of FGRRES_16221 contributed to the establishment of symptomless infection . The CFEM domain of PTH11 in M . oryzae is also required for receptor function , appressoria formation , virulence and redox regulation [36] . The commensal and opportunistic human pathogen Candida albicans encodes three heme-binding secreted , cell wall and cell envelope localised CFEM proteins , namely , Rbt5 , Pga7 and Csa2 , which are highly expressed in low iron environments , including host infection [34 , 44 , 45] . The novel helical-basket fold consisting of six α-helices is stabilized by disulphide bonds formed from the eight cysteine residues . The Asp80 , which residue serves as the axial ligand conferring oxidation-specific Fe3+ heme binding properties of the C . albicans proteins [34] , is absent from PTH11 in M . oryzae . These structural traits are conserved in the CFEM domain of the FGRRES_16221 receptor . Therefore , during F . graminearum infections of wheat the environmental iron and oxidation-state of the apoplast may play a role in the activation of FGRRES_16221-mediated signalling and the coordination of virulence . The discovery of a fungal GPCR and specific extracellular domains that influence sterol membrane and mycotoxin biosynthesis , while contributing to virulence , opens new avenues for biotechnology to minimise diseases in crop species .
Fusarium graminearum strains were cultured and conidia prepared as previously described [2] . Fungal strains were grown for 3 and 5 days on nutrient-rich potato dextrose agar ( PDA ) , nutrient-poor synthetic nutrient agar ( SNA; 0 . 1% KH2PO4 , 0 . 1% KNO3 , 0 . 1% MgSO4·7H2O , 0 . 05% KCL , 0 . 02% glucose , 0 . 02% sucrose and 2% agar ) and SNA minus carbon supplemented with 1% of an alternative carbon source ( i . e . fructose , xylose , cellobiose , CMC , inulin , pectin or xylan ) . Fungal strains were grown on SNA in the presence of the iron chelator 2–2’-dipyridyl , at concentrations ranging from 50–200 μM , for 3 days . Fungal growth was photographed on a Nikon D40X under natural light . The ability to undergo homothallic perithecial development and the release of ascospores was assessed on carrot agar as previously described [20] . Perithecia were imaged on a Lecia MZFL11 stereomicroscope under bright field light . The susceptible spring wheat ( Triticum aestivum ) cultivar , Bobwhite , was grown as previously described [2] . At anthesis , 5 μl droplets of 5x104 conidia were placed in the floral cavity of the outer florets of the 5th and 6th spikelet from the top of the wheat head . The inoculated plants were kept at high humidity for 48 h , of which the first 24 h were dark [2] . Disease symptoms were scored by counting the number of symptomatic spikelets below the point of inoculation every three days until day 15 . Arabidopsis thaliana ecotype Landsberg erecta ( Ler-0 ) was grown and floral spray inoculated , when at least two open flowers and no more than three siliques present on their primary bolts , and scored using the Fusarium Disease Index as previously described [46] . Split marker-mediated transformation targeted fungal genes for replacement with the hygromycin , or geneticin , selectable markers by homologous recombination [47] . The NEBuilder Assembly tool was used for primer design ( S1 Table ) . The Gibson Assembly Cloning kits ( New England Biolabs ) were used to amplify the respective DNA sequences , which were ligated into the pGEMT-easy plasmid ( Promega ) and transformed into 5α Competent Escherichia coli . For each targeted gene replacement , two plasmids contained either the 5’ flanking region plus the first hygromycin/geneticin fragment , or the second hygromycin/geneticin fragment plus the 3’ flanking region . For FGRRES_16221 truncations , the two plasmids contained either the 5’ flanking region plus first hygromycin fragment , or the second hygromycin fragment plus the truncated FGRRES_16221 gene ( the CFEM: 75–370 nt , CT: 1380–1620 nt and TM3-7+CT: 730–1620 nt ) and the 3’ flanking region . Plasmids were recovered using GenElute Plasmid Miniprep Kit ( Sigma Aldrich ) . Transformation cassettes were PCR amplified using HotStarTaq DNA Polymerase ( Qiagen ) and purified by phenol ( 25 ) :chloroform ( 24 ) :isoamyl-alcohol ( 1 ) ( Sigma Aldrich ) precipitation . The F . graminearum parental PH-1 , Δ16221_1 and Δ16221_3 strains were polyethyleneglycol ( PEG ) -mediated protoplast transformed as previously described [45] . Positive gene disruption transformants were selected with hygromycin ( 75 μg/ml; Calbiochem ) , and complemented transformants were selected with geneticin ( 75 μg/ml; Sigma Aldrich ) . Mycelia was collected from 2-day old yeast extract peptone dextrose ( YPD ) cultures grown at 25°C , 180 rpm . Fungal DNA was extracted as previously described [48] . Homologous integration was confirmed by PCR using external 5’ and 3’ primers paired with primers internal to the split marker fragments . Two or three independent transformants were selected for biological evaluation . Wheat heads were frozen and freeze dried at 15 dpi , then ground into a powder under liquid nitrogen . A 0 . 1 g aliquot was removed and total DNA extracted as previously described [48] . Fungal and plant DNA within the sample was determined by absolute qPCR quantification , against a standard curve of genomic DNA of known concentration , using Sybr Green ( Sigma Aldrich ) with the F . graminearum specific TRI5 ( 5’-GATGAGCGGAAGCATTTCC-3’ and 5’-CGCTCATCGTCGAATTC-3’ ) and the wheat Cdc48 ( 5’-GTCCTCCTGGCTGTGGTAAAAC-3’ and 5’-AGCAGCTCAGGTCCCTTGATAC ) gene primers . Thermocycle parameters were [95°C , 3 min; ( 95°C 30 sec , 62°C , 30 sec; 72°C , 40 sec ) x40] and the dissociation curve [95°C , 15 sec; 60°C , 1 min; 95°C , 15 sec] . Fungal burden was represented by the ratio of fungal-plant DNA . DON was extracted in 5 ml H2O from 0 . 3 g ground wheat heads for 30 mins 180 rpm at 30°C . The soluble fraction was diluted 1:6 in 50 mM Tris pH8 , and subsequently 1:10 in H2O . DON was quantified by ELISA ( Beacon Analytical Systems ) per the manufactures instructions . The fungal burden and DON contamination for each treatment was calculated from two technical replicates and the analysis of 10–12 biological replicates . The split-ubiquitin system ( Dualsystems Biotech ) was used to investigate interaction between four F . graminearum GPCRs ( FGRRES_02655 , FGRRES_07270 , FGRRES_07792 and FGRRES_16221 ) and Gα-proteins ( Gpa1 , Gpa2 , and Gpa3 ) . Full length cDNAs of the GPCRs were cloned into the pTMBV4 vector ( the C-terminal half of ubiquitin plus the LexA::VP16 reporter [Cub] fused to the C-terminus of each receptor ) and the GPA1 , GPA2 and GPA3 cDNAs were cloned into pDL2XN ( the N-terminal half of ubiquitin [NubG] was fused to the C-terminus of each G-protein ) . The non-GPCR interacting Alg5 membrane protein was fused with NubG . The S . cerevisiae strain NMY32 was transformed using the LiAc method . Briefly , an overnight culture of NMY32 was diluted to OD600 0 . 3 , in a final volume of 50 ml YPD broth , and incubated at 30°C to an OD600 of 0 . 6–1 . 0 . Cells were harvested by centrifugation , washed in water , and resuspended in 100 mM LiAc in Tris-EDTA ( 10 mM Tris , 1 mM EDTA pH 7 . 4 ) . 0 . 2 μg plasmid DNA was then incubated for 30 mins at 30°C with 100 μl competent cells , 10 μl freshly denatured ssDNA ( 10mg/ml ) , and 600 μl PEG-LiAc solution [100 μl 1M LiAc ( pH 7 . 4 ) , 100 μl H2O , 800 μl 50% ( w/v ) polyethylene glycol 3350 per ml] . 70ul DMSO was added and the transformation mixture was heat shocked for 15 mins at 42°C , then kept on ice for two mins . The yeast cells were washed , then resuspended , with water and plated on selective media ( SD-leucine for Cub containing strains , and SD-tryptophan for NubG containing strains ) . Following confirmation of protein expression by Western blotting , GPCR-containing strains were co-transformed with each of the three Gα proteins by the same method . Interaction was determined by the growth of yeast transformants on a medium lacking histidine and/or adenine . The genomic localisation of the putative GPCRs was displayed on the four F . graminearum chromosomes [49] and aligned to regions associated with high frequency recombination [28] using Omnimap [50] . Orthologues of FGRRES_07792 and FGRRES_16221 were identified in 436 fungal genomes , representing the 12 of the 13 different taxonomic classes or subphyla within Dikarya , using the genomic resource PhytoPath ( www . PhytoPathdb . org ) [51] . No genomes for Lecanoromycetes were represented . Therefore , BlastP analyses using the mature FGRRES_07792 and FGRRES_16221 protein sequences were performed , at the expected ( e-value ) cut-off thresholds of 1x10-50 and 1x10-100 , on the predicted proteomes of four Lecanoromycetes presented on the JGI Mycocosm portal [52] . The mature protein sequence , and the CFEM domains , of the eight class X CFEM-containing F . graminearum GPCRs and PTH11 from M . oryzae were aligned using ClustalW and a phylogenetic neighbour-joining PHYML tree was constructed . The macroscopic appearance of representative diseased plants at 3–15 dpi was photographed on a Nikon D40X under natural light , while the excised inoculated spikelets and the rachis internodes below were imaged on a Lecia M205 stereomicroscope under bright field light . SEM was used to assess the establishment of floral colonisation . The wheat palea of the inoculated spikelet was excised at 2 dpi and mounted onto a cryo stub using a 50:50 mixture of OCT compound ( Sakura FineTek ) and colloidal graphite ( TAAB ) and plunge frozen in liquid nitrogen . Samples were transferred under vacuum to the GATAN ALTO 2100 cryo chamber stage maintained at −180°C . Paleae were etched for 1 min at −95°C prior to gold coating , and transferred to the cold stage of JEOL LV6360 SEM maintained at −150°C for histological examination of the progression of infection . Rachis internodes were fixed for 24 h with 4% paraformaldehyde , 2 . 5% glutaraldehyde in 0 . 05 M Sorensen’s phosphate buffer ( NaH2PO4:Na2HPO4 , pH7 . 2 ) , then washed 3× with 0 . 05 M Sorensen’s buffer . Fixed rachis internodes were dehydrated in a graded ethanol series , embedded in medium grade LR white resin ( TAAB ) and polymerized at 60°C for 16h . Semi-thin 1 μm sections were cut on an ultramicrotome ( Reichert-Jung , Ultracut ) and collected on glass slides . After staining with aqueous 0 . 1% toluidine blue O ( TBO ) in 1% sodium tetraborate pH9 , sections were mounted in DPX ( Sigma Aldrich ) , then examined and imaged using a Zeiss Axiophot light microscope . Fungi were grown in yeast extract peptone dextrose ( YPD; Sigma-Aldrich ) broth for 3 days at 25°C and 180 rpm . Mycelia was collected by vacuum filtration , washed with sterile water and frozen in liquid nitrogen . Wheat spikelets and the sequential rachis segments below the inoculated spikelet were dissected and frozen in liquid nitrogen at 3 and 7 dpi . Ten plants were combined for each biological sample , and experiments were performed in triplicate . Total RNA was extracted from frozen mycelia and wheat tissues with Quick-RNA MiniPrep™ kits ( Zymoresearch ) . RNA integrity was confirmed using the Bioanalyzer Nano kit ( Agilent technologies ) and the Agilent Bioanalyzer 2100 . RNA sequencing libraries were polyA-based mRNA enriched and sequenced ( non-strand specific paired-end reads ) on the Illumina HiSeq4000 platform by BGI Tech Solutions ( Hong Kong , China ) . Low quality reads were filtered using SOAPnuke [53] . To calculate expression values , clean reads were mapped to reference F . graminearum [49] and wheat ( http://plants . ensembl . org/Triticum_aestivum/Info/Index/ ) genomes using HISAT2 [54] . StringTie [55] was used to reconstruct transcripts and novel transcripts identified using Cuffcompare [56] . Reference and novel transcripts were combined and mapped onto the reference genomes using Bowtie2 [57] . Gene expression values ( FPMK ) were calculated using RSEM [58] . Pearson correlation identified outliers were removed from the analysis . DEGs ( FDR <0 . 05 , ±1log2 fold change in expression ) were identified using read counts in EdgeR [59] and overrepresented GO terms ( FDR <0 . 05 and <0 . 01 ) were identified using Blast2GO [60] . Fungal strains ( 10 μl 1x106 conidia ) were grown in liquid SNA media with 2% wheat germ oil ( Invitrogen ) as the sole carbon source for 3 days at 25°C and 180 rpm . Media was supplemented with 25 μl Rhodamine B solution ( 0 . 001% w/v ) . Fungal cultures were photographed on a Nikon D40X under natural light . Lipase secretion was detected by measuring the fluorescence ( Ex 540 nm , Em 600 nm ) of the supernatant on a SpectraMax i3 ( Molecular Devices ) . | Fusarium Head Blight ( FHB ) is the number one floral disease of cereals and poses a serious health hazard by contaminating grain with harmful mycotoxins . Fusarium graminearum adapts to the host plant environment , coordinating fungal development , metabolism and virulence . Here we show that non-classical G-protein coupled receptors ( GPCRs ) contribute to FHB disease on wheat , promoting symptomless infection through their regulation of fungal membrane , mycotoxin and secreted protein biosynthesis . Disruption of GPCR host sensing activated an enhanced wheat defensive response to infection . This amounts to increased chitinase and plant cell wall biosynthesis , resulting in apoplastic and vascular occlusions that impede the progression of symptomless infection . These non-classical receptors were confirmed to be bona fide G-protein interactors , and specific receptors domains were required for virulence . Our results show that GPCR signalling is important to FHB disease establishment . The discovery of fungal GPCRs and specific extracellular domains that influence sterol membrane and mycotoxin biosynthesis , while contributing to virulence , opens new avenues for biotechnology to minimise diseases in crop species . | [
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] | 2019 | Non-canonical fungal G-protein coupled receptors promote Fusarium head blight on wheat |
Next generation sequencing of viral populations has advanced our understanding of viral population dynamics , the development of drug resistance , and escape from host immune responses . Many applications require complete gene sequences , which can be impossible to reconstruct from short reads . HIV env , the protein of interest for HIV vaccine studies , is exceptionally challenging for long-read sequencing and analysis due to its length , high substitution rate , and extensive indel variation . While long-read sequencing is attractive in this setting , the analysis of such data is not well handled by existing methods . To address this , we introduce FLEA ( Full-Length Envelope Analyzer ) , which performs end-to-end analysis and visualization of long-read sequencing data . FLEA consists of both a pipeline ( optionally run on a high-performance cluster ) , and a client-side web application that provides interactive results . The pipeline transforms FASTQ reads into high-quality consensus sequences ( HQCSs ) and uses them to build a codon-aware multiple sequence alignment . The resulting alignment is then used to infer phylogenies , selection pressure , and evolutionary dynamics . The web application provides publication-quality plots and interactive visualizations , including an annotated viral alignment browser , time series plots of evolutionary dynamics , visualizations of gene-wide selective pressures ( such as dN/dS ) across time and across protein structure , and a phylogenetic tree browser . We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use . Simulations show how FLEA dramatically reduces the error rate of this sequencing platform , providing an accurate portrait of complex and variable HIV env populations . A public instance of FLEA is hosted at http://flea . datamonkey . org . The Python source code for the FLEA pipeline can be found at https://github . com/veg/flea-pipeline . The client-side application is available at https://github . com/veg/flea-web-app . A live demo of the P018 results can be found at http://flea . murrell . group/view/P018 .
Next generation sequencing ( NGS ) has become an invaluable tool for studying HIV and other rapidly evolving viruses by providing direct high resolution measurements of viral genetic diversity within the host . NGS has been used to study immune escape [1–7] , drug resistance [3 , 7–12] , transmission bottlenecks [3 , 13–15] , population structure and dynamics [2 , 3 , 16–22] , tropism dynamics [23] , and multiplicity of infection [24] . It is also used in clinical virology [25 , 26] . For reviews of the promises and challenges of NGS applications in virology , see [27 , 28] , [29] , and [30] . Full-length sequences can resolve features that are difficult to assemble from short sequences [8 , 31] . For instance , Pacific Biosciences SMRT sequences were able to resolve 1 . 5 kb msg isoforms from Pneumocystis jirovecii , but reads from a 454 instrument could not be assembled correctly [31] . For tracking evolutionary patterns in viral populations , accurately resolving these features provides a more accurate history of the population , which becomes especially relevant when epistatic interactions and linkage between mutations effect phenotypic changes in the pathogen [32–34] . For example , studies of HIV env frequently use functional assays to measure the potency with which a given antibody or donor serum neutralizes a specific env strain [35] , which requires knowing the full env sequence . We have developed a pipeline for handling long read HIV env sequencing data from within-host viral populations: the Full-Length Envelope Analyzer ( FLEA ) . FLEA addresses the specific challenges posed by large volumes of such data , e . g . , using the sequencing protocols we previously described in Laird Smith et al [36] , which also contains an overview of a prototype of FLEA . Here we describe the full pipeline and experimentally demonstrate its ability to resolve populations of closely related variants . FLEA uses state-of-the-art tools and methods at every step and can be accessed through a web browser or on a high-performance cluster . FLEA is readily extensible to other genes and systems . FLEA has recently been used by the authors in two high-profile studies . In [37] , we describe how FLEA was used to process PacBio HIV env data from a clinical trial of monoclonal antibody 10-1074 . For sequences sampled before and after therapy , FLEA reveals that prior to antibody therapy low-frequency env variants were present with mutations that typically confer resistance to 10-1074 . Additionally , when resistance emerges , it emerges multiple times , exploiting many different resistance pathways . FLEA was also used to characterize the longitudinal env population that drove development of a broadly neutralizing antibodies against the apex of the env trimer , sampled from donor PC64 from the Protocol C primary infection cohort [38] . There exist dozens of standalone pipelines developed for analyzing HIV and related sequence data , including longitudinal samples [4 , 9 , 12 , 39] . However , it was necessary to develop a new tool due to HIV env’s extensive natural indel variation and the high rate of indels in long PacBio reads , which are especially problematic when any spurious indel in the 2 . 6kb env amplicon corrupts the reading frame , rendering the sequence uninterpretable . Previous analysis [36] determined that , for PacBio amplicon sequencing of an Env clone ( for the set of sequencing and filtering conditions employed therein ) , 4 out of 5 errors are indels , and these occur more commonly in long homopolymer runs , with the per-base error rate ranging from 1 in 300 for a homopolymer of length 2 , but up to nearly 1 in 50 for a homopolymer of length 6 . On average , the per-base error rate was around 1 in 200 , yielding an average of roughly 13 errors per 2 . 6kb sequence . With HIV env , the common strategy of mapping reads to a reference fails because the diversity in variable regions of env , predominantly driven by extensive long insertions and deletions , means that these regions in sampled reads lack homology to those in any heterologous reference sequence , causing alignment-to-reference strategies to fail . Instead , FLEA relies on a fine-grained cluster-and-consensus strategy to remove spurious indels from reads . The task is related to Liang et al . ( 2016 ) , but , rather than distinguishing a small number of variants at 81-91% identity , we must distinguish potentially hundreds of variants that differ by only a handful of bases . The main contribution of the FLEA pipeline , therefore , is the reconstruction of a population , including accurate inference of relative frequencies of closely-related minority variants , from SMRT sequences alone . In addition , it performs many useful analyses on this population , such as alignment , phylogenetic reconstruction , and selection inference , and provides interactive visualizations for the results . The full pipeline is available as an online resource , or for local installation .
The input to FLEA is a set of FASTQ files from the PacBio RS-II or Sequel . Each set corresponds to one time point , containing circular consensus sequence ( CCS ) reads , which can be obtained using the “Reads of Insert” protocol on PacBio’s SMRTportal or SMRTanalysis tools . Upon completion , the FLEA pipeline produces results as JSON ( Javascript Object Notation ) files , a standard format for machine ( and human- ) readable structured data . The logic of FLEA is implemented in Nextflow [40] , a workflow framework for deploying parallel pipelines to clusters and clouds . FLEA consists of multiple sub-pipelines , as shown in Fig 1 . Details of the quality and consensus pipelines are depicted in Fig 2 . Together , these two pipelines take error-prone CCS reads and convert them into unique high-quality consensus sequences . The alignment pipeline generates a multiple sequence alignment , which is used by multiple methods in the analysis pipeline . The first steps remove low quality reads and filter out common sequencing artifacts . Parameters given in these steps were chosen for full-length HIV envelope sequences from the RS-II or Sequel platforms . Other reads with different properties ( error rates , error models , lengths , homopolymer distributions , etc . ) likely require different parameters . All steps are run independently per time point . Filter by error rate . The input FASTQ files contain Phred scores for each base , encoding the probabilities of incorrect base calls . USEARCH [41] is used to remove reads with an expected error rate greater than 1% , computed as the mean of the per-base error probabilities . Trim heads/tails . A fraction of reads from the Laird Smith et al . sequencing protocol contain poly-A or poly-T heads or tails ( cause unknown ) , which can be hundreds of bases long and sometimes contain a small number of other bases . These heads and tails are trimmed with a hidden Markov model ( Fig 3 ) implemented in Pomegranate [42] . The emission probabilities of the model were fixed , and the transitions trained using Baum-Welch . The Viterbi path for each sequence is computed , and bases emitted by head and tail nodes are removed . Filter long runs . Reads with homonucleotide runs longer than 16 bases are discarded . This length was chosen to be twice the length of the longest such run in the LANL HIV database [43] . Filter contaminants and trim reads . Sample contamination can introduce non-native sequences that interfere with subsequent analyses , so these contaminants must identified and discarded . USEARCH is used to compare reads to a contaminant database and a reference database using usearch_global . Alignments returned from querying the database are then used to trim reads to the gene boundaries . Trimming terminal insertions is vital for the accuracy of downstream tasks , such as length filtering and clustering . The contaminant database contains HXB2 and NL4-3 env , each ubiquitous in labs working with env sequences and a common source of sample contamination . Reads that match with ≥ 98% identity are discarded . Since a 1% error rate cutoff was earlier used , this parameter conservatively ensures that these contaminants are almost certainly identified . The reference database contains thirty-eight sequences representing the major HIV Group M subtypes from the LANL sequence database [43] . Reads with ≤ 70% identity to every sequence in the reference database are discarded . This cutoff is chosen to retain reads remotely similar to HIV Group M while excluding contaminants such as human or bacterial genome reads . If a sample is from SIV , or from a non group-M HIV+ donor , then more appropriate reference sequences should be added to the database . Filter by length . By default , sequences shorter than 90% or longer than 110% of the length of the reference sequence are discarded . However , sequences with large deletions are frequently observed in HIV . These likely represent replication incompetent envelopes , and their reduced length can cause them to be dramatically oversampled due to PCR length bias . Users who want to include these species in their analyses should modify these parameters . Reads that pass this quality assurance phase have low expected error rates and no homonucleotide runs , are within 70% identity of at least one reference sequence , are ( after trimming ) no more than 10% different in length than a reference sequence , and do not match the contaminant database . We refer to these sequences as quality-controlled sequences ( QCS ) . The FLEA web app is built using modern web design principles . It consists of two parts: a Javascript client-side app , written using the Ember . js [55] framework , and a server-side REST ( REpresentational State Transfer ) service for serving JSON-formatted data . There are two main benefits to using this decoupled pattern for scientific web applications . First , the client-side code only needs to be downloaded once , at the start of the session . The data are requested from the server and cached as needed . Once everything is loaded , the visualizations run entirely in the browser with no delays for page loads . Second , the REST service may be reused by other apps and third-party tools . The web app presents the results of the FLEA analysis as a series of interactive visualizations . The report is organized into the following sections .
The true sequences and copy numbers are not known for the P018 data . In order to assess the accuracy of our inferred sequence population , we used the HQCSs from a previous FLEA run to simulate a gold standard dataset on which to assess the FLEA pipeline . The simulation procedure starts with the HQCSs and copy numbers from the FLEA results on P018 , then augments them with additional mutated sequences to create a gold standard set of templates . Mutated sequences were added because our clustering strategy may artificially merge similar templates . For each template , noisy reads with a SMRT-style error profile were sampled . Full details of the simulation process appear in the supporting information . These simulated reads were sent through the FLEA pipeline , both with and without frame correction . The resulting QCS and HQCS sequences were compared to the ground truth using Earth Mover’s Distance ( EMD ) , using normalized copy numbers for the population weights and edit distance for the distance matrix . The fully constrained EMD has units that can be directly interpreted as the average change per nucleotide necessary to transform one sequence population into another . We also calculate two variants of EMD for further insight into how well the inferred population B estimates the sequences in the ground truth population A . EMDFP removes the constraint on A , allowing any amount of flow from A to B . It is a measure of false positives because it grows when B contains extra sequences distant from any in A . Similarly , EMDFN removes the constraint on B . It grows when B fails to recapitulate sequences in A , and therefore is a measure of false negatives . To see the effect of sequencing runs of different depths , the experiment was repeated for 300 , 1 , 000 , 3 , 000 , and 10 , 000 reads per time point . The results , which appear in Table 1 , show the benefit of FLEA’s approach of reducing sequence errors via clustering and consensus . The QCS sequences , although they have few false negatives ( EMDFN = 0 . 0782 ) for n = 10 , 000 , are dominated by false positives ( EMDFP = 8 . 3 ) . However , adding the consensus sub-pipeline virtually eliminates false positives ( EMDFP = 0 . 0336 ) , at the cost of only a 2 . 4x increase in false negatives , for a 8 . 6x improvement in EMD to 1 . 0549 . The frame correction step further improve both EMDFP and EMDFN because it turns false positives into true positives . The full-length env sequencing protocol yields approximately 10 , 000 reads per run; the P018 data averaged 9 , 744 reads per time point . Therefore , these results with n = 10 , 000 suggest that FLEA is capable of taking a full sequencing run of CCS reads from a diverse viral population with an average of 9 . 56 errors per sequence and inferring HQCSs with an average of 1 . 01 errors per sequence , which corresponds to an average error rate of 0 . 038% . Moreover , these error rates are mostly caused by low-abundance sequences in both the true population and the inferred FLEA sequences . Fig 10 shows that FLEA perfectly recovers all sequences from all time points that account for at least 1 . 6% of the population . An in-depth breakdown of the false negatives appears in Table D and Fig . M in S1 Text . FLEA was run directly on the P018 sequences , and the results are summarized here . The full results of this run are available to view at http://flea . murrell . group/view/P018 . Fig 2 shows the number of sequences from the V03 time point that make it to each stage of the quality and consensus pipelines . At three months post infection , the majority amino-acid sequence variant is shared by 52 . 1% of the population , and the next most common variants accounts for just 8 . 66% . This relative lack of diversity is consistent with early infection dynamics . By 37 months post infection there is much more diversity: the most common variant accounts for only 3 . 96% of the population . Donor P018 shows signs of potential N332 glycan specificity , as shown by the motif trajectories in Fig 6 . The glycan supersite , centered around N332 in V3 , is a common target for broadly-neutralizing antibodies [60] because these sites are often conserved , so mutations in these regions are associated with escape [61] . A year into sampling ( V12 ) , mutations 328R and 330H dominate , and the majority of sequences also contain 339N from 22 months ( V22 ) onwards . The error rates of PacBio CCS sequences are usefully predicted by the QV scores provided by the instrument [36] . We show ( Fig . G through Fig . L in S1 Text that the effective number of bases that are corrected in each CCS read ( as measured by the difference between that CCS and the HQCS to which it contributes ) was extremely well predicted ( Spearman’s rho from 0 . 69 to 0 . 76 ) by the QV scores . This result is especially encouraging given that our pipeline does not currently exploit these QV scores beyond the initial filtering step . Further , PacBio sequences have higher indel than substitution rates , and this was recapitulated in the number of corrected indels vs substitutions , although this ratio appeared to vary from one time point to the next .
A public instance of FLEA is hosted at http://flea . datamonkey . org . The Python source code for the FLEA pipeline can be found at https://github . com/veg/flea-pipeline . The client-side application is available at https://github . com/veg/flea-web-app . A live demo of the P018 results can be found at http://flea . murrell . group/view/P018 , with an explanatory page at: http://murrell . group/FLEAexplained/ . The FLEA pipeline analyzes longitudinal full-length env sequences and provides visualizations of the results . Using simulations , we show that FLEA is capable of inferring accurate HIV env consensus sequences and population frequencies . Despite each CCS read containing an average of ten errors , our approach distinguishes variants that differ by as little as one base from an amplicon with high indel variation . It uses those high-quality consensus sequences to generate a codon-aware multiple sequence alignment of all time points , estimate ancestral sequences , infer the phylogenetic tree , and perform many other population-level analyses with high accuracy . These results are presented in a visualization suite that is highly general and applicable to many related sequencing problem . While we provide a web application that should suffice for sequencing most standard Env samples from HIV-1 group M , we recommend that those who frequently engage in such sequencing , or who wish to sequence less straightforward samples ( eg . SIV or SHIV ) , install FLEA locally . This provides a range of customization and tuning options , such as the filtering parameters and the set of reference sequences . While our USEARCH-based clustering and consensus strategy for denoising long PacBio amplicons performs well when error rates are < 1% , there is a clear need for more sophisticated long-read de-noising algorithms that exploit the additional depth of lower quality reads that we currently discard . This will be especially beneficial for longer PacBio amplicons , because the CCS read quality distribution degrades with length . For example , while we can currently obtain around 15 , 000 CCS reads < 1% from a P6/C4 RS-II run of our 2 . 6kb env amplicon; this read count drops to ∼ 1 , 000 for full-length 9kb HIV genomes . Additionally , FLEA does sometimes erroneously collapse sequences from very similar templates , and more sophisticated approaches to amplicon denoising could likely improve upon this . Both the pipeline and client-side visualizations are under development , with many improvements planned , including a novel clustering algorithm that reduces false positives and a novel consensus algorithm that uses quality scores and performs frame correction . We plan to integrate epitope prediction into the FLEA pipeline and add appropriate visualizations for the case when users have IC50 values available for their sequences . Finally , FLEA will be expanded to support other amplicons . | Viral populations constantly evolve and diversify . In this article we introduce a method , FLEA , for reconstructing and visualizing the details of evolutionary changes . FLEA specifically processes data from sequencing platforms that generate reads that are long , but error-prone . To study the evolutionary dynamics of entire genes during viral infection , data is collected via long-read sequencing at discrete time points , allowing us to understand how the virus changes over time . However , the experimental and sequencing process is imperfect , so the resulting data contain not only real evolutionary changes , but also mutations and other genetic artifacts caused by sequencing errors . Our method corrects most of these errors by combining thousands of erroneous sequences into a much smaller number of unique consensus sequences that represent biologically meaningful variation . The resulting high-quality sequences are used for further analysis , such as building an evolutionary tree that tracks and interprets the genetic changes in the viral population over time . FLEA is open source , and is freely available online . | [
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] | 2018 | Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons |
Sri Lanka records substantial numbers of snakebite annually . Primary rural hospitals are important contributors to health care . Health care planning requires a more detailed understanding of snakebite within this part of the health system . This study reports the management and epidemiology of all hospitalised snakebite in the Kurunegala district in Sri Lanka . The district has 44 peripheral/primary hospitals and a tertiary care hospital-Teaching Hospital , Kurunegala ( THK ) . This prospective study was conducted over one year . All hospitals received copies of the current national guidelines on snakebite management . Clinical and demographic details of all snakebite admissions to primary hospitals were recorded by field researchers and validated by comparing with scanned copies of the medical record . Management including hospital transfers was independently assessed against the national guidelines recommendation . Population rates were calculated and compared with estimates derived from recent community based surveys . There were 2186 admissions of snakebites and no deaths in primary hospitals . An additional 401 patients from the district were admitted directly to the teaching hospital , 2 deaths were recorded in this group . The population incidence of hospitalized snakebite was 158/100 , 000 which was significantly lower than community survey estimates of 499/100 , 000 . However there was no significant difference between the incidence of envenomation of 126/100 , 000 in hospitalised patients and 184/100 , 000 in the community survey . The utilisation of antivenom was appropriate and consistent with guidelines . Seventy patients received antivenom . Anaphylactic reactions to antivenom occurred in 22 patients , treatment reactions was considered to be outside the guidelines in 5 patients . Transfers from the primary hospital occurred in 399 ( 18% ) patients but the majority ( 341 ) did not meet the guideline criteria . A snake was identified in 978 cases; venomous snakebites included 823 hump-nosed viper ( Hypnalespp ) , 61 Russell’s viper , 14 cobra , 13 common krait , 03 saw scaled viper . Primary hospitals received a significant number of snakebites that would be missed in surveys conducted in tertiary hospitals . Adherence to guidelines was good for the use of antivenom but not for hospital transfer or treatment of anaphylaxis . The large difference in snakebite incidence between community and hospital studies could possibly be due to non-envenomed patients not presenting . As the majority of snakebite management occurs in primary hospitals education and clinical support should be focused on that part of the health system .
Snakebite is a neglected health issue , mostly affecting rural agricultural communities of the developing countries [1] . Over 40 , 000 hospital admissions due to snakebites are officially recorded in Sri Lanka [2] . Hump-nosed pit vipers ( Hypnale spp . ) , Russell's viper ( Daboia russelii ) , common krait ( Bungarus caeruleus ) , cobra ( Naja naja ) , saw-scaled vipers ( Echis carinatus ) and several mildly venomous and non-venomous snake species are responsible for snakebites in Sri Lanka . Of these , Russell's vipers , common krait , cobra , saw-scaled vipers and the Hypnale species are the medically important snakes[3] . Sri Lanka is divided into three climatic zones based on rainfall: wet , dry and intermediate [4] , [5] . The differences in rainfall have led to much diversity in the flora and fauna , and in land use in these zones , leading to differences in snakebite patterns [6] . Its dry zone reports the highest incidence of snakebite resulting high morbidity mortality and economic hardships . Sri Lanka has a well developed network of government hospitals which provide treatment at no cost to the patients . Within any district there are a number of small primary hospitals supported by at least one referral hospital . It is estimated that no Sri Lankan is more than 30 minutes from a primary hospital . When indicated the government hospital system can offer advanced supportive care ( ventilation , dialysis ) and imported Indian Polyvalent Antivenom . There are established national guidelines on the management of snakebite produced and distributed by the Sri Lankan Medical Association [7] . These guidelines provide advice on management of envenomation from both identified and unidentified snakes , treatment of anaphylactic adverse reactions to antivenom and indications for interhospital patient transfer . The actual burden of snakebite for primary hospitals has not been described . While this can be inferred from community surveys of snakebites such surveys have not been validated in predicting hospitalization for snakebite[8] . Previous studies of hospitalized snakebites have been limited to tertiary care hospitals which are potentially biased by referral patterns . This study tests the validity of community surveys as a method to predict hospital admission , quantifies the burden of snakebite in the primary hospital system and measures care delivered against the benchmark of the national guidelines within an entire predominately rural district .
This observational prospective study was conducted in all of the inpatient health facilities in Kurunegala district of North Western Province ( NWP ) of Sri Lanka . The province is bound to dry and wet climate zones where the one of the highest incidence of snake bites reported . All patients who presented with snakebite between the 25th May 2013 and 25th May 2014 to any of the 44 primary hospitals or to the tertiary Teaching Hospital Kurunegala ( THK ) in Kurunegala district were enrolled in the cohort . The Primary Hospitals includes the Base Hospitals and the Divisional Hospitals . The Base Hospitals provide health care in relation to four main specialties only . The Divisional Hospitals are hospitals with very low facilities and they do not provide any specialized care . Data linkage was undertaken to identify the outcome of any patient transferred from a primary hospital to the THK . After date linkage for transfers all subsequent analysis was anonymized . The 2012 Sri Lankan census was used for estimating district population[9 , 10] . A previously published community survey of snakebite within the district was undertaken between August 2012 to June 2013 was used to compare with the population incidence of hospitalized snakebite calculated in this study [8] . The data extracted from the patients’ hospital records were transcribed into data extraction forms , and entered into a database in Microsoft Access by trained research assistants . The main variables extracted were demographic information , identification of snakes , clinical signs and symptoms treatment . A scanned copy of hospital record was attached to the data record . Snakes were identified by hospital staff if the snake specimen was brought to the hospital using the SLMA guidelines for the identification of snakes [7] . In the absence of the snake being brought to hospital snake were identified from history of patients and witnesses . The major determinant for use of polyvalent antivenom was the clinical syndrome of envenomation[7] . Syndromic diagnosis has been demonstrated to have a high specificity for species diagnosis [11] . This is important in identifying Hypnale hypnale envenomation as polyvalent antivenom is ineffective and not indicated . Recorded data included epidemiological and demographic details , clinical features of envenoming such local pain , swelling , necrosis and coagulopathy , neurotoxicity and other systemic symptoms . Details of antivenom administration , premedication against adverse drug reactions and management of adverse reactions were recorded . Using predefined criteria based on SLMA guideline[7] an expert clinician independently reviewed and scored scanned copies of the hospitals record to identify; the appropriateness of transfers to tertiary care centers , accuracy of identification of offending snakes , evidence of envenoming , indication for antivenom ( AV ) therapy , regimen and dose of AV therapy , management of AV adverse reactions and appropriateness of overall patient management . The accepted indications of transfers were anticipated ventilatory problems , need of ICU care , severe coagulopathy , impending acute kidney injury , need of surgical care for local necrosis and refractory shock , lack of resuscitation facilities , AV and emergency medications . Data were entered into a database in Microsoft Access by trained research assistants . The database was independently cross checked with the original data sources for accuracy and completeness by two other researchers . Data analysis was performed in the R programing language version 3 . 2 . 5 . All the individual level variables including the signs and symptoms for envenoming and the incidence of snake bites were considered for descriptive analysis . The study was approved by the Ethical Review Committee , Faculty of Medicine , University of Peradeniya , Sri Lanka . As the study was an audit of clinical practice undertaken in collaboration with the treating Health Authority , North Western Province . Provincial Health individual patient consent was not required by the IRB .
The median age of the patients presenting to the primary hospital was 40 years ( IQR 27–53 ) , and 59% were males . Median time to hospital arrival was 45 minutes ( IQR 30–90 ) and 49% of bites occurred between 6pm and 12am ( S1 Table ) . The offending snake was identified in 978 ( 45% ) cases: 03 mildly venomous species , 61 non-venomous snakes and 914 venomous snakes . The venomous snakebites included 823 hump-nosed viper ( Hypnale spp ) , 61 Russell’s viper , 14 cobra , 13 common krait , 03 saw scaled viper and 3 Green pit vipers . Of the identified , 91 cases ( 9% ) the live or death specimen were brought to the study hospitals ( S2 Table ) . Antivenom was given to 70 ( 3% ) patients and 22 ( 31% ) of were documented to have developed anaphylactic reactions . Sign or symptoms of envenoming were detected in 1690 cases ( 77 . 3% ) in the primary hospitals and 383 ( 95 . 5% ) direct admissions to THK including the unidentified bites . The total district incidence of envenomed was 126 ( 95% CI 105–150 ) cases per 100 , 000 population . Of the envenomed cases in the primary hospitals , local envenomation was detected in 1510 cases ( 89% ) , non-specific systemic effects such as abdominal pain , nausea , vomiting , diarrhea , chest pain and headache in 259 cases ( 15 . 3% ) and , the specific systemic effects such as coagulopathy , neurotoxicity , spontaneous bleeding and nephrotoxicity in 359 cases ( 21% ) . These clinical manifestations occurred either as sole manifestation or in combination with others ( S3 Table ) . Of the 2186 cases , antivenom has been given to 70 ( 3% ) patients as they had signs of systemic envenoming . Of them , 22 had developed anaphylactic reactions to antivenom , only 6 were judged to be severe ( Table 2 ) . Treatment was indicated in all patients , there was no record of treatment for 3 patients . All other patients received treatment that was appropriate for the severity of the reaction; 73% received adrenaline , 54% hydrocortisone , 28% IV antihistamine ( either promethazine or chlorphenamine ) . All the patients with severe anaphylactic reactions had the hypotension with the range of systolic blood pressure from 60 to 70 . One patient had unrecordable BP and pulse . Of them , 04 received the repeated doses of adrenaline , 03 treated with dopamine , 05 with IV hydrocortisone , 03 with IV Promethazine and 01 patient nebulized with oxygen . The indications for the use of antivenom in the primary hospitals was considered appropriate in all cases . In 6% ( 4/70 ) of patients the dose of antivenom used was less than that recommended by the national guidelines . No patients who remained in the primary hospital were identified as inappropriately not receiving antivenom when antivenom treatment was indicated . Of the total , 399 ( 18% ) patients were transferred out from primary hospitals . Only 58 transfers were indicated according to the apriori expert criteria ( Fig 1 ) . The most common reason for transfer was systemic envenomation with unpredictable outcome ( Table 3 ) . Documentation in the patient notes for the reason for transfer was only found in 84 records with only 19 meeting transfer criteria ( S4 Table ) . Within the transfer group 105 patients were transferred to a facility in another health district and 294 cases were transferred to THK . In the transfer to THK hospital case records of 177 were available for analysis , 30 cases ( 17% ) received AVS at THK 14 of these patients were identified by the expert review as having indications for antivenom in their primary hospital admission record .
This study reveals that the majority ( 82% ) of snake bite in the district is not managed in the tertiary referral hospital but is successfully managed in the primary hospital . This has implications for resource utilization and training . Unnecessary transfers could be addressed with additional doctor and community education . However as the majority of snakebite patients remain in the primary hospitals there may be unmet health needs . Previous research in Sri Lanka in envenomed patients showed that 54% met the criteria for depression and 27% post-traumatic stress disorder with 10% of patients ceasing work[29] . Some symptoms were responsive to brief psychological intervention delivered by non-specialist doctors[30] . Currently there are trials on hump nose antivenom , Given the high prevalence of hump-nosed viper in this other rural regions the introduction of an antivenom will have important implications for health planning as the number of patients who could potentially receive antivenom will dramatically increase . This will increase direct treatment costs as well as transfers . As in all chart review based studies the record of clinical signs and symptoms is likely to be incomplete . This is obvious with the low rate of recording of explicit reasons for transfer to another hospital . While outcomes of death , transfer and use of antivenom are likely to be robust anaphylactic reactions are most likely underestimates in particular mild ones [27] . Misidentification of offending snakes by hospital staff is a source of error , in a prospective study this occurred in 6% of samples . However clinical syndromes had a high specificity for species identification and should reduce inappropriate antivenom use in H . hypnale [11] . Errors in snake identification by patient or bystander is likely to be higher than hospital staff but is not likely to impact on decisions to treat which is based upon clinical envenomation .
Peripheral hospitals received the majority of snakebites that would be missed in surveys conducted in tertiary hospitals . Snakebites were treated appropriately and effectively in the primary hospitals with only a few needing antivenom therapy . Most of the transfers were unnecessary indicating need of guideline and education on improvement . Further education and confidence building in management of snakebite is recommended among all categories of health staff in the primary hospitals . | Snakebite is a neglected tropical disease which mainly affects the rural population in tropical countries . In Sri Lanka the disease burden is an important cause of hospital admission ( > 40 , 000 recorded annually ) . Most of the previous epidemiological studies in the Island have been done in tertiary care hospitals . We studied the snakebite admissions in all inpatient health facilities ( 44 primary hospitals and a tertiary care teaching hospital ) in an entire rural district where the one of the highest incidence of snakebites reported . The Peripheral hospitals received the majority of snakebites that would be missed in the previous surveys conducted in tertiary care Hospitals . Such an approach is likely to incorporate significant referral bias which may not provide accurate data for health planning . Antivenom is freely available to Sri Lankan government hospitals . All peripheral hospitals keep antivenom and national guidelines are available on management of snakebites . Our data shows that the majority of snakebites in the district are successfully cared for within the primary hospitals only a few needing antivenom therapy . Most of the transfers were not indicated when compared to the criteria described in the national guidelines . Further education and confidence building in management of snakebite is recommended among all categories of health staff in the primary hospitals . | [
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] | 2017 | A prospective cohort study of the effectiveness of the primary hospital management of all snakebites in Kurunegala district of Sri Lanka |
The function of miR165/166 in plant growth and development has been extensively studied , however , its roles in abiotic stress responses remain largely unknown . Here , we report that reduction in the expression of miR165/166 conferred a drought and cold resistance phenotype and hypersensitivity to ABA during seed germination and post-germination seedling development . We further show that the ABA hypersensitive phenotype is associated with a changed transcript abundance of ABA-responsive genes and a higher expression level of ABI4 , which can be directly regulated by a miR165/166 target . Additionally , we found that reduction in miR165/166 expression leads to elevated ABA levels , which occurs at least partially through the increased expression of BG1 , a gene that is directly regulated by a miR165/166 target . Taken together , our results uncover a novel role for miR165/166 in the regulation of ABA and abiotic stress responses and control of ABA homeostasis .
The phytohormone abscisic acid ( ABA ) plays critical roles in plant growth and development , such as seed maturation , seed germination , seedling growth , stomatal movement , as well as plant responses to abiotic and biotic stress , including drought , salinity , cold and pathogen infection [1–4] . The fluctuation of cellular ABA levels , which are determined by biosynthetic and catabolic pathways , allow plants to cope with physiological and environmental conditions [5–7] . De novo ABA biosynthesis from carotenoids is the primary pathway to produce ABA [7] . Many genes involved in this pathway have been identified , such as ABA1 , ABA2 , ABA3 , NCED3 and AAO3 [8 , 9] . An additional biosynthetic pathway occurs through hydrolysis of Glc-conjugated ABA ( abscisic acid-glucose ester [ABA-GE] ) to ABA by two glucosidases , AtBG1 and AtBG2 , which localize to the ER and vacuole , respectively [10 , 11] . Hydroxylation and conjugation are catabolic pathways that mediate the fine-tuning of ABA levels . Members of the cytochrome P450 family , CYP707A1 to CYP707A4 , control the hydroxylation reaction , and ABA uridine diphosphate glucosyltransferase ( UGT ) catalyzes the conjugation of ABA with Glc to produce ABA-GE [12–17] . Plant responses to ABA is mediated by a network of signaling pathways . In the core pathway , ABA is perceived by the ABA receptors , PYRABACTIN RESISTANCE1 ( PYR1 ) /PYR1-likes/REGULATORY COMPONENT OF ABA RECEPTORs ( RCARs ) [18 , 19] . Once bound to ABA , PYLs will recruit PROTEIN PHOSPHOSTASE 2C ( PP2C ) [20] and form a PYR/RCAR-PP2C complex to inhibit the PP2C activity , thereby activating the SNF1-RELATED PROTEIN KINASE2 ( SnRK2 ) kinases [21–23] . The activated SnRK2s phosphorylate downstream effector proteins including the AREB/ABF-type basic/region leucine zipper ( bZIP ) transcription factors , which control the expression of many ABA-responsive genes [24 , 25] . Among these transcription factors , ABA INSENSITIVE 3 ( ABI3 ) , ABI4 and ABI5 are essential regulators in the control of seed germination and early seedling growth [26–32] . A class of single-stranded RNAs that are 20–22 nucleotides in length and are referred to as microRNA ( miRNAs ) can regulate gene expression at post-transcriptional levels through specific base-pairing to target messenger RNAs [33] . miRNAs play critical roles in plant development , such as phase transition , pattern formation and morphogenesis [34] . miRNAs also play crucial roles in biotic and abiotic stress responses [35–38] . Additionally , more and more evidence is revealing that miRNAs are involved in hormonal responses . miR159 targets several MYB transcription factors , such as MYB33 , MYB65 and MYB101 , which interact with GA-response elements and control anther development and flowering time under short days [39 , 40] . Disruption of the miR159-mediated repression of MYB33 and MYB101 alters responses to ABA during seed germination [41] . The auxin response pathway is also regulated by miRNAs . Proper regulation of Auxin Response Factor 10 ( ARF10 ) , ARF16 and ARF17 by miR160 is required for both shoot and root development [42–44] . ARF6 and ARF8 are targeted and negatively regulated by miR167 [45 , 46] . Expression of a miR167-resistant ARF6 or ARF8 gene results in ovule and anther development defects [47] . miR167 could also target IAA-Ala Resistant3 ( IAR3 ) , which converts an inactive form of auxin to bioactive auxin [48] . miR390 guides the generation of trans-acting siRNAs , which target ARF2 , ARF3 and ARF4 that are required for the proper establishment of adaxial-abaxial identity of lateral organs and vegetative phase transition [49–52] . The NAC1 transcription factor is targeted by miR164 and acts on lateral root development through regulating auxin responses [45 , 53–56] . miR393 targets auxin receptor TIR1 and closely related F-box genes [46 , 57] . In addition , miR319-mediated regulation of TCP4 is required for the biogenesis of jasmonic acid through the modulation of LIPOXYGENASE2 ( LOX2 ) [58] . miR165/166 is one of the most extensively studied miRNAs , which have been shown to be involved in plant development . miR165/166 targets the Class III homeodomain leucine zipper family of transcription factor genes , including PHBULOSA ( PHB ) , PHVOLUTA ( PHV ) , REVOLUTA ( REV ) , ATHB-8 and ATHB-15 , which are required for the promotion of adaxial identity of lateral organs [59–62] . Recent work revealed that REV could directly regulate the expression of auxin biosynthetic enzymes TAA1 and YUCCA5 ( YUC5 ) , which in turn influence free auxin levels , and this was shown to be required for the shade-avoidance response [63] . The cytokinin ( CK ) biosynthesis gene ISOPENTENYL TRANSFERASE 7 ( IPT7 ) was found to be the direct target of PHB , and the direct activation of IPT7 by PHB was shown to control the root meristem differentiation regulatory network [64] . Here we present evidence for an important role for miR165/166 in the regulation of ABA and abiotic stress responses and the maintenance of ABA homeostasis . We show that disruption of miR165/166-mediated repression of its targets through reducing miR165/166 expression levels leads to a drought and cold resistance phenotype and ABA hypersensitivity during and after seed germination . We found that ABI4 acts downstream of a miR165/166-mediated pathway and could be directly regulated by a miR165/166 target . We also discovered that miR165/166-mediated negative regulation of its targets is essential for maintaining ABA homeostasis at least partly through modulating the expression of BG1 , which converts inactive ABA to active ABA . Our study links the miR165/166-mediated regulatory module to the ABA regulatory network and demonstrates a critical role for the miRNA in ABA responses and homeostasis .
To determine whether the miR165/166 mediated network plays important roles in response to abiotic stress , the previously reported stable transgenic Arabidopsis STTM165/166-31nt plants [65] , in which the expression of miR165/166 is dramatically reduced , were used in stress resistance tests . We compared the phenotype of wild type and STTM165/166 plants under drought conditions . When water was withheld from 3-week-old plants for up to 2 weeks , wild type plants severely wilted and displayed injury and reduced growth . In contrast , STTM165/166 plants appeared much healthier and less affected by the limited water ( Fig 1A ) . When the wilted wild type and STTM165/166 plants were re-watered , only a small proportion of the wild type plants survived and continued to grow . However , a substantial proportion of STTM165/166 plants recovered ( Fig 1A and 1B ) . Altered sensitivity to drought stress in plants is often caused by an altered rate of water loss from leaves . Consequently , we analyzed the water loss rate and found that detached wild type leaves lost water at a faster rate than STTM165/166 leaves ( Fig 1C ) . Interestingly , STTM165/166 is also more resistant to freezing temperatures compared with wild type based on freezing survival assay and cold-induced electrolyte leakage assay ( Fig 2A and 2B ) . Given that CBF genes play critical roles in freezing tolerance , we analyzed the expression of these genes to test whether miR165/166 mediated regulation of freezing tolerance occurs through modulating CBF factors . However , no substantial difference in the expression levels and patterns of CBF1-3 under cold treatment was detected between wild type and STTM165/166 plants ( Fig 2C ) . The expression of known CBF downstream genes , such as RD29A and COR15A , was also analyzed ( Fig 2D ) and we found that the transcript levels of these genes in STTM165/166 in response to cold stress are similar to that of wild type . These results indicate that miR165/166 may modulate freezing tolerance through CBF-independent factors . We also tested the response of STTM165/166 to ABA . Without ABA treatment , there was no significant difference in the seed germination and cotyledon greening between wild type and STTM165/166 ( Fig 3A ) . However , when the wild type and STTM165/166 seeds were sown on MS medium supplemented with ABA , we found that STTM165/166 was hypersensitive to ABA during seed germination . A delay of cotyledon greening was also observed for STTM165/166 plants ( Fig 3A , 3B and 3C and S1 Fig ) . We examined the expression of miR165/166 and its targets in STTM165/166 at this early developmental stage with or without ABA treatment by qRT-PCR analysis , and found that the levels of mature miR165/166 were indeed dramatically reduced ( Fig 3D and S2 Fig ) , and all the five target RNAs examined were elevated to different extents ( Fig 3E and S2 Fig ) . These results indicate that blocking the full function of miR165/166 disturbs ABA responses . We also tested the ABA response of mutants of miR165/166 target genes , but did not observe a significant difference with that of the wild type ( S3 Fig ) . The ABA-related phenotype that results from the compromised miR165/166 function indicates that a miR165/166 mediated regulatory module may affect ABA responses . To establish the molecular link between a miR165/166 mediated regulatory module and an ABA mediated regulatory network , we first compared expression of ABA-responsive genes , such as RESPONSIVE TO DESSICATION 29A ( RD29A ) , RD29B , RAB18 , EM1 and EM6 in wild type and STTM165/166 plants . Interestingly , without ABA treatment , the transcript levels of these genes were upregulated to different extents in STTM165/166 plants ( Fig 4A ) . However , the difference in the expression of these genes disappeared when exogenous ABA was applied ( Fig 4B ) . When seedlings were treated with 50 μM ABA for different time periods , there were still no significant differences in the transcript levels of ABA-responsive genes between wild type and STTM165/166 plants ( S4 Fig ) . Since the expression of ABA-responsive genes was upregulated in STTM165/166 under normal conditions , we speculated that ABA signaling may be activated or endogenous ABA level is altered . We examined the expression of core components of ABA signaling pathway , such as PYLs ( PYR1 , PYL1 , PYL2 , PYL4 , PYL5 ) , SnRK2s ( SnRK2 . 2 , SnRK2 . 3 , SnRK2 . 6 ) , ABI1 , ABI2 and HAB1 . No significant difference in the expression of these genes was found between wild type and STTM165/166 ( S5 Fig ) . We also compared the expression of these genes in wild type and STTM165/166 seedlings treated with 50 μM ABA for different time periods , and no significant difference was detected ( S6 , S7 and S8 Figs ) . Since ABI3 , ABI4 and ABI5 are central regulators in the control of ABA- responsive genes , we determined the effect of knockdown miR165/166 on the expression of these genes . We found that the expression of ABI4 was substantially increased in STTM165/166 under normal conditions ( Fig 5A ) . We then tested the expression of ABI4 in PHB:PHB G202G-YFP lines expressing a miRNA-resistant version of PHB fused to GFP driven by the PHB promoter . Interestingly , we found that ABI4 transcripts accumulated to higher levels in the tagged lines compared with that of wild type ( Fig 5B ) . Bioinformatic analysis revealed that a typical HD-ZIPIII binding consensus sequence exists in the ABI4 promoter region ( Fig 5C ) , and this prompted us to determine whether ABI4 could be directly regulated by a miR165/166 targeted HD-ZIPIII . Thus , we conducted an EMSA assay , and found that PHB protein could bind to the region containing the typical HD-ZIPIII binding consensus sequence ( Fig 5D ) . This indicates that a miR165/166 target can directly modulate ABI4 expression . We also examined the expression of genes involved in the ABA homeostasis pathway . We could not detect any significant difference in the transcript level of any gene involved in de novo ABA biosynthesis , such as ABA1 and NCED3 , between wild type and STTM165/166 ( S9 Fig ) . In addition to genes involved in ABA de novo synthesis , genes required for ABA conjugation or deconjugation also affect ABA homeostasis . We then checked the expression of genes involved in this pathway . Interestingly , we found that the expression of BG1 was dramatically elevated in STTM165/166 seedlings compared with that of wild type ( Fig 6A ) , but the expression of UGT genes was not altered ( Fig 6A ) . We also found that the upregulation of BG1 in STTM165/166 was not limited to the seedling stage . The transcript level of BG1 was also higher in STTM165/166 leaves and flowers compared with that of wild type ( Fig 6B ) . To examine the effect of the altered expression of these genes on ABA levels in STTM165/166 , we measured the content of ABA by ELISA using an anti-ABA antibody [10] . We found that the ABA content in STTM165/166 plants was approximately 3 fold of that in wild type ( Fig 6C ) . This indicates that regulation of the BG1 gene mediated by the miR165/166 regulatory module contributes to changes in ABA content . To determine whether the upregulated BG1 expression might contribute to the drought resistance and reduced water loss phenotypes of STTM165/166 plants , we generated STTM165/166 plants in bg1-2 mutant background by crossing STTM165/166 plants and bg1-2 mutant plants , and we found that the drought resistance and reduced water loss phenotypes of STTM165/166 plants were partially suppressed by bg1-2 ( S10 Fig ) . These indicate that the upregulation of BG1 in STTM165/166 accounts at least partially for its abiotic stress phenotypes . Since the expression of BG1 was enhanced in STTM165/166 , we next investigated its expression in PHB:PHB G202G-YFP lines to determine whether higher expression of PHB could also affect the expression of BG1 . We found that the expression of BG1 was upregulated in the PHB:PHB G202G-YFP line ( Fig 7A ) . To determine whether PHB is directly associated with the BG1 promoter , we first analyzed the sequence of the BG1 promoter and found that it contains a PHB recognition motif ( Fig 7B ) . A ChIP assay was then performed using PHB:PHB G202G-YFP lines and this showed that one region of the promoter was highly enriched relative to the 35S:GFP control ( Fig 7C ) . The enriched region contains the PHB recognition motif . Additionally , EMSA assay further confirmed that PHB protein could bind to the enriched region ( Fig 7D ) . These findings indicate that BG1 is also a direct target of PHB .
Unlike some miRNAs , such as miR160 , miR167 and miR393 , which directly target and regulate the expression of key components of the auxin response pathway , the miR165/166 targets themselves are not major components of hormone response pathways but they regulate the transcription of important components of hormone pathways . Recent work showed that REV could directly modulate auxin biosynthetic gene expression and is involved in the shade-avoidance response pathway [63] , whereas PHB directly activates the CK biosynthesis gene IPT7 and is integrated into the root meristem differentiation regulatory network [64] . Here we provide evidence that the miR165/166-PHB module is involved in regulating ABA homeostasis . The expression of BG1 could be directly promoted by PHB . Therefore , upregulation of the miR165/166 target gene expression caused by compromised miR165/166 function results in the increased expression of BG1 , which in turn further modulates ABA homeostasis . Proper regulation of miR165/166 is important for normal ABA responses . Once miR165/166 is repressed , its repression on target genes will be released , and the upregulated expression of miR165/166 targets will directly promote the accumulation of ABI4 , which in turn activates downstream ABA responsive genes . Meanwhile , the increased miR165/166 targets could also upregulate the expression of the BG1 gene , which at least in part contributes to the elevation of ABA content in STTM165/166 . Thus , the ABA hypersensitivity phenotype of STTM165/166 during seed germination and post-germination stages might be attributed to both the higher levels of active ABA and stronger ABA response caused by higher expression of BG1 and ABI4 , respectively . Like the ABI3 and ABI5 transcription factors , ABI4 also plays a critical role in ABA responses , but compared with ABI3 and ABI5 , how the activity of ABI4 is modulated is largely unknown . In this study , we found that HD-ZIPIII transcription factors , which are the direct targets of miR165/166 , could directly bind to the ABI4 gene promoter and regulate its expression . Thus , miR165/166 is relevant to ABI4 in ABA responses . It has been observed that the expression of miR165/166 was altered under different abiotic stress conditions , such as cold , heat , salt and oxidative stress [66–70] . Regulation of miR165/166 expression may help plants to cope with environmental stresses . Given that miR165/166 is an important regulator in plant growth and development , the miR165/166 meditated regulatory module might help coordinate developmental programs with environmental cues to optimize plant growth and developmental processes under stress . miR165/166 is evolutionarily conserved in a wide range of plant species and its function in plant development is also very conserved . Future studies will determine whether the role of miR165/166 mediated regulatory module in ABA response and homeostasis is conserved in other plant species .
All Arabidopsis plants used in this study are in the Columbia-0 ( Col-0 ) ecotype . Plants were grown in soil at 23°C under a 16h light/8h dark cycle . STTM165/166 , PHB:PHB G202G-YFP lines , bg1-2 and abi4-1 have been described previously [10 , 65 , 71 , 72] . To construct GST-PHB , the DNA of PHB was amplified using the genomic DNA of PHB:PHB G202G-YFP lines as template . The PCR products were purified and digested with EcoRI and inserted into the corresponding sites of the pGEX4T-1 vector . To measure the rate of germination , seeds were harvested and stored under identical conditions . Seeds were surfaced sterilized and stored at 4°C for 3 days . Seeds were plated on MS plates containing 1% sucrose and 0 . 3% phytogel , and germinated at 22°C in a 16-h/8-h light/dark condition . Electrolyte leakage assay was performed as previously described [73] to determine the freezing tolerance of plants in this study . In brief , 3-week-old plants grown in soil were subjected to cold acclimation at 4°C for 7 days before freezing treatment . At each temperature point , three replicates were performed . A fully developed rosette leaf was placed in a small tube containing 100 ul deionized water , and a small ice chip was then added to each tube . Incubate the tube in a freezing bath ( model 1187 , VWRScientific ) with temperature at 0°C . The temperature was reduced by 1°C every 30 min until -11°C was reached . At each temperature point , the tubes were removed from the freezing bath and placed on ice . Transfer the leaves and solutions to large tubes with 25 ml deionized water . Shake the tubes overnight and measure the conductivity of solutions . Then autoclave the tubes at 121°C around 20 min , and shake the tubes for another 3 hours before measuring the conductivity . Finally , calculate the ratio of conductivity before and after autoclaving . For freezing survival assay , 12-day-old seedlings grown on MS plates containing 1% sucrose and 0 . 8% agar were subjected to cold acclimation at 4°C for 7 days . The freezing treatment was conducted in a freezing chamber with the following program: the temperature was set at 4°C and reduced to 0°C within 30 min and then the temperature was reduced 1°C every 1hr until -7°C was reached . Transfer the plates at 4°C for 12hr in the dark and recover the seedlings at 23°C for 5 days . For ABA treatment , seedlings were grown in ½ MS liquid medium for one week were treated with 50 μm ABA for the indicated times as described previously [74] . For the examination of mRNA expression level , total RNA was extracted using the RNeasy mini kit ( Qiagen ) according to the manufacturer’s instructions , and reversely transcribed using the High-Capacity cDNA Archive Kit ( Applied Biosystems ) . Quantitative real-time PCR was performed using the SYBR Green PCR master mix kit according to the manufacturer’s instructions . Actin mRNA was used as an internal control . Relative gene expression level was calculated from 2-ΔΔCt values . Primers used for qPCR are listed in S1 Table . Mature miRNA quantification was performed according to TaqMan Small RNA Assays protocol ( Applied Biosystems ) . Arabidopsis SnoR101 was used as an internal control . TaqMan Gene Expression Master Mix ( Applied Biosystems ) was used to perform qRT-PCR . ChIP assays were conducted as previously described [75] . Briefly , 2 . 0 g materials and the anti-GFP ( Abcam ) antibody were used for ChIP assay . The precipitated DNA was dissolved in 100 ul of TE buffer , and 2 ul was used for ChIP real-time PCR . Three independent biological replicates were performed , and a representative result is presented . Primer pairs used for ChIP enrichment test are described in S1 Table . GST-PHB recombinant fusion protein was expressed in the E . coli BL21 strain and purified using Glutathione sepharose 4B beads ( GE Healthcare ) . The oligonucleotides were labeled with α-32P-dATP using T4 Polynucleotide Kinase ( NEB ) , the 32P-labeled probes were incubated in 20 ul reaction mixtures containing 20 mM Tris-HCI ( pH7 . 5 ) , 300 mM NaCI , 5 mM MgCI2 , 0 . 1% NP-40 , 0 . 5 mM DTT for 20 to 60 min at room temprature , and separated on 6% polyacrylamide gels in Tris-glycine buffer ( 50 mM Tris , 380 mM glycine , 2 mM EDTA , pH 8 . 0 ) . The oligonucleotides used for EMSA are listed in S1 Table . ABA content was measured with a Phytodetek ABA test kit ( Agdia , Inc . , Elkhart , IN ) following the manufacturer’s instructions . | Functions of miRNAs in plant development and stress responses have been extensively studied . However , little is known about how a miRNA may perform critical functions in both plant development and abiotic stress responses . One well-known miRNA , miR165/166 , has critical roles in plant development . In this study , we show that this miRNA also has important functions in ABA and abiotic stress responses . Since the expression level of miR165/166 can be reduced to different extents using short tandem target mimicry ( STTM ) , in the present work , we used STTM165/166 transformants with moderate developmental phenotype to examine its potential role in abiotic stress responses . Our results show that miR165/166 plays critical roles in drought and cold stress resistance as well as in ABA responses . Our work reveals that miR165/166-mediated regulatory module is linked with ABA responses and homeostasis through ABI4 and BG1 . | [
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] | 2016 | The miR165/166 Mediated Regulatory Module Plays Critical Roles in ABA Homeostasis and Response in Arabidopsis thaliana |
Leprosy is a chronic infection where the skin and peripheral nervous system is invaded by Mycobacterium leprae . The infection mechanism remains unknown in part because culture methods have not been established yet for M . leprae . Mce1A protein ( 442 aa ) is coded by mce1A ( 1326 bp ) of M . leprae . The Mce1A homolog in Mycobacterium tuberculosis is known to be associated with M . tuberculosis epithelial cell entry , and survival and multiplication within macrophages . Studies using recombinant proteins have indicated that Mce1A of M . leprae is also associated with epithelial cell entry . This study is aimed at identifying particular sequences within Mce1A associated with M . leprae epithelial cell entry . Recombinant proteins having N-terminus and C-terminus truncations of the Mce1A region of M . leprae were created in Escherichia coli . Entry activity of latex beads , coated with these truncated proteins ( r-lep37 kDa and r-lep27 kDa ) , into HeLa cells was observed by electron microscopy . The entry activity was preserved even when 315 bp ( 105 aa ) and 922 bp ( 308 aa ) was truncated from the N-terminus and C-terminus , respectively . This 316–921 bp region was divided into three sub-regions: 316–531 bp ( InvX ) , 532–753 bp ( InvY ) , and 754–921 bp ( InvZ ) . Each sub-region was cloned into an AIDA vector and expressed on the surface of E . coli . Entry of these E . coli into monolayer-cultured HeLa and RPMI2650 cells was observed by electron microscopy . Only E . coli harboring the InvX sub-region exhibited cell entry . InvX was further divided into 4 domains , InvXa—InvXd , containing sequences 1–24 aa , 25–46 aa , 47–57 aa , and 58–72 aa , respectively . Recombinant E . coli , expressing each of InvXa—InvXd on the surface , were treated with antibodies against these domains , then added to monolayer cultured RPMI cells . The effectiveness of these antibodies in preventing cell entry was studied by colony counting . Entry activity was suppressed by antibodies against InvXa , InvXb , and InvXd . This suggests that these three InvX domains of Mce1A are important for M . leprae invasion into nasal epithelial cells .
Hansen's disease is a chronic infection with acid fast bacillus where skin and peripheral nerves are damaged by the infection with Mycobacterium leprae ( M . leprae ) . Although the number of Hansen’s disease cases has drastically decreased in developed countries , worldwide , the number of new cases of Hansen’s disease has only dipped below 200 , 000 per year . Hansen’s disease is one of the Neglected Tropical Disease ( NTDs ) and is still a major problem against public health [1] . Hansen’s disease can be broadly divided into tuberculoid leprosy ( T type ) and lepromatous leprosy ( L type ) , depending on the host immune response to M . leprae [2] . Tuberculoid leprosy triggers predominantly cellular immunity response , and is also called paucibacillary , because very few are detected at the focus of infection or nasal mucosal membrane . On the other hand , lepromatous leprosy triggers predominantly humoral immunity , and is also called multibacillary , because it is detected in a large amount at the focus of infection and , in particular , from nasal mucosal membrane . Nasal discharge from lepromatous leprosy patients , therefore , is considered as the main source of the infection [3] . Infection of Hansen’s disease has conventionally been considered to occur through close skin contact or through wounds , but recently another infection mode , in which M . leprae in the aerosol from nasal discharge of lepromatous leprosy patients invades into the upper respiratory tract and nasal mucosal membrane to cause infection , has come to be recognized [3–10] . However , the invasion mechanism in this infection mode has not been extensively studied yet . M . leprae cannot be artificially cultured . One possible reason for this is the presence of a large number of pseudogenes . M . leprae has various enzyme-coding genes that are replaced with pseudogenes , and therefore has only a minimum metabolic activity and multiplies in macrophages and Schwann cells . Invasion mechanism of M . leprae into Schwann cells have been studied by Rambukkana , et al . , in details . The study revealed that the binding of M . leprae to dystroglycan of Schwann cells in the presence of laminin-2 requires phenolic glycolipid PGL-1 and 21 kDa protein ( ML1683 ) on the bacteria surface to enter the Schwann cells [11–14] . To infect Schwann cells , M . leprae has to invade the epithelial cells first . The mechanism of M . leprae invasion into the epithelial cells , however , has not been elucidated yet . Meanwhile , gene regions involved in the invasion of Mycobacterium tuberculosis ( M . tuberculosis ) into epithelial cells are already known [15 , 16] . Casali et al . reported that , using adhesin involved in diffuse adherence ( AIDA ) method , the region coded for by 316–531 bp of M . tuberculosis mce1A region ( Rv 0169; 198534–199898 bp , 1365 bp ) is expressed on the surface of E . coli as a polypeptide chain , thereby imparting the E . coli with the ability to invade HeLa cells , that the invasion activity is inhibited by the monoclonal antibody ( Ab ) that recognizes the continuous peptide of InvIII region ( 388–453 bp ) [17–19] . It became clear that M . leprae includes a region ( ML2589 , 1326 bp ) highly homologous to Mce1A protein of M . tuberculosis . Sato et al . reported that a recombinant protein , a 37 kDa protein encoded by 73–921 bp , which is the Mce1A region excluding the signal sequence , was found to have an invasion activity into epithelial cells [20] . However , the active sequence involved in the invasion by M . leprae into epithelial cells has not been identified . The present study was conducted to identify the active sequence in the Mce1A region . In this study , the N-terminus and C-terminus truncated proteins expressed on the E . coli , where E . coli with specific regions are expressed thereon by the AIDA method , and hyperimmune antisera against the invasion region are used to investigate the invasion activity into epithelial cells .
The genomic DNA used in the study was isolated from M . leprae strain Thai 53 , which was maintained at Leprosy Research Centre , National Institute of Infectious Diseases , Japan , as previously described [21 , 22] . The pQE30 plasmid and E . coli M15 ( pREP4 ) were purchased from Qiagen ( Valencia , CA ) . The pQE30 plasmid was used as expression vector . E . coli M15 ( pREP4 ) was used as a host for the vector , as recommended by the manufacturer . The pMK90 plasmid and E . coli UT4400 were obtained from Dr . Riley ( University of California at Berkeley , California , USA ) . In Sanger Center M . leprae strain TN complete genome sequence , mce1A gene is a 1326 bp putative ORF located between positions 3092446 and 3093771 ( NCBI-GeneID: 910890 ) . The mce1A DNA sequence of strain Thai 53 was identical to that of strain TN . It was subcloned into pQE30 vector in a truncated reading frame . The 603 bp ORF deleted at 5’ and 3’ ends of mce1A gene is located between positions 316 and 921 ( Fig 1 ) . This sequence was amplified by polymerase chain reaction ( PCR ) directly from the genomic DNA of M . leprae strain Thai 53 with oligonucleotide primers designed to introduce SacI and HindIII endonuclease restriction sites at the ends . The amplified products were ligated into the pQE30 vector linearized with SacI and HindIII . The use of pQE30 vector allowed the plasmid to express the Mce1A product with a polyhistidine ( 6 × His ) tag at the N-terminus ( r-Mce1A ) . The resultant plasmid was cloned into E . coli M15 ( pREP4 ) by electroporation ( Gene Pulser II , Bio-Rad , Hercules , CA ) , according to the manufacturer’s instructions . Plasmid pMK90 is an ampicillin-resistant pBR322 derivative that expresses a recombinant AIDA protein under the control of its own promotor [23] . The AIDA coding sequence has been altered to remove the native passenger; it consists of a 49-amino-acid signal peptide . A 78-amino-acid linker with the entire 440 amino acid barrel core is incorporated between Xma1 and Xba1 of the multiple cloning site . A 216 bp DNA fragment encoding invX ( M . leprae positions 3092761–3092976 bp ) , 222 bp DNA fragment encoding invY ( M . leprae positions 3092977–3093198 bp ) , 168 bp DNA fragment encoding invZ ( M . leprae positions 3093199–3093366 bp ) was amplified by PCR from a plasmid containing mce1A and cloned into pMK90 , generating UT4400/pMKinvX , UT4400/pMKinvY , and UT4400/pMKinvZ . The correct insert was confirmed by sequencing . The predicted amino acid sequence of InvX is VNADIKATTVFGGKYVSLTTPEHPSQKRLTPQTVIDARSVTTEINTLFQTITLIAEKVDPIKLNLTLSAAAQ ( 316–531 bp ) , the predicted amino acid sequence of InvY is SLAGLGERFGQSIVNGNSVLDDVNSQLPQARHDIQQLASLGDTYANSASDFFDFLNNSIVTSRTINQQQKDLDQ ( 532–753 bp ) , and the predicted amino acid sequence of InvZ is VLLAAVGFGNTGADIFSRSGPYLARGAADLVPTAQLLDTYSPAIFCTLRNYHDIEP ( 754–921 bp ) ( Fig 1 ) . Recombinant protein was expressed and purified according to manufacture’s instruction . Briefly , E . coli M15 [pREP4] containing pQE30/mce1A plasmid was grown overnight in 10-ml superbroth containing 100 μg/ml ampicillin and 50 μg/ml kanamycin . A 500 μl aliquot of bacterial suspension was pelleted , resuspended in 30 ml of superbroth and incubated at 37°C for 1–2 h until OD600 = 0 . 6 . Then isopropyl β-D-thiogalactoside was added to final concentration 1 mM and incubated for 3 h at 37°C . The induced and uninduced r-E . coli strains were analyzed by SDS-polyacryamide gel electrophoresis ( SDS-PAGE ) . The newly expressed protein formed an inclusion body in the r-E . coli host . The inclusion body was therefore purified under denaturing conditions according to the instructions of the expression vector’s respective manufactures . The 6 × His tag Mce1A solubilized with lysis buffer ( 6 M Guanidine , 10 mM Tris—HCl , 100 mM NaH2PO4 , pH 8 . 0 ) was bound to a Ni—NTA resin column equilibrated with lysis buffer , and was eluted by elusion buffer ( 6 M Guanidine , 10 mM Tris—HCl , 100 mM NaH2PO4 , 20–250 mM imidazole , pH 6 . 3 ) . The eluted protein were subsequently refolded with 1 mM dithiothreitol ( Sigma , St . Louis , MO , USA ) and 0 . 1 mM phenylmethylsulfonyl fluoride ( Sigma ) by dialysis , gradually removing guanidine . The r-Mce1A was finally purified and refolded as a soluble protein . The purified r-Mce1A protein ( 2 μg ) is migrated using SDS-PAGE , and a single band was confirmed with Coomassie brilliant blue R-250 staining . The Ab against the Mce1A protein was prepared in BALB/c mice ( a 45 kDa recombinant Mce1A protein prepared previously using E . coli was used as the immunogen ) . The r-45 kDa- Mce1A protein was used for Ab production because it was most abundantly expressed in the E . coli host that we used . The r-45 kDa-Mce1A protein was mixed with Titer Max Gold ( AdipoGen Life Sciences , Liestal , Switzerland ) of the same amount . Approximately 100 μg of the protein was administered subcutaneously at five sites in four 7-weeks-old BALB/c mice , followed by two booster injections of 100 μg each 2 and 4 weeks after the first injection . Regarding the specificity of the Ab , Western blot analysis revealed that it reacts with the whole-cell lysate of M . leprae strain Thai 53 and this was used for experiment . A bacterial pellet ( containing ≈ 107 organisms ) of M . leprae strain Thai 53 that had been multiplied in footpads of athymic nude mice , was fixed in 3% glutaraldehyde in phosphate buffer saline ( PBS ) pH 7 . 6 for 24 h , washed five times in PBS and then exposed at 4°C for 16 h to a 1:1000 dilution of the mice Ab raised against Mce1A . The suspension was then washed and incubated at 4°C for 16 h with colloidal gold suspension containing 5 nm gold particles ( 1 . 9 × 1013 particles ml-1 ) conjugated to anti-mouse IgG goat Ab ( Amersham/GE Health Care Life Science , Tokyo , Japan ) . The cells were washed again five times in PBS , stained with 0 . 1% uranyl acetate in water and examined with a HITACHI model H-15 electron microscope . HeLa cells and RPMI2650 cells were purchased from America Type Culture Collection ( ATCC , Manassas , VA ) . HeLa cells ( ATCC CCL-2 ) were maintained with Dulbecco’s modified Eagle’s media ( DMEM; Invitrogen , Carlsbad , CA ) supplemented with 50 μg/ml gentamicin ( GM ) and 10% fetal bovine serum ( FBS ) ( JRH Bioscience , Lenexa , KS ) . RPMI2650 human epithelial nasal septal cell line ( ATCC CCL30 ) was grown in Eagle’s minimum essential medium ( EMEM; Invitrogen , Carlsbad , CA ) supplemented with 50 μg/ml GM and 10% FBS . Cells were maintained in culture and for the assay , were detached from the plastic by using 0 . 25% Trypsin-EDTA ( 1× ) with phenol red ( Gibco , Grand Island , NY , USA ) at 37°C . The cells were then centrifuged at 280 × g for 7 min at 4°C , counted in Neubauer hemocytometer , and plated into tissue culture well or flask at 37°C in a 5% CO2 atmosphere . A 30 μl of stock suspensions of 1 . 1 μm diameter polystyrene latex beads , containing 5 × 108 beads/ml ( Sigma ) , were mixed in 150 μl of PBS containing 50 μg/ml of each set of protein and incubated for 16 h at 37°C . After incubation , the samples were centrifuged at 7000 × g and resuspended in 750 μl of PBS . A 500-μl sample of this suspension was added to a near-confluent cultured cell monolayer grown in a 25-cm2 flask containing 7 ml of appropriate media for cultured cells . The cells were incubated for 5 h at 37°C in a CO2 incubator , washed four times with PBS and one time with 0 . 1 M cacodylate phosphate buffer ( pH 7 . 6 ) , and then collected with cell-scraper ( Becton Dickinson , Japan ) . The collected cells were fixed with 2% glutaraldehyde in 0 . 1 M cacodylate phosphate buffer ( pH 7 . 6 ) at 4°C overnight , post-fixed with 1% osmium tetroxide in PBS , dehydrated through graded ethanol solutions and embedded in Spurr’s low-viscosity embedding media . The ultrathin sections were stained with uranyl acetate and lead citrate and examined with a JEM-1200EX ( JEOL , Tokyo , Japan ) transmission electron microscope . Coated beads with bovine serum albumin ( BSA ) fraction V ( Boehringer Mannheim , GmbH , Germany ) were used as negative controls . E . coli ( UT4400/pMKinvX ) cells were fixed onto microscope slides with 0 . 4% paraformaldehyde for 10 min at room temperature , and non-specific binding was blocked by incubation in 1% ( wt/vol ) BSA for 30 min . Slides were incubated for 1 h with a 1:200 dilution of a rabbit Ab raised against InvXa , InvXb , InvXc , and InvXd , washed , and incubated with 1:1000 dilution of fluorescein isothiocyanate-labeled anti-rabbit Ab ( Abcam Plc , Cambridge , UK ) for 30 min . Normal rabbit IgG was used for labelling for the negative control . After extensive washing , the coverslips were mounted . Slides were viewed on an Olympus BX51 inverted microscope with an epifluorescence attachment . Anti-InvXa , anti-InvXb , anti-InvXc , and anti-InvXd Abs were added in the amount of 1:200 to E . coli that externally express UT4400/pMKinvX by AIDA adjusted to 1 × 108 CFU/ml . This was allowed to react on a rotating platform at 4°C overnight to make Ab-treated bacteria and the viable bacteria were counted . E . coli externally expressing proteins by AIDA were allowed to react with IgG from healthy control rabbits in a similar manner as the control , where this was used as the bacteria untreated by Ab . After the medium for RPMI2650 cells , which were monolayer-cultured in a 24-well plates , 5 × 105 cells/well , was replaced with a medium not containing antibiotic agent , the Ab-treated bacteria and untreated bacteria were added at a bacteria to cells ratio of 30:1 . After culturing in CO2 incubator at 37°C for 3 h , the surface of the cells were washed with PBS five times , and the medium was replaced with a 100 μg/ml GM-appended DME medium to kill the bacteria outside the cells , followed by additional incubation for 2 h . The surface of cells was washed with PBS , and then 0 . 1% Triton X-100-added PBS was added in the amount of 1 ml/well to break the cells and the bacteria inside the cells were harvested . The harvested bacteria suspension liquid was serially diluted 10 times with PBS , and then was applied to Heart Infusion agar medium ( Nissui , Tokyo , Japan ) . This was left overnight at 37°C , and then the colonies were counted to determine the number of bacteria entered into the cells . The cultured cells were prepared in the amount of 3 wells each , and the average of each well and standard deviation were calculated and the result was presented on a graph . This study was approved by the Institutional Animal Care and Use Committee ( Permission number: 2013153 ) and carried out in accordance with the KITASATO University Animal Experimentation Regulations .
Immunoelectron microscopy was employed to determine whether M . leprae expressed the Mce1A protein on the cell surface . The bacilli expressing Mce1A protein were pretreated with an Ab raised against r-45 kDa Mce1A protein , and were followed by incubation with anti-IgG Ab-conjugated colloidal gold particles ( Fig 2 ) . The immunoelectron microscopic study revealed that the native Mce1A protein is expressed on the surface of bacilli . This confirms that the M . leprae not only expresses Mce1 , but the Mce1 is transported to the cell surface and sufficiently presented such that it can bind the Ab against it . The active sequence involved in the invasion into the epithelial cells was investigated in the following manner . The r-lep37 kDa protein , which had been prepared in the previous experiment using r-lep45 kDa protein as the reference by truncating the C terminus to 308 aa ( 922 bp ) , was further truncated to 105 aa ( 315 bp ) from N terminus to provide r-lep27 kDa protein where the proteins using were expressed using an E . coli expression system ( Fig 1 ) . Each of the truncated protein was observed for invasion activity into HeLa cells using an electron microscope . In this observation , images of beads coated with r-lep37 kDa protein and beads coated with r-lep27 kDa protein invading into the cytoplasm of HeLa cells were captured , but BSA-coated beads , which are the negative control , were not found to invade the cytoplasm ( Fig 3 ) . This result suggest that the active sequence is present between 316–921 bp , which encodes r-lep27 kDa protein . The active sequence was further investigated . The 316–921 bp region was divided into invX; 316–531 bp , invY: 532–753 bp , invZ: 754–921 bp , and each of the regions was incorporated into AIDA vector to produce a recombinant E . coli externally expressing the proteins ( Fig 1 ) . The E . coli externally expressing the proteins by the AIDA method were observed for invasion activity into HeLa cells and RPMI2650 cells under the electron microscope . E . coli expressing InvX ( UT4400/pMKinvX ) was found in abundance in the cytoplasm . E . coli expressing InvY ( UT4400/pMKinvY ) , InvZ ( UT4400/pMKinvZ ) , UT4400 , and UT4400/pMK90 were observed present around the cells but not inside the cytoplasm ( Fig 4 ) . These results suggest that the active sequence is present in 316–531 bp ( invX ) . Next , using a GM protection assay , the number of bacteria which entered into RPMI2650 cells was determined in colony forming units ( CFU ) . To determine uptake of the host E . coli cells using a GM protection assay , we assessed the invasive ability of InvX , InvY and InvZ expressing E . coli cells showed invasion levels at the 3 h time point . In RPMI2650 cells , invasive activity of InvX-expressing E . coli was significantly higher than that of InvY , InvZ , and negative control ( Fig 5 ) . The result was similar to the observations by electron microscopy . Invasion activity into nasal mucosa epithelial cells was successfully imparted to an E . coli by externally expressing the InvX region of M . leprae on the E . coli . The InvX mediates the nasal epithelial cells invasion by non-pathogenic E . coli . The InvX region within Mce1A protein is then sufficient for the invasion of E . coli into the cells . Indirect immunofluorescence was used to determine which regions of Mce1A are sufficient to confer invasive ability to E . coli . In order to examine whether the Abs recognize each of the regions , fluorescence immunostaining was conducted on the Abs . Fluorescence microscopy revealed bacterial surface binding of the InvX Abs by their binding of labelled secondary Abs of fluorescence goat anti-rabbit IgG ( Fig 6 ) . In order to investigate an active site involved in the entry of Mce1A protein of M . leprae into nasal mucosal cells , we analyzed inhibitory effects of the resultant Abs on the cell uptake of InvX-expressing E . coli by the inhibition assay . As shown in CFU analysis , the InvX-expressing E . coli pretreated with anti-InvXa Ab , anti-InvXb Ab , and anti-InvXd Ab had significantly lower entry than the IgG control , but there was no significant difference in pretreatment with anti-InvXc Ab and IgG control ( Fig 7 ) . These findings suggest that the invasion activity was most suppressed when using Abs to cover the polypeptide chain encoded by 316–387 bp and expressed on the surface of E . coli .
A number of studies have been conducted on the infection mode of M . leprae . In 1955 , Khanolkar et al . reported that M . leprae infection of M . leprae occurs by normal skin contact [3] . However , in 1963 Weddell et al . revealed that the infection does not occur unless the bacteria is inoculated under the skin[25] . Rees et al . induced immune suppressed mice to inhale an aerosols containing M . leprae which successfully infected the mice via upper airway [4] . Following this , Chehl et al . revealed that transnasal infections of M . leprae of nude mice was possible [5] . From these studies , it became clear that the infection from aerosol containing M . leprae and through the nasal membrane can be established . However , as of today , only limited studies have been conducted regarding molecular mechanisms involved in the invasion . The Mce region is present in tuberculosis complex such as M . tuberculosis and Mycobacterium bovis , as well as in atypical mycobacteria such as Mycobacterium avium and Mycobacterium intracellulare [26] . Chitale et al . revealed that this Mce1A protein involved in the invasion into epithelial cells is expressed only in tuberculosis complex [16] . We had found that M . leprae has a region highly homologous with to the Mce1A region of M . tuberculosis , and so far have prepared a recombinant protein ( Mce1A protein ) encoded by mce1A region ( ML2589; 3092446 to 3093771 , 1326 bp ) of M . leprae to investigate invasion activities to epithelial cells [15 , 20] . In the present study , we have confirmed that the Mce1A protein was actually expressed , as a native protein , on the surface of M . leprae , and prepared a recombinant protein by truncating the N terminus and C terminus of Mce1A region of M . leprae to investigate the invasion activity into the epithelial cells . As a result , it was found that invasion activity is maintained even if 105 aa ( 315 bp ) is truncated from N terminus and 308 aa ( 922 bp ) is truncated from C terminus . Next , 316 bp to 921 bp region was divided into 3 parts , and each part was incorporated into an AIDA vector , where each region was externally expressed as a polypeptide chain to investigate whether the ability to invade can be imparted to non-pathogenic E . coli . These E . coli which externally express the protein by AIDA method were examined for the invasion activity using RPMI2650 cells , where the results indicate that active sequence of M . leprae involved in the invasion into nasal mucosa epithelial cells is present in the 316–531 bp of mce1A region . The most important region of Mce1A protein involved in the invasion of M . tuberculosis into human epithelial cells is called the InvIII cell and this is located between amino acids of position 130 to position 152 [27] . The InvIII region of M . tuberculosis corresponds to InvXb of M . leprae . The sequence of the regions are identical between amino acid of position 1 to position 22—counted from N terminus of InvXb except that amino acids at positions 1 to 3 , 5 , 8 , 9 , 13 are different between M . leprae and M . tuberculosis . Suppression test results also indicated that the most important region of Mce1A protein of M . leprae involved in the invasion into human epithelial cells is different from that of M . tuberculosis . Based on this study , it was found that Mce1A protein of M . leprae is expressed on the bacteria surface as a native protein , as it is in M . tuberculosis , and that N terminus region of Mce1A protein of M . leprae , in addition to the active region of M . tuberculosis , is involved in the entry . These findings suggest that Mce1A , and in particular the InvX region of this protein , is involved in the invasion of M . leprae into nasal mucosa epithelial cells . Importantly , Ab reagents to the InvX region were developed which will allow confirmatory studies with viable M . leprae , an organism refractory to genetic manipulation . In order to further elucidate the role of this protein in the entry of M . leprae into nasal mucous membrane epithelial cells , rather than using E . coli as a proxy , we plan to use M . leprae in our next study . Since any effective prevention of infective disease depends on the accurate analysis and understanding of the mode of infection and blocking of the pathway of transmission , we are confident that this paper provides valuable information and inspiration for the prevention of Hansen’s disease , including vaccine development and effective control methods targeting the entry protein . | Mce1A protein is a cell surface protein encoded by the mce1A region of mce1 locus of M . tuberculosis and M . leprae , and is involved in the bacteria’s invasion into epithelial cells . Using cloned sub domains of mce1A and peptides synthesized for these sub domains , cell entry studies and binding studies were performed . The present study revealed that the active sequence of M . leprae involved in the invasion into nasal mucosa epithelial cells is present in the 316–531 bp region of mce1A . The Mce1A protein is a good candidate as a contributor to invasion of M . leprae and M . tuberculosis into epithelial cells . The comparative data between Mce1A of M . leprae and M . tuberculosis was relied on to further elucidate the role of specific regions within Mce1A . The most important region of Mce1A protein involved in the invasion of M . tuberculosis into human epithelial cells is called the InvIII region , which is located between amino acids at position 130 to 152 . The InvIII region of M . tuberculosis corresponds to InvXb of M . leprae . The sequences of these regions are identical between amino acids at positions 1 to position 22 as counted from the N terminus , except that amino acids at positions 1 to 3 , 5 , 8 , 9 , 13 are different between M . leprae and M . tuberculosis . | [
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] | 2019 | The unique tropism of Mycobacterium leprae to the nasal epithelial cells can be explained by the mammalian cell entry protein 1A |
Mucosal immunoglobulins comprise mainly secretory IgA antibodies ( SIgAs ) , which are the major contributor to pathogen-specific immune responses in mucosal tissues . These SIgAs are highly heterogeneous in terms of their quaternary structure . A recent report shows that the polymerization status of SIgA defines their functionality in the human upper respiratory mucosa . Higher order polymerization of SIgA ( i . e . , tetramers ) leads to a marked increase in neutralizing activity against influenza viruses . However , the precise molecular mechanisms underlying the effects of SIgA polymerization remain elusive . Here , we developed a method for generating recombinant tetrameric monoclonal SIgAs . We then compared the anti-viral activities of these tetrameric SIgAs , which possessed variable regions identical to that of a broadly neutralizing anti-influenza antibody F045-092 against influenza A viruses , with that of monomeric IgG or IgA . The tetrameric SIgA showed anti-viral inhibitory activity superior to that of other forms only when the antibody exhibits low-affinity binding to the target . By contrast , SIgA tetramerization did not substantially modify anti-viral activity against targets with high-affinity binding . Taken together , the data suggest that tetramerization of SIgA improved target breadth , but not peak potency of antiviral functions of the broadly neutralizing anti-influenza antibody . This phenomenon presumably represents one of the mechanisms by which SIgAs present in human respiratory mucosa prevent infection by antigen-drifted influenza viruses . Understanding the mechanisms involved in cross neutralization of viruses by SIgAs might facilitate the development of vaccine strategies against viral infection of mucosal tissues .
Secretory IgA antibodies ( SIgAs ) play an important role as a first line of defense by inactivating pathogens on mucosal surfaces; this is especially true in the case of viruses such as influenza [1 , 2] . Recently , extensive efforts were made to develop novel vaccines that induce immunity via the mucosal route . SIgA is the major contributor to humoral mucosal immunity and is a key molecule that underpins the action of mucosal vaccines [3 , 4] . Therefore , understanding how SIgA works is important if we are to accelerate development of mucosal vaccines . IgA is the major immunoglobulin isotype in humans; indeed , its production exceeds that of all other immunoglobulin classes combined [2] . In addition , IgA displays a number of features that make it unique among the immunoglobulin classes; the most characteristic of these is its quaternary structure [5] . Most of the IgA in human serum is monomeric ( comprising two α heavy ( H ) and two light ( L ) chains ) . IgA present in external secretions is highly heterogeneous , although the majority is present in the form of polymers in which the heavy chains are covalently linked by a J chain . Moreover , these polymeric IgA antibodies are associated with the extracellular portion of the polymeric immunoglobulin receptor ( pIgR ) , called the secretory component ( SC ) , resulting in SIgA [5] . SIgA is composed primarily of dimers , although some larger polymeric forms , particularly tetramers , are present at low levels [5–10] . These tetrameric SIgA antibodies display greater neutralizing activity against influenza A viruses in the nasal mucosa than monomers or dimers [8 , 9] . However , the molecular mechanisms that underlie these characteristics of tetrameric SIgA remain largely unknown . Therefore , to elucidate these molecular mechanisms and evaluate the impact of SIgA polymerization on protection against viral infections , it is essential to obtain IgA antibodies as monomers , dimers , and tetramers that display identical variable regions; only in this way can we make a fairly accurate comparison of their functions . Although several in vitro methods of generating recombinant polymeric IgA have been reported , they focus mainly on producing dimeric IgA [11–13] rather than tetramers . No one has yet developed a method of generating trimeric or tetrameric IgA molecules . Here , we developed a method of generating recombinant monoclonal human tetrameric SIgAs by co-expressing human αH , L , and J chains plus the SC in mammalian cells . This simple method enabled us to examine the effects of SIgA polymerization on its anti-viral activity against influenza A viruses . We compared the reactivity and functionality of generated broadly neutralizing antibodies ( bnAb ) comprising monomeric IgA , dimeric SIgA , or tetrameric SIgA and found that SIgA polymerization led to a marked increase in activity against viruses to which the antibodies bind with low-affinity , but not with high-affinity at monomeric state . Taken together , the results suggest that SIgA polymerization improves target breadth , but not the peak potency of anti-viral functions of bnAbs against influenza A viruses .
Previous studies report that co-expression of αH , L , and J chains in mammalian cells results in formation of dimeric IgA [11–14] . However , production of polymeric IgA antibodies larger than dimers is restricted [14] . Indeed , even when researchers succeeded in generating some polymeric antibodies larger than dimers , they were not well characterized [13] . In general , trimeric or tetrameric forms of IgA are present in external sections as secretory forms containing a SC . Therefore , to generate polymeric IgA antibodies in secretory form , the SC was co-expressed in mammalian cells along with human α1 heavy ( A1 ) , L , and J chains . Next , IgA antibodies purified from the cell culture supernatant were separated by size exclusion chromatography ( SEC ) . SEC analysis revealed that co-expression of A1 , L , and J chains produced IgA antibodies with three different quaternary structures , corresponding to peak A ( retention volume around 10 . 4 mL ) , peak B ( retention volume around 9 . 3 mL ) , and peak C ( retention volume around 8 . 4 mL ) . Peak C ( with the lowest retention volume corresponding to the largest molecule size ) was increased to a significantly greater extent upon co-expression of the SC ( Fig 1A ) . Furthermore , co-expression of the SC along with a α2 heavy ( A2m2 ) chain instead of A1 ( another subclass of human IgA ) led to a marked increase in production of molecules corresponding to peak C and a reduction in production of those corresponding to peak B ( Fig 1A ) . To characterize these polymeric forms of recombinant IgA1 and IgA2m2 , we analyzed each peak fraction containing IgA antibodies co-expressed with the SC by sodium dodecyl sulfate polyacrylamide gel electrophoresis ( SDS-PAGE ) , and Blue Native polyacrylamide gel electrophoresis ( BN-PAGE ) . SDS-PAGE revealed that the peak fractions corresponding to peaks B and C comprised A1/A2m2 , L , and , J chains plus the SC , suggesting that these antibodies were secretory forms . By contrast , the fraction corresponding to peak A lacked the J chain and the SC ( Fig 1B , left panel ) . BN-PAGE analysis showed that IgA1 in peak B had a molecular weight of around 500 KDa , whereas peak C mainly contained proteins with molecular weight >720 KDa ( Fig 1B , right panel ) . The band observed in peak B was not detected in peak C from IgA2m2 , although the band corresponding to the protein with a molecular weight >720 KDa was detected ( Fig 1B , right panel ) . To determine the molecular size of the recombinant IgA antibodies more accurately , each peak fraction of IgA1 or IgA2m2 ( derived from A1/L/J/SC- or A2m2/L/J/SC-expressing cells , respectively ) was examined by high-mass MALDI-TOF MS . IgA1 samples yielded peaks corresponding to four quaternary structures: a monomer ( Mo , MH+ = 158 . 211 ± 0 . 163 kDa ) in peak A ( Fig 1C ) , a dimer ( Di , MH+ = 407 . 976 ± 0 . 603 kDa ) in peak B ( Fig 1D ) , a trimer ( Tr , MH+ = 561 . 075 ± 0 . 678 kDa ) in peak C , and a tetramer ( Te , MH+ = 716 . 775 ± 0 . 879 kDa ) in peak C ( Fig 1E ) . By contrast , IgA2m2 yielded peaks corresponding to three quaternary structures: a monomer ( Mo , MH+ = 161 . 461 ± 0 . 190 kDa ) in peak A ( Fig 1F ) , a trimer ( Tr , MH+ = 575 . 022 ± 0 . 633 kDa ) in peak C , and a tetramer ( Te , MH+ = 735 . 493 ± 0 . 941 kDa ) in peak C ( Fig 1G ) . Although high-mass MALDI-TOF MS analysis is only a qualitative , and not a quantitative method , the peaks corresponding to the trimer in peak C were much smaller than those corresponding to the tetramer in peak C; this was true for both IgA1 and IgA2m2 , implying that the major quaternary structure in peak C was tetramer ( for both IgA1 and IgA2m2 ) . To rule out the possibility that the peak C fraction comprised aggregates of dimeric SIgA , we determined the ratios of each SIgA1 or SIgA2m2 subunit in the peak B or C fraction . We performed LC-MS analysis of marker peptides selected for respective IgA subunits after addition of corresponding stable isotope-labeled internal standard peptides followed by trypsin digestion . The ratio of H:L:J:SC of the peak C derived from both of IgA1 and IgA2m2 was approximately 8:8:1:1 , whereas that of peak B derived from IgA1 was approximately 4:4:1:1 ( Fig 1H ) . This was consistent with a previous report of human tetrameric IgA [6] , and confirmed that majority of polymeric IgA molecules in the peak C fraction were tetrameric , and not dimeric ( ratio , 4:4:1:1 ) or trimeric ( assumed ratio , 6:6:1:1 ) . Therefore , the peak A , B , or C fractions generated by co-expression of SC and A1/A2m2 , L , and J chains were labeled monomeric , dimeric , or tetrameric , respectively . For further confirmation of the structures of this recombinant tetrameric SIgA antibody in peak C , we visualized the quaternary molecular architecture of the SIgA1 ( A1Te ) or SIgA2m2 ( A2m2Te ) molecules in the peak C fraction using high-speed atomic force microscopy ( HS-AFM ) . HS-AFM revealed that peak C contained molecules with eight radial arms ( A1Te ) or more than six arms ( A2m2Te ) , a similar quaternary structure to that of tetrameric SIgA derived from human nasal mucosa , but not similar to trimeric IgA; this also suggests most of the molecules in this fraction were tetrameric ( Fig 1I ) . Taken together , the data show that co-expression of SC along with IgA1/IgA2m2 heavy , light , and J chains in mammalian cells increases production of recombinant tetrameric monoclonal SIgAs , which possess a characteristic quaternary structure corresponding to tetrameric SIgAs found in human external secretions . In a previous study , we showed that trimeric/tetrameric SIgAs in the human nasal mucosa display greater neutralizing activity against influenza A viruses than monomeric immunoglobulins [8 , 9] . To reveal the mechanism underlying this polymerization-mediated antibody activity enhancement , recombinant monomeric , dimeric or tetrameric monoclonal SIgAs possessing variable regions of antibody clone F045-092 , a bnAb against influenza A viruses [15 , 16] , was prepared . It was reported by Ohshima et al . that clone F045-092 IgG possesses binding activity against all H3N2 viruses isolated during 1968 to 2004 , as well as some H1N1 , H2N2 , and H5N1 viruses [16] . The antibody recognizes the receptor-binding domain on the hemagglutinin ( HA ) protein of influenza A viruses and shows hemagglutination inhibition ( HI ) activity and neutralization ( NT ) activity [15 , 16] . Antibodies with HI activity block the interaction between the receptor-binding domain located on the HA head and its sialic-acid receptor [17] . In addition , HI activity is the main component of anti-influenza virus immunity in vivo , and correlates with the level of protection against influenza in humans . At first , to determine whether polymerization of monoclonal SIgAs influences their reactivity with HA proteins of influenza A viruses , we examined the reactivity of monomeric IgA1 ( A1Mo ) , dimeric SIgA1 ( A1Di ) , tetrameric SIgA1 ( A1Te ) , monomeric IgA2m2 ( A2m2Mo ) , and tetrameric SIgA2m2 ( A2m2Te ) harboring identical variable regions derived from F045-092 against recombinant HA proteins from A/Sydney/05/97 ( H3N2; Syd05 ) , A/New York/55/2004 ( H3N2; NY55 ) , A/New York/39/2012 ( H3N2; NY39 ) , A/Victoria/210/2009 ( H3N2; Vic210 ) , A/Victoria/361/2011 ( H3N2; Vic361 ) , A/New Caledonia/20/99 ( H1N1; NC20 ) , A/Japan/305/1957 ( H2N2; JP305 ) , and A/Indonesia/05/2005 ( H5N1; Ind05 ) by Enzyme-linked immunosorbent assay ( ELISA ) . The reactivity of IgA1 antibodies to HA proteins increased significantly in line with molecular size ( the exception was NY55 HA ) ( Fig 2A and 2B ) . In particular , the reactivity of tetrameric SIgA1 against Vic210 HA , Vic361 HA , NC20 HA , and Ind05 HA was significantly higher than that of dimeric SIgA1 . By contrast , the three forms of IgA1 antibodies ( Mo , Di , and Te ) showed no difference in reactivity to NY55 HA; all three showed good potency , indicating that the effects of SIgA1 polymerization might be limited by the binding mode between the epitope and paratope . Meanwhile , A2m2Te showed markedly higher reactivity against HA proteins of all viruses than A2m2Mo ( Fig 2C and 2D ) . Increase in reactivity of F045-092 IgA1 and IgA2m2 by polymerization could also be observed against whole virions of NC20 virus ( S1 Fig ) . These results suggest that tetramerization boosts the avidity of the F045-092 SIgA antibody to HA on the virions . In order to fairly compare binding characteristics of F045-092 IgG1 , A1 , and A2m2 against a recombinant HA protein , we examined the binding dynamics of these antibodies to JP305 HA by surface plasmon resonance ( SPR ) . A1Mo and A2m2Mo dissociated less well from JP305 HA than IgG1 ( Fig 3A ) . In addition , A1Te and A2m2Te dissociation rates were evidently lower than those of their smaller molecular sizes , A1Mo , A1Di , or A2m2Mo , respectively ( Fig 3B and 3C ) . Thus , although isotype conversion to IgA backbone from IgG backbone influenced the antibody reactivity , IgA tetramerization boosted the antibody avidity of IgA molecules , which is likely to be through different mechanisms from the effect by the isotype conversion from IgG to IgA backbone . Polymerization of the F045-092 antibody using an IgA backbone increased its reactivity with several HA proteins . However , the biological activity of antibodies specific for influenza viruses , which is designated as the “functionality” of an antibody here , does not necessarily correspond to the binding activity observed in an ELISA , which is designated as the “reactivity” of an antibody here . The HI and NT assays are the most widely accepted assays for measuring the functional activity of antibodies against influenza viruses [18] . Although both assays measure the functionality of inhibitory antibodies , they measure immune responses in different ways . The NT assay measures the ability of antibodies to inhibit virus infection of mammalian host cells . By contrast , HI activity correlates only with the ability of antibodies to inhibit virus attachment to host cells via sialic-acid receptors; thus , the readout from the HI assay emphasizes steps that occur very early during infection [17] . Therefore , the two activities do not necessarily correlate , and the difference depends on how the antibody interacts with its target antigen . The effect of SIgA polymerization on HI activity of F045-092 differed by virus strain and IgA antibody subclass . Here , we found that the HI activities of A2m2Te against Syd05 or NY55 viruses were significantly higher than that of the F045-092 antibody with an IgG1 backbone ( Fig 4A and 4B ) . In addition , the HI activity of all of polymerized SIgAs ( A1Di , A1Te , and A2m2Te ) against Vic361 or NC20 viruses was markedly higher than that of IgG1 ( Fig 4E and 4F ) . By contrast , the HI activity of SIgAs against NY39 or Vic210 viruses was similar to that of IgG1 ( Fig 4C and 4D ) . The degree of NT activity enhancement by SIgA polymerization also differed by the virus strain used and the IgA antibody subclass . The NT activity of the polymerized SIgA against Syd05 or NY39 viruses was no different from that of IgG1 ( Fig 4I and 4K ) , but NT activity against Vic210 or NC20 viruses was significantly higher than that of IgG1 ( Fig 4L and 4N ) . However , only the IgA1 polymer ( A1Di or A1Te ) showed higher NT activity against NY55 or Vic361 viruses than IgG1 ( Fig 4J and 4M ) . Enhancement in functionality of F045-092 by SIgA polymerization could also be seen against the JP305 and Ind05 viruses , each of the H2N2 and H5N1 subtype , respectively ( Fig 4G , 4H , 4O and 4P ) . Of note , for JP305 and Ind05 virus strains , against which F045-092 IgG1 did not possess HI activity , significant increases in HI activity could be observed by just converting F045-092 from IgG1 to A1Mo form ( Fig 4G and 4H ) . A significant increase could also be observed in NT activity against Ind05 virus by the same conversion ( Fig 4P ) . This may be , in part , due to the difference in F045-092 avidity to HA between IgG1 , and IgA monomers including A1Mo and A2m2Mo ( Fig 3A ) . Furthermore , virus neutralization experiments in the mouse respiratory tract indicated that there is a slight possibility that polymeric SIgA have additive effects on protection from influenza virus infection in vivo even in the absence of increased NT activity in vitro ( S2 Fig ) . Taken together , the results suggest that although there are some differences in the levels of functional enhancement in the HI or NT assays , polymerization of SIgA led to a significant increase in functionality against some viruses . The effects of SIgA polymerization on functionality against influenza A viruses were more complex; Fig 4 shows that some viruses were more susceptible to SIgA polymers than others . The degree of enhancement may be defined by the antibody clone’s inherent binding affinity to various HA molecules . To clarify the relationship between reactivity and altered anti-viral activity shown in Fig 4 induced by SIgA polymerization , we plotted the HI and NT activities of IgG1 , IgA monomer , and IgA polymers against six viruses ordered based on the reactivity to F045-092 with an IgG1 backbone , which is defined here as the “original” reactivity . Syd05 , NY55 , NY39 , Vic210 , Vic361 , and NC20 viruses , against which F045-092 possessed both HI and NT activity at the IgG1 form , were included in the analyses . As a result , we found that the polymerized antibodies showed increased anti-viral activity ( i . e . , HI and NT activity ) against the viruses to which they originally bound with relatively low-affinity ( Fig 5A , 5B , 5D and 5E ) . By contrast , tetramerization of SIgA2m2 increased its anti-viral activity against almost all viruses when compared with the monomeric IgA2m2 antibody , although the monomeric IgA2m2 antibody showed lower activity than the IgG1 form; this suggests that the IgA2m2 backbone has some functional disadvantages compared to the IgG1 or IgA1 backbones , and that tetramerization of SIgA2m2 might overcome the disadvantages inherent in the IgA2m2 backbone ( Fig 5C and 5F ) . To determine more accurately how SIgA polymerization affects reactivity and functionality of antibodies , we measured the increase in reactivity and anti-viral activity ( HI or NT activities ) and compared them with those of the monomeric forms . The data clearly show that SIgA1 dimerization increased anti-viral activity ( HI and NT activities ) , and that tetramerization of SIgA1 and SIgA2m2 led to a significant increase in anti-viral activity against viruses with low original reactivity . Polymerization of SIgAs had a negligible effect on anti-viral activity against viruses with relatively high original reactivity such as Syd05 , NY55 , NY39 , and Vic210 when compared with that against viruses with low original reactivity , such as Vic361 and NC20 ( Fig 5G , 5H and 5I ) . By contrast , no significant difference in the effect of IgA polymerization on antibody reactivity could be observed among the six viruses ( Fig 5G , 5H and 5I ) . In addition , the effects of SIgA1 or SIgA2m2 tetramerization on anti-viral activities against the NC20 virus , which exhibited the lowest original reactivity against , were significantly greater than the effects of SIgA1 dimerization ( Fig 5J ) . Furthermore , SIgA1 tetramerization led to a higher-fold increase in NT activity than in HI activity against the NC20 virus , although SIgA1 dimerization led to a similar degree of increases in NT and HI activity ( Fig 5J ) . On the other hand , SIgA2m2 tetramerization led to a higher-fold increase in HI activity rather than in NT activity against the NC20 virus . The differing effects of polymerization on SIgA1 and SIgA2m2 functionality suggest that each subclass of polymerized SIgA has a distinct mechanism of action when it comes to inhibiting influenza A virus infection . To summarize , tetramerization of both IgA subclass increased anti-viral activities against influenza A viruses . These functional enhancements of antibodies appeared striking against viruses to which antibodies showed relatively low original reactivity , and no evident functional enhancements could be observed against viruses to which antibodies showed relatively high original reactivity . The number of antigen binding sites per antibody molecule did not simply correlate with the degree of increase in antibody reactivity nor functionality . Taken together , polymerization of a bnAb IgA antibody leads to an increase in its target breadth , but not in its peak potency of anti-viral functional activities ( Fig 5K ) .
In the present study , we show that tetrameric monoclonal SIgA antibodies could be successfully generated by co-expression of antibody chains with the human SC in a mammalian cell line . Previous studies have shown that co-expression of αH , L , and J chains in vitro induces production of polymeric IgA , which comprises mainly dimeric IgA and some multimeric IgA antibodies [11–14] . However , these multimeric IgA antibodies were not characterized in detail , and differences in function between dimeric and multimeric IgA antibodies have remained obscure . The method described in the present study enables efficient production of recombinant tetrameric SIgA monoclonal antibodies , which enabled detailed examination of the molecular features and functions of SIgA antibodies of different valence . The observation that the co-expression of A2 , L , and J chains and the SC enhances the production of polymeric SIgA antibodies is inconsistent with previous reports [11 , 12] showing that stable transfection of a mouse myeloma cell line ( Sp2/0 ) expressing human SC and mouse-human chimeric dimeric IgA1 produced dimeric but not tetrameric SIgA [12] . In addition , CHO cells constitutively expressing human A2 , L , and J chains and the SC also produced dimeric SIgA but no tetrameric SIgA [11] . However , these studies used stable cell lines constitutively expressing antibodies; these were obtained by a repeated cloning process in which cells expressing dimeric SIgA were selected . These methods may emphasize production of dimeric SIgA alone and create bias toward selecting cell clones that do not produce multimers larger than dimers . On the other hand , some IgA-producing hybridomas secrete trimeric and tetrameric IgA spontaneously in the absence of the J chain and SC [19 , 20] , indicating that αH chains have the intrinsic ability to form tetramers . However , plasma cells secreting polymeric IgA in vivo synthesize the J chain covalently linked to the αH chain [21] , and IgA-producing cells in mucosal tissues express the J chain whereas IgA-positive cells in normal bone marrow do not [22] . These conflicting observations indicate that tetramerization of IgA may vary according to the intracellular environment . Here , we used a transient expression system based on Expi293F human cells derived from the 293 cell line . This system is specialized for recombinant protein expression and as such may not accurately and fairly reflect the molecular machinery involved in in vivo protein syntheses in specific types of cells , such as antibody-secreting cells , and may involve mechanisms distinct from the naive pathway used in vivo to generate tetrameric IgA antibodies . Although the molecular mechanism ( s ) responsible for the marked effects of SC co-expression on tetramer formation remain unclear ( and appear to be artificial ) , we used sophisticated analytical chemistry techniques such as high-mass MALDI-TOF MS , HS-AFM , and LC-MS to show that tetrameric SIgAs obtained by this method have a molecular architecture similar to that of antibodies produced in vivo , and that they are fully functional in term of inactivating influenza A virus . We previously reported that polymeric SIgAs larger than dimers play critical in vivo roles in protecting the human upper respiratory mucosa from virus attack , although the molecular mechanisms that underlie these particular characteristics of polymeric SIgA remain largely unknown [9] . The recombinant monoclonal IgA or SIgA ( monomers , dimers , and tetramers ) prepared herein served as fundamental tools for evaluating the impact of SIgA polymerization on anti-viral protection . Comparison of the reactivity and functionality of monomeric IgA , dimeric SIgA , and tetrameric SIgA F045-092 antibodies revealed that SIgA polymerization led to a marked increase in functionality against viruses to which the antibodies bound with relatively low affinity , but not with high affinity . This may suggest that in the case when the paratope and epitope of an antibody completely matches , the anti-viral activities against the virus will reach maximum level at monomeric state , leaving no room for further boosting of anti-viral activity by SIgA polymerization . Furthermore , against viruses with low affinity , the increase in functionality ( e . g . , HI and NT activity ) due to tetramerization is much higher than the increase in reactivity , indicating that mechanisms other than increased avidity could be involved in functional enhancement . Therefore , polymerization of IgA may increase the breadth , but not the peak potency , of antibody function . In addition , recent reports present conflicting data on the effect of IgA polymerization; these reports focused on improving the functionality of bnAb against HIV1 by swapping the Fc region from IgG to IgA , and then polymerizing the IgA , though among these studies , the effect of IgA polymerization has remained controversial [23–29] . These reports used various viruses and bnAb antibody clones . Based on our observations that the degree of functional enhancement of IgA via polymerization might depend on the original affinity between the antibody and the antigen , we believe that the differences among data reported in the previous studies are due to differences in the viruses and clones used . Furthermore , the effect of dimerization of SIgA on antibody reactivity and functionality was markedly lower than that of tetramerization of SIgA ( as evidenced by our observations ) , and previous reports did not examine the function of tetrameric forms . Of note , in addition to the valence of IgA antibodies , the antibody subclasses and isotypes , which define the structure of the antibody backbone , may also influence the reactivity and functionality of antibodies [30 , 31] . Human α1 and α2 H chains comprise one variable and three constant regions ( CH1 , CH2 , and CH3 ) , and harbor unique hinge regions between CH1 and CH2 . The hinge region of IgA1 comprises 26 amino acids , whereas that of IgA2 comprises 13 . The extended hinge region of IgA1 makes it highly susceptible to IgA1-specific proteases produced by several bacterial pathogens . However , this extended hinge provides greater segmental flexibility than that observed for IgA2 . Thus , IgA1 may be better at binding antigens spaced at greater distances , which may enable recognition of pathogens ( such as viral particles ) possessing repeated antigenic structures spaced along their surfaces . Moreover , IgA1 accounts for most of the increase in anti-influenza virus IgA antibody titers observed in the human upper respiratory tract after influenza virus infection [32] . By contrast , antibodies in colostrum or saliva , which are specific for bacterial lipopolysaccharide and lipoteichoic acid , are predominantly IgA2 , suggesting that the type of antigen may influence the subclass-specific IgA response [33] . The disadvantage of IgA2 antibodies in anti-viral activity could also be observed in the data presented in the current study . Whereas the HI and NT activities of monomeric IgA1 are higher than those of IgG1 ( Fig 5B and 5E ) , the anti-viral activities of monomeric IgA2m2 are generally lower than those of IgG1 ( Fig 5C and 5F ) . Since IgA2m2 could successfully boost these anti-viral activities by SIgA tetramerization , it could be assumed that SIgA tetramerization may be functioning as a way to overcome these functional disadvantages of monomeric SIgA2m2 antibodies . The fact that a significant increase in reactivity against H3 NY55 HA by SIgA tetramerization was only seen in IgA2m2 and not in IgA1 is also in accordance with such theories ( Fig 2 ) . In addition , we found that tetramerization of IgA1 and IgA2 increases different functions ( HI activity and NT activity ) , which are distinct indicators of influenza virus infection ( Figs 2 , 5H and 5I ) . This suggests that each polymerized SIgA subclass has a distinct mechanism of action against influenza virus infections , and that tetrameric SIgA1 ( which shows increased NT activity ) might be more potent against influenza virus infections than tetrameric SIgA2 . This may explain the molecular mechanisms underlying IgA subclass-specific immune responses to pathogens . The observations made herein broaden our knowledge about the functions of tetrameric SIgA . Nevertheless , further work is needed if we are to obtain a more detailed picture of the functions of tetrameric SIgAs and the underlying molecular mechanisms . The method described herein may form the foundation for further studies designed to examine the impact of polymerizing antibody clones with different characteristics; this may enable us to generate bnAb against other virus infections including HIV and influenza viruses . In conclusion , the comparison of reactivity and functionality among monomeric IgA , dimeric SIgA , and tetrameric SIgA monoclonal antibodies obtained by a novel method described herein revealed that SIgA tetramerization dramatically enhanced their functionality against viruses , to which the antibodies bind with relatively low affinity , but not with sufficient affinity , indicating SIgA tetramerization improves target breadth , but not peak potency of anti-viral functions of a bnAb against influenza A viruses . This phenomenon suggests the potential of SIgA antibodies to prevent infection of antigenically drifted influenza viruses at the human respiratory mucosa .
The study using embryonated chicken was carried out in compliance with the Standards Relating to the Care and Management of Laboratory Animals and Relief of Pain ( the Ministry of Environment Notification No . 88 ) . The use of embryonated chicken eggs before hatching is not considered animal use . Embryonated eggs were purchased from Omiya Kakin Laboratory ( Saitama , Saitama , Japan ) , inoculated with influenza viruses at day 8–11 , incubated at 35°C for 2 days , and then incubated at 4°C overnight before allantoid fluid harvesting . For mice experiments , 7-week-old female BALB/c mice were purchased from Japan SLC ( Hamamatsu , Shizuoka , Japan ) . Animal studies were performed in strict accordance with the Guidelines for Proper Conduct of Animal Experiments of the Scientific Council of Japan . All animal experiments were conducted in strict compliance with animal husbandry and welfare regulations in handled in biosafety level two animal facilities according to the guidelines of the Animal Care and Use Committee of the National Institute of Infectious Diseases , and were approved by this Committee ( approval no . 118088 ) . Mice were monitored daily for clinical signs of morbidity and mortality up to 21 days post infection . The human endpoint was used for mice that lost 30% or more of their initial body weight during the study . When the animals met the criteria , they were scored dead and euthanized under excess isoflurane anesthesia according to institutional guidelines . Madin-Darby canine kidney ( MDCK , ATCC ) cells were maintained in Dulbecco’s modified Eagle’s medium ( DMEM , Gibco ) containing 10% FBS ( FBS , Gibco ) and pen-strep mix ( 100 units/ml of penicillin and 100 μg/ml of streptomycin , Gibco ) at 37°C/5% CO2 [34] . Expi293F ( ThermoFisher Scientific ) cells were maintained in Erlenmeyer flasks in Expi293 expression medium at 37°C/8% CO2 . Influenza viruses were grown in 8–11-day-old embryonated chicken eggs . The virus strains used in this study were: A/Sydney/05/97 ( H3N2; Syd05 ) , A/New York/55/2004 ( H3N2; NY55 ) , A/New York/39/2012 ( H3N2; NY39 ) , A/Victoria/210/2009 ( H3N2; Vic210 ) , A/Victoria/361/2011 ( H3N2; Vic361 ) , A/New Caledonia/20/99 ( H1N1; NC20 ) , A/Japan/305/57 ( H2N2; JP305 ) , and A/Indonesia/05/2005 ( H5N1; Ind05 ) , and mouse adapted A/Guizou/54/1989 ( H3N2; Gui54 ) . The plasmid harboring the α1H or α2H chain was derived from the γ1HC vector [35] by replacing the IgG1 constant domain with the human IgA1 or IgA2m2 constant domain , respectively . The DNA fragment encoding the human IgA1 constant domain was amplified by PCR using plasmid pFUSE-CHIg-hA1 ( InvivoGen ) as a template . The DNA fragment encoding the human IgA2m2 constant domain was codon-optimized ( for humans ) and synthesized using GeneArt Strings DNA Fragments ( ThermoFisher Scientific ) . To establish the method used to produce tetrameric SIgA antibodies , the Fab regions derived from the B12 clone were used . The DNA fragment encoding the variable region of the H or L chain of the B12 clone was amplified by PCR using cDNA obtained from a single-sorted B cell from a healthy adult volunteer . The DNA fragment encoding the variable region of the H or L chain of F045-092 [16] was codon-optimized and synthesized using GeneArt Strings DNA Fragments ( ThermoFisher Scientific ) . These synthesized DNA fragments were cloned into α1H , α2H , γ1HC , or λLC vectors . Human J chain was synthesized using GeneArt Strings DNA Fragments ( ThermoFisher Scientific ) and cloned into the pCXSN vector [36] . Human SC , consisting of the extracellular domain of the polymeric immunoglobulin receptor [37] , the thrombin recognition site , and a hexa-histidine affinity tag at the C-terminus was synthesized and cloned into the pCXSN vector . To generate IgG , Expi293F cells grown in Expi293 expression medium were diluted to 2 . 5×106 cells/ml and transfected with 100 μg of plasmid ( 35 μg of γ1HC and 65 μg of λLC ) using 267 μl of ExpiFectamine293 Transfection reagent per 100 ml of final culture volume . To generate IgA , Expi293F cells were diluted to 2 . 5×106 cells/ml and transfected with 40 μg of αH , 40 μg of λLC , 20 μg of J chain , and 20 μg of SC using 267 μl of ExpiFectamine293 Transfection reagent in 100 ml of final culture volume . At 16–18 hours post-transfection , 500 μl of ExpiFectamin293 Transfection Enhancer 1 and 5 ml of ExpiFectamin293 Transfection Enhancer 2 were added . Then , 5–7 days later , the cell culture supernatants were centrifuged at 2 , 000×g and filtered to remove cell debris . The supernatants were then purified using CaptureSelect IgG-Fc ( Hu ) ( ThermoFisher Scientific ) or CaptureSelect IgA ( ThermoFisher Scientific ) , according to the manufacturer’s instructions . To prepare monomeric IgA , dimeric SIgA , and tetrameric SIgA , IgA samples purified using CaptureSelect were subjected to gel filtration chromatography on a Superose6 10/300 GL column ( GE Healthcare ) or Superose6 Increase 10/300 GL column ( GE Healthcare ) . The peak fractions corresponding to each structure were collected and concentrated using Amicon Ultracell ( Millipore ) centrifugation units with a cut-off of 30 kDa and the buffers were changed to 20 mM phosphate buffer ( PB ) ( pH 7 . 4 ) using a Zeba Spin Desalting Column ( ThermoFisher Scientific ) . Purified antibodies were analyzed by Blue Native polyacrylamide gel electrophoresis ( BN-PAGE ) on NativePAGE 3–12% Bis-Tris gels ( ThermoFisher Scientific ) and by sodium dodecyl sulfate polyacrylamide gel electrophoresis ( SDS-PAGE ) on NuPAGE 4–12% Bis-Tris gels ( ThermoFisher Scientific ) . NativeMark ( ThermoFisher Scientific ) or Precision Plus Protein All Blue standards ( Bio-Rad Laboratories , Inc . ) were used as a molecular weight markers for BN-PAGE or SDS-PAGE , respectively . The SDS-PAGE gels were stained with SimplyBlue SafeStain ( ThermoFisher Scientific ) . The mammalian cell-derived HA proteins used in this study were: H1 NC20 , H3 NY39 , H3 Vic361 , H3 Vic210 , H3 NY55 , H3Syd05 , H3 BJ353 ( from A/Beijing/353/1989 ( H3N2 ) virus ) , H2 JP305 , and H5 Ind05 . These HA proteins comprise the extracellular domain of HA C-terminally fused to the thrombin site , the trimeric Foldon of T4 fibritin , and a hexa-histidine affinity tag [38] or a Strep-tag II and a hexa-histidine affinity tag . HA proteins were expressed using the Expi293 Expression System ( ThermoFisher Scientific ) , according to the manufacturer’s instructions . Briefly , Expi293F cells grown in Expi293 expression medium in Erlenmeyer flasks were diluted to 2 . 5×106 cells/ml and transfected with 100 μg of a HA-encoding plasmid using 267 μl of ExpiFectamine293 Transfection reagent per 100 ml of culture volume . At 16–18 hours post-transfection , 500 μl of ExpiFectamin293 Transfection Enhancer 1 and 5 ml of ExpiFectamin293 Transfection Enhancer 2 were added . At Day 5 , the medium was clarified by centrifugation at 2 , 000×g , filtered , and purified on a HisTrap excel column ( GE Healthcare ) . HA proteins with a Strep-tag II were purified with Strep-Tactin Superflow resin ( iba ) , according to the manufacturer’s instructions , after purification on a HisTrap excel column . The purified HA proteins were concentrated using Amicon Ultracell ( Millipore ) centrifugation units with a cut-off of 30 kDa and the buffer was changed to phosphate buffered saline ( PBS ) ( pH 7 . 4 ) . The HA proteins were stored at -80°C until use . Stable isotope-labeled peptides ( summarized in Table 1 ) were custom synthesized by Anygen . The internal standard peptides were mixed into 1–2 μg of each SIgA sample in 100 mM Tris-HCl/1 mM CaCl2 ( pH 7 . 6 ) . The samples were reduced with 5 mM dithiothreitol ( Wako ) at 56°C for 30 min and subsequently alkylated with 25 mM iodoacetamide ( Wako ) at room temperature for 30 min . The samples were then digested with sequencing-grade-modified trypsin ( Promega; 1:20 enzyme/substrate ratio ) at 37°C for 16 h . After addition of formic acid to a final concentration of 1% and filtration through a 0 . 45 μm filter , the peptide solutions were analyzed by electrospray LC-MS using an ultra-high resolution quadrupole time-of-flight mass spectrometer maXis II ( Bruker Daltonics ) coupled to a Shimadzu Prominence UFLC-XR system ( Shimadzu ) . Peptide separation was performed using a BIOshell A160 Peptide C18 HPLC Column ( 5 μm particle size , L × I . D . 150 mm × 2 . 1 mm; Supelco ) at a flow rate of 500 μl/min and a column temperature of 80°C with a binary gradient as follows: 98% solvent A ( 0 . 1% formic acid ) for 2 min , linear gradient of 2–50% solvent B ( 100% acetonitrile ) for 4 min , 90% solvent B for 2 min , and 98% solvent A for 2 min . The MS scan was performed over an m/z range of 50–2500 with a frequency of 2 Hz using otofControl version 4 . 0 ( Bruker Daltonics ) . The absolute amounts of respective SIgA subunits were estimated using the peak area ratio of selected marker peptides to that of the corresponding internal standard peptides . Purified antibodies were filtered using Cosmo spin filter H ( Nacalai Tesque , Inc . ) to remove precipitates or debris before SEC analysis . Then , the antibodies were passed through an Agilent Bio SEC-5 500 Å ( 7 . 8×300 mm ) column ( Agilent Technologies ) coupled to an Agilent 1260 Infinity Bio-inert HPLC system ( Agilent Technologies ) . Analyses were performed using 1 μg or more of each antibody sample , with a flow rate of 1 ml/min . PBS ( pH 7 . 4 ) was used as an eluent . Data were analyzed using OpenLAB CDS ChemStation Edition ( Agilent Technologies ) . MALDI-TOF MS analysis was performed using the CovalX HM4 interaction module , with a standard nitrogen laser focusing on mass ranges from 0 to 1 , 500 kDa [8] . Aliquots ( 20 μl ) of each protein sample were pipetted to prepare 2-fold dilutions , each with a final volume of 10 μl . Aliquots ( 1 μl ) of each obtained dilution were mixed with 1 μl of a matrix comprising a re-crystallized sinapinic acid matrix ( 10 mg/ml ) in acetonitrile/water ( 1:1 vol/vol ) and 0 . 1% TFA ( K200 MALDI Kit; CovalX ) . After mixing , 1 μl of each sample was spotted onto the MALDI plate ( SCOUT 384; Bruker ) . After crystallization at room temperature , the plate was introduced into the MALDI mass spectrometer and analyzed immediately in high-mass MALDI mode . The analysis was repeated in triplicate . The following parameters were applied: mass spectrometer , linear and positive mode; ion source 1 , 20 kV; ion source 2 , 17 kV; lens , 12 kV; pulse ion extraction , 400 ns; HM4 gain voltage , 3 . 14 kV; and HM4 acceleration voltage , 20 kV . The instrument was externally calibrated using clusters of BSA and IgG . Three spots per sample were analyzed ( 300 laser shots per spot ) . The presented spectrum corresponds to the sum of 300 laser shots . The MS data were analyzed using CovalX Complex Tracker analysis software , version 2 . 0 . The HS-AFM experiments were performed using a Nano Explorer High-Speed atomic force microscope ( Research Institute of Biomolecule Metrology Co . , Ltd . ) with an Ultra-Short Cantilever ( USC-F1 . 2-k0 . 15; NanoWorld ) . The tetrameric SIgA antibodies [2 μg/ml ( 2 μl in 10 mM PB ( pH7 . 4 ) ) ] were adsorbed onto a mica surface ( Ted Pella , Inc . ) , incubated for 10 min , washed with 20 μl of double-distilled water ( DDW ) , and then subjected to time-lapse imaging in DDW . Images containing 200×200 pixels were obtained at a scan rate of one frame per second ( fps ) . Images were analyzed using SPIP software ( Image Metrology A/S ) . Half-area flat-bottomed microtiter plates ( Costar ) were coated overnight at 4°C with either recombinant HA proteins ( H1 NC20 , H2 JP305 , H3 NY39 , H3 Vic361 , H3 Vic210 , H3 NY55 , H3 Syd05 , or H5 Ind05 ) or whole virions ( H1 NC20 ) . Plates were coated with 50 ng/well for recombinant HA proteins except for H5 Ind05 and 250 ng/well for H5 Ind05 recombinant HA proteins and H1 NC20 whole virions . Plates were blocked for 1 h at 37°C with 1% BSA in PBS ( pH 7 . 4 ) and serially diluted antibody samples were added to each well . Following incubation for 2 h at 37°C , wells were washed three times with PBS containing 0 . 05% Tween 20 . After addition of diluted HRP-conjugated goat anti-human IgA antibody ( Bethyl ) , HRP-conjugated mouse anti-human IgA2 antibody ( abcam ) or HRP-conjugated goat anti-human IgG-Fc fragment antibody ( Bethyl ) plates were incubated for 1 h at 37°C , washed three times , and incubated with One-Step Ultra TMB ELISA HRP substrate solution ( Thermo Fisher Scientific ) . The reaction was stopped with H2SO4 . Absorbance at 450 nm ( reference: 655 nm ) was measured in an iMark Microplate Reader ( Bio-Rad ) . ELISA binding was expressed in terms of the area under the curve ( AUC ) as it better captures changes in both affinity and maximum binding of each antibody [39–41] . Curves and AUCs were constructed using GraphPad Prism software . The reactivity value was defined as the reciprocal of the lowest concentration ( μg/ml ) of antibody that bound to each viral HA protein . The titers of mice serum IgG specific for the HA proteins of H3 BJ353 virus , which was isolated in the same year as the challenge virus , A/Guizou/54/1989 ( H3N2; Gui54 ) virus , were determined by ELISA . Half-area flat-bottomed microtiter plates ( Costar ) were coated ( 250 ng/well ) overnight at 4°C with the HA proteins . Plates were blocked for 1 h at 37°C with 1% BSA in PBS ( pH 7 . 4 ) and serially diluted serum samples were added to each well . Following incubation for 2 h at 37°C , wells were washed three times with PBS containing 0 . 05% Tween 20 . After addition of diluted HRP-conjugated goat anti-mouse IgG-Fc fragment antibody ( Bethyl ) plates were incubated for 1 h at 37°C , washed three times , and incubated with One-Step Ultra TMB ELISA HRP substrate solution ( Thermo Fisher Scientific ) . The reaction was stopped with H2SO4 . Absorbance at 450 nm ( reference: 655 nm ) was measured in an iMark Microplate Reader ( Bio-Rad ) . The antibody titer for a given sample was calculated as the reciprocal of the highest dilution of the test sample that gave an absorbance greater than a cutoff value equal to the mean + 3 standard deviation ( SD ) of 8 two-fold serial dilutions ( starting at 1:20 and ending at 1:2560 ) of the negative control serum ( uninfected mice ) . SPR assay was performed by using Biacore X100 ( GE Healthcare Japan ) . Recombinant trimeric HA proteins of H2 JP305 with a C-terminal His-tag was immobilized on the surface of Sensor Chip NTA ( GE Healthcare Japan ) by using the NTA reagent kit ( GE Healthcare Japan ) according to the manufacturer’s instructions . After trimeric HA immobilization ( 1 μg/ml for 180 seconds ) , the molecular interaction of HA with either IgG or IgA was analyzed with a contact time of 60 seconds and a dissociation time of 600 seconds with an antibody concentration of either 100 μg/ml ( Fig 3A ) or 50μg/ml ( Fig 3B and 3C ) . To compare the degree of antibody dissociation from recombinant HA proteins between multiple antibody forms , sensorgrams obtained from multiple analyses were x and y-axis adjusted ( x = 0 , y = 0: baseline , y = 100: binding ) . HI titers were examined using a microtitration method as previously described , with minor modifications [42] . Briefly , purified antibodies ( in duplicate ) were serially diluted ( two-fold ) , mixed with an equal volume of diluent containing influenza virus equivalent to 4 HA units , and incubated for 10 min at room temperature . Turkey red blood cells ( RBCs ) were added to the mixture , incubated at room temperature , and measurements were taken after 30 min . HI activity was defined as the reciprocal of the lowest concentration ( μg/ml ) of antibody that completely inhibited virus-mediated hemagglutination of RBCs . A microneutralization assay was performed using MDCK cells and 100 TCID50 ( 50% tissue culture infectious doses ) of influenza virus essentially as previously described [43] . Briefly , 2-fold serial dilutions of each sample were mixed with an equal volume of diluent containing influenza virus equivalent to 100 TCID50 . This was added to the wells of a 96-well plate containing a monolayer culture of MDCK cells . Four control wells containing virus or diluent alone were included on each plate . The plates were incubated for 5 days at 37°C/5% CO2 . All wells were observed for the presence or absence of cytopathic effects by light microscopy . NT activity was defined as the reciprocal of the lowest concentration ( μg/ml ) of antibody that neutralized the virus . Mouse adapted A/Guizou/54/1989 ( H3N2; Gui54 ) virus , which could infect mice and could be neutralized by F045-092 antibody was used for mice experiments . Virus was pre-incubated with either F045-092 IgG1 , IgA1 monomer ( A1Mo ) , IgA1 polymer ( unfractionated crude mixture of IgA1 monomers and polymers; A1Poly ) , or PBS prior to mice challenge . 40 LD50 of Gui54 virus pre-incubated with F045-092 antibody ( 0 . 2 μg or 2 μg/head of either IgG1 , A1Mo , or A1Poly ) or PBS were intranasally administered to infect the upper ( 10 μl/head , 5 μl/nostril ) and lower ( 20 μl/head ) respiratory tracts of 7-week-old female BALB/c mice ( six per experimental condition ) . Three days post-infection , nasal wash , and lung wash samples were collected and virus titers were measured by plaque assays . Mice were monitored daily for survival and weight loss until two weeks post-infection . Mice that lost 30% or more of their initial body weights were euthanized . Twenty-one days post-infection , serum samples were collected and anti-HA IgG titers were determined by ELISA . Measurement of virus titers within mice nasal and lung wash samples were done by plaque assay , as described by Tobita et al . [44] . In brief , serial 10-fold dilutions of samples were prepared , and 200 μl aliquots of each dilution were inoculated into MDCK cells in a six-well plate . After 1 hr of incubation for sample absorption , each well was overlaid with 2 ml of agar medium . Plates were incubated for 2 days at 37°C/5% CO2 and stained with crystal violet for plaque counting . The virus titer of each experimental group was represented by the mean ± SD of pfu/ml of samples from six mice in each group . All statistical analyses were performed using the Prism statistical software package ( version 6 . 0; GraphPad Software , Inc . ) . An unpaired Student t-test , the Holm-Sidak t-test , one-way ANOVA followed by Tukey’s multiple comparison test , the Kruskal-Wallis test followed by Dunn’s multiple comparison tests , or two-way ANOVA followed by Dunnett's multiple comparisons tests were used to analyze each data set as indicated in the figure legends . The threshold for statistical significance was set at 5% ( p < 0 . 05 ) . For statistical analyses of HI and NT titers , half of the detection limit value was applied to samples with titers below the detection limit . | SIgAs exist as mainly dimers and tetramers and play critical roles in mucosal immune responses against influenza . Detailed characterization of these anti-viral SIgA is important for better understanding of the mechanisms underlying anti-viral immunity . Here , we describe a means of generating a recombinant tetrameric monoclonal SIgA to enable exhaustive characterization of tetrameric SIgAs . The tetrameric monoclonal SIgA possessing variable regions of anti-influenza viruses broadly neutralizing antibody show that tetramerization of SIgA improves target breadth , but not the peak potency , of their anti-viral functions . These results broaden our knowledge about the fundamental role of SIgA tetramerization in anti-viral humoral response at the human respiratory mucosa . | [
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] | 2019 | IgA tetramerization improves target breadth but not peak potency of functionality of anti-influenza virus broadly neutralizing antibody |
Effector molecules translocated by the Salmonella pathogenicity island ( SPI ) 1-encoded type 3 secretion system ( T3SS ) critically contribute to the pathogenesis of human Salmonella infection . They facilitate internalization by non-phagocytic enterocytes rendering the intestinal epithelium an entry site for infection . Their function in vivo has remained ill-defined due to the lack of a suitable animal model that allows visualization of intraepithelial Salmonella . Here , we took advantage of our novel neonatal mouse model and analyzed various bacterial mutants and reporter strains as well as gene deficient mice . Our results demonstrate the critical but redundant role of SopE2 and SipA for enterocyte invasion , prerequisite for transcriptional stimulation and mucosal translocation in vivo . In contrast , the generation of a replicative intraepithelial endosomal compartment required the cooperative action of SipA and SopE2 or SipA and SopB but was independent of SopA or host MyD88 signaling . Intraepithelial growth had no critical influence on systemic spread . Our results define the role of SPI1-T3SS effector molecules during enterocyte invasion and intraepithelial proliferation in vivo providing novel insight in the early course of Salmonella infection .
Non-typhoidal Salmonella like Salmonella enterica subsp . enterica sv . Typhimurium ( S . Typhimurium ) represent a major causative agent of gastroenteritis in humans worldwide [1 , 2] . Infection usually occurs through the ingestion of contaminated food or drinking water . Salmonella colonizes the distal small intestine , penetrates the intestinal epithelium and induces a strong inflammatory tissue response provoking the main clinical symptoms such as abdominal pain and diarrhea . In the healthy human host , non-typhoidal Salmonella remain restricted to the intestinal tissue . In contrast , spread to systemic organs associated with high mortality is observed in immunosuppressed individuals and newborns . This renders Salmonella one of the most important causative agents of neonatal sepsis and meningitis in parts of Asia and sub-Saharan Africa [3 , 4] Salmonella employs a multitude of virulence factors to overcome the mucosal barrier and evade the cellular and humoral host defence [5] . Effector molecules secreted by the Salmonella pathogenicity island ( SPI ) 1-type 3 secretion system ( T3SS ) act during the early phase of infection and enable Salmonella to penetrate the intact intestinal epithelial barrier and reach the subepithelial tissue [6 , 7] . SPI1-T3SS effector molecules such as SipA , SopA , SopB , and SopE2 intimately interact with host cell processes and manipulate cellular functions such as F-actin dynamics , signal transduction , chemokine secretion , fluid homeostasis , membrane trafficking and tight junction formation [6 , 8–24] . Thereby , they facilitate enterocyte invasion followed by intraepithelial proliferation , histological hallmark of Salmonella pathogenesis [7 , 25–29] . An intact SPI1-T3SS has been strongly associated with mucosal inflammation and diarrhea and thus the clinical symptoms of Salmonella gastrointestinal infection in different models [30–36] . The presence in all Salmonella subspecies and clinical isolates indicates a critical and non-redundant function of SPI1 also during human infection [37 , 38] . The functional relevance of the SPI1-T3SS for tissue infiltration , mucosal inflammation and enhanced fluid secretion in vivo has first been characterized using the bovine ileal loop or oral calf infection model [13 , 32–34 , 39–42] . Infection of calves mimics the disease in humans , characterized by small intestinal mucosal inflammation with chemokine secretion and leukocyte infiltration as well as enhanced fluid secretion [43–45] . Epithelial invasion has also been observed in guinea pig , swine and rabbit intestinal tissue [25–27 , 46 , 47] . In the most widely used animal model of adult mice , however , oral administration of Salmonella does not lead to detectable epithelial invasion and mucosal inflammation but causes a typhoid fever-like systemic infection following a largely SPI1-independent M cell-mediated mucosal translocation [48–50] . Streptomycin administration prior to infection facilitates bacterial expansion and leads to mucosal inflammation [35] . Salmonella-induced tissue pathology , however , is largely restricted to the caecum and colon and SPI1-dependent epithelial invasion is observed at low frequency due to rapid enterocyte exfoliation [28 , 29 , 35 , 51 , 52] . Although enterocyte invasion and intracellular proliferation has been observed in epithelial cells of the caecum of S . Typhimurium infected adult animals and mechanisms of host defence have been investigated [29 , 53] , the role of individual SPI1-T3SS mediated effector molecules during the early steps of Salmonella infection in vivo has remained ill-defined . We have recently introduced a novel oral Salmonella infection model using neonate mice [50] . In this model , Salmonella invades the neonatal small intestinal epithelium , forms intraepithelial microcolonies and spreads to systemic organs in a strongly SPI1-T3SS dependent manner . Here , we used this model and employed wild type Salmonella , sopABE2sipA quadruple mutants complemented with individual effector molecules , the respective triple mutants , sopE2sipA , sopAE2 , and sopBE2 double mutants as well as sipA , sopB , and sopE2 single mutants in combination with wild type and myeloid differentiation primary response gene 88 ( MyD88 ) -/- mice to investigate the contribution of individual SPI1-T3SS effector molecules and host factors during epithelial cell invasion and intraepithelial microcolony formation in vivo .
We initially employed a previously established approach using a sopABE2sipA quadruple mutant S . Typhimurium strain complemented in trans by an expression plasmid encoding the respective SPI1 virulence factors SipA , SopA , SopB or SopE2 [42] . Consistent with our previous results obtained using the SPI1-T3SS defective S . Typhimurium invC mutant , the sopABE2sipA quadruple mutant was unable to invade murine enterocytes , failed to induce a significant transcriptional epithelial response and remained restricted to the gut lumen ( S1A–S1F Fig ) [50] . Complementation with SipA alone significantly enhanced S . Typhimurium viable counts in isolated enterocytes , spleen , liver and mesenteric lymph node ( MLN ) tissue and induced transcriptional epithelial activation ( S1A–S1F Fig ) . Consistently , immunostaining visualized sipA complemented ΔsopABE2sipA Salmonella within intestinal epithelial cells ( S1G Fig ) . Also sopE2 complemented quadruple mutant Salmonella were observed intracellularly ( S1G Fig ) . In contrast , no enterocyte invasion could be observed for sopA or sopB complemented ΔsopABE2sipA Salmonella ( S1G Fig ) . Whereas SopE2 is conserved in all pathogenic strains of Salmonella , some strains additionally harbor a homologue broad-spectrum guanine nucleotide exchange factor , SopE [54–56] . Also SopE enhanced the invasive behavior leading to a significant increase in enterocyte invasion , transcriptional stimulation as well as spread to systemic tissues ( S2A–S2F Fig ) [57] . Importantly , albeit able to invade the epithelium , sipA , sopE2 and sopE complemented ΔsopABE2sipA Salmonella were unable to proliferate and generate intraepithelial microcolonies ( S1G Fig , S2G Fig ) . To overcome the technical obstacles associated with trans-complementation such as plasmid loss , multiple effector gene copies or an impaired access of regulatory elements we next employed triple mutants leaving the fourth SPI1-T3SS effector gene under the native regulatory control . In accordance with our previous results , sopABE2 and sopABsipA mutant Salmonella expressing solely a functional SipA and SopE2 effector , respectively , displayed the ability to invade primary enterocytes and enhance Cxcl2 and Cxcl5 mRNA expression in the intestinal epithelium ( Fig 1A and 1C , S3C Fig ) . Both mutants also penetrated the mucosal barrier reaching liver , MLN , and spleen tissue at numbers comparable to wild type bacteria ( Fig 1B , S3A and S3B Fig ) . In contrast , sopBE2sipA and sopAE2sipA mutant bacteria expressing sopA or sopB alone failed to significantly invade and penetrate the epithelium , stimulate a transcriptional response and spread to systemic organs ( Fig 1A–1C ) . Consistently , immunostaining identified intraepithelial Salmonella in the presence of SipA or SopE2 but not SopA or SopB ( Fig 1D ) . Again , despite the intraepithelial localization , SipA expressing ΔsopABE2 or SopE2 expressing ΔsopABsipA Samonella failed to proliferate intracellularly . Following internalization , Salmonella manipulates maturation of the endosomal compartment . This recruits the lysosomal-associated membrane protein ( LAMP ) 1 from Golgi-derived vesicles [58] and provides the environmental signals that coordinate the expression of SPI2-T3SS effector genes and the development of a replicative compartment [59 , 60] . LAMP1 recruitment to intraepithelial bacteria was observed following infection with wild type but not ΔsopABE2 or ΔsopABsipA Salmonella ( Fig 1E and 1F ) . Additionally , we used a previously described SPI2 reporter construct expressing gfp under the control of the ssaG promoter to analyze the induction of SPI2-encoded genes [52] . SPI2 reporter activity was detected in intraepithelial wild type but not SipA expressing ΔsopABE2 or SopE2 expressing ΔsopABsipA Salmonella ( Fig 1G and 1H ) . Together , these results identifed the critical but redundant role of SopE2 and SipA for enterocyte invasion in vivo and highlighted the requirement of enterocyte invasion for transcriptional stimulation . Notably , invasion per se appeared not to be sufficient to generate an appropriate intracellular niche allowing intraepithelial bacterial proliferation . On the other hand , the formation of intraepithelial microcolonies did not significantly promote systemic spread . The ability and degree of individual SPI1-T3SS effector molecules to confer an enterocyte-invasive phenotype differed markedly between the situation in vivo and a classical in vitro cell culture-based invasion assay ( S1H Fig , S2H Fig , S3D Fig ) illustrating the need for a detailed investigation of the bacteria-epithelial cell interaction in vivo [61] . Host innate immune recognition through Toll-like receptor ( TLR ) 2 , 4 and 9 and signaling through the common adapter molecule MyD88 has previously been shown to provide the stimulatory signal for SPI2 effector gene expression and represent a prerequisite for the expression of SPI2-encoded effector genes , intracellular growth and microcolony formation in myeloid cells [60] . Interestingly , innate immune stimulation in Salmonella-infected neonate mice was also induced by TLR stimulation and mediated by the common adapter molecule MyD88 [50] . We therefore tested the requirement of intact MyD88-dependent signaling for intraepithelial Salmonella proliferation in vivo . As expected , MyD88-deficient mice exhibited significantly reduced epithelial Cxcl2 and Cxcl5 mRNA expression ( S4A and S4B Fig ) . However , in contrast to the situation in myeloid cells , Salmonella maintained its ability to generate intraepithelial microcolonies with similar numbers of microcolonies per villus also in the absence of MyD88 signaling as illustrated by immunostaining and transmission electron microscopy ( Fig 2A–2C ) . Also , LAMP1 was recruited to the majority of Salmonella-containing vacuole ( SCV ) in enterocytes and the SPI2 reporter was induced in the absence of MyD88-dependent signal transduction ( Fig 2D–2G ) . The disease course was significantly accelerated rather than delayed , most probably as a result of an impaired MyD88-mediated antimicrobial host defence ( S4C Fig ) . Thus , intraepithelial Salmonella proliferation and microcolony formation occurred independently of MyD88-mediated host innate immune signaling in vivo . Although SipA or SopE2 were sufficient to facilitate enterocyte invasion , Salmonella failed to induce intraepithelial microcolony formation . This suggested that intracellular proliferation required the contribution of SPI1-T3SS effector proteins beyond their invasion-promoting function . We first investigated the requirement of SipA and/or SopE2 for intraepithelial proliferation . As expected , ΔsopE2sipA Salmonella exhibited severely impaired enterocyte invasion , transcriptional stimulation and organ spread ( Fig 3A–3C , S5A–S5C Fig ) . In contrast , sipA or sopE2 mutant bacteria displayed only a minor phenotype with intact enterocyte invasion , transcriptional stimulation and spread to systemic organs ( Fig 3D–3F , S5D–S5F Fig ) . Strikingly , however , sopE2 mutant bacteria similar to wild type Salmonella generated LAMP1-positive intraepithelial microcolonies , whereas ΔsipA Salmonella failed to do so ( Fig 3G , 3H and 3I ) . In contrast , both ΔsopE2 and ΔsipA Salmonella exhibited detectable intraepithelial SPI2 reporter activity ( Fig 3J and 3K ) . Consistent with intracellular proliferation of ΔsopE2 Salmonella , the presence of SipA as compared to SopE2 resulted in significantly higher intraepithelial viable counts ( Fig 3D ) . The enhanced number of intraepithelial bacteria was in turn associated with increased Cxcl2 mRNA expression as well as augmented spread to spleen , MLN and liver tissue ( Fig 3E and 3F , S5D and S5E Fig ) . We next defined the role of SopA and/or SopB during microcolony formation , analyzing the phenotype of sopAE2 and sopBE2 double mutant Salmonella in vivo . Both SipA expressing sopAE2 and sopBE2 mutants gained access to the intracellular compartment of epithelial cells , spread to systemic anatomical sites and stimulated a potent transcriptional response ( Fig 4A–4C , S6A–S6C Fig ) . Interestingly , sopBE2 mutant Salmonella failed to generate microcolonies , whereas the majority of sopAE2 mutant-infected epithelial cells exhibited intraepithelial growth ( Fig 4D and 4E ) . Consistently , significantly lower intraepithelial bacterial numbers were found for ΔsopBE2 but not ΔsopAE2 Salmonella as compared to wild type bacteria ( Fig 4A ) . Also , sopAE2 mutant but not sopBE2 mutant Salmonella recruited LAMP1 ( Fig 4F and 4G ) and upregulated SPI2 gene expression ( Fig 4H and 4I ) . These results highlighted the role of SipA and SopB for intraepithelial proliferation and excluded SopA as critical SPI1 component for intraepithelial microcolony formation . To further evaluate SopB as a potential essential effector for intraepithelial proliferation , we next tested single sopB mutant Salmonella in vivo . Unexpectedly , sopB mutant Salmonella induced a more severe clinical phenotype with accelerated disease progression . Due to the accelerated disease course induced by ΔsopB Salmonella , the following analyses were performed at day 2 and 3 postinfection ( p . i . ) ( Fig 5 , S7 Fig ) . Enterocyte invasion of both wild type and ΔsopB Salmonella already occurred at this early time point , but spread to spleen and liver tissue remained low ( Fig 5A and 5C , S7A Fig ) . Infection with ΔsopB Salmonella was accompanied by significantly enhanced Cxcl2 and Cxcl5 mRNA expression that was not observed during infection with wild type Salmonella ( Fig 5D , S7B Fig ) . This increase in epithelial immunostimulation was associated with a significantly accelerated bacterial spread to the MLN ( Fig 5B ) and enhanced numbers of caspase 3- and caspase 8-positive enterocytes ( Fig 5E and 5F , S7C Fig ) . Since a similar phenotype was not observed after infection with sopBE2 mutant Salmonella ( Fig 4 ) , these results suggested that SopB by a hitherto unidentified mechanism counteracts the proapoptotic activity induced by SopE2 [62 , 63] . Strikingly , immunostaining revealed that Salmonella deficient solely for sopB were still able to proliferate intraepithelially demonstrating that SopB is not essential for intraepithelial microcolony formation ( Fig 5G ) . Consistently , ΔsopB Salmonella generated LAMP1-positive intraepithelial endosomal compartments ( Fig 5H and 5I ) and showed induction of SPI2 reporter gene activity ( Fig 5J and 5K ) . The fact that both sopE2 and sopB single mutant Salmonella were able to grow intraepithelially ( Figs 3G and 5G ) , whereas sopBE2 double mutant Salmonella failed to form intraepithelial microcolonies ( Fig 4D and 4E ) suggests that SopE2 and SopB exert a critical but redundant role during intraepithelial proliferation and microcolony formation . Neonate mice infected with the SipA-expressing sopABE2 triple mutant Salmonella exhibited a more severe disease phenotype . Whereas mice infected with wild type Salmonella showed low but still significant weight gain during the first days after infection , mice infected with sopABE2 mutant Salmonella failed to increase their body weight and exhibited an aggravated course of the disease ( S8A and S8B Fig ) . We therefore infected 4-day-old mice in some experiments to facilitate the analysis . The accelerated disease course of ΔsopABE2 Salmonella was associated with an increased tissue inflammation and epithelial barrier impairment illustrated by an enhanced translocation of labelled 4 kDa dextran at day 3 p . i . and a reduced length of the small intestine ( Fig 6A , S8C and S8D Fig ) . Flow cytometric analysis of lamina propria immune cells confirmed a significantly stronger recruitment of monocytes and polymorphonuclear cells ( PMN ) 3 days after infection with ΔsopABE2 Salmonella as compared to wild type Salmonella ( Fig 6B and 6C , S8E and S8F Fig ) . Immunohistological detection of infiltrating PMNs corroborated the role of SipA in tissue inflammation . Salmonella infection enhanced the number of lamina propria PMNs and this effect was significantly reduced after infection with ΔsipA S . Typhimurium ( S8G and S8H Fig ) . Notably , genetic complementation with wild type sipA ( ΔsipA psipA ) as well as a form of SipA with a point mutation at position 434 ( ΔsipA psipAD434A ) previously described to harbor reduced inflammatory activity reversed this phenotype ( S8G and S8H Fig ) . These results demonstrate an intrinsic proinflammatory activity of SipA . They are consistent with previous studies showing that SipA inhibits the phospholipid glutathione peroxidase ( GPX4 ) and leads to enhanced secretion of the proinflammatory chemotactic eicosanoid hepoxillin A3 ( HXA3 ) [64 , 65] . However , our results fail to confirm a significant importance of the caspase 3 cleavage site in SipA for this activity [12 , 66] . The proinflammatory activity of SipA was reported to occur independently of enterocyte invasion , following secretion and binding of SipA to the epithelial surface molecule p53-effector related to PMP-22 ( PERP ) [12 , 65 , 67 , 68] . Consistently , the aggravated disease phenotype was also observed after infection with Salmonella that lack SopA , SopB and SopE2 and carry two point mutations in SipA ( SipAK635A E637W ) previously shown to impair the actin-modulating activity and reduce the invasion-promoting effect of SipA ( S8B Fig ) . The reduced invasion-promoting activity of SipAK635A E637W as compared to wild type SipA was confirmed by quantification of the number of intraepithelial bacteria 2 days after infection with ΔsipA S . Typhimurium complemented with either psipA or psipAK635A E637W ( S8I Fig ) . The invasion-independent activity of SipA suggested that it might act in trans and stimulate the epithelium at anatomical locations distant to the site of enterocyte invasion . To test whether the SipA-mediated immune stimulation contributes to the intraepithelial growth and microcolony formation , we next infected mice with a 1:1 mixture of SipA-sufficient wild type Salmonella and SipA-deficient ΔsopABsipA Salmonella . As shown in previous experiments ( Fig 1A and 1D ) , ΔsopABsipA Salmonella were able to invade epithelial cells through the activity of SopE2 but failed to proliferate intraepithelially . Following double infection , wild type Salmonella readily formed microcolonies in intestinal epithelial cells ( Fig 6D , double stained appearing in yellow ) . In contrast , ΔsopABsipA Salmonella invaded but failed to proliferate intracellularly ( Fig 6D , in red ) . Thus , the induction of a proinflammatory signal by SipA-expressing wild type Salmonella was not sufficient to induce a replicative endosomal environment in distant enterocytes and rescue the intraepithelial proliferation defect of SipA-deficient ΔsopABsipA Salmonella . Next , we investigated the intrinsic activity of SipA in vivo . We therefore analyzed ΔsipA Salmonella complemented in trans with the gene for ( i ) wild type SipA ( ΔsipA psipA ) ( ii ) SipA with two point mutations at position 635 and 637 previously shown to impair its actin stabilization and reduce the invasion-promoting activity ( ΔsipA psipAK635A E637W ) [67] ( S8I Fig ) , ( iii ) SipA that lacks the caspase 3 cleavage site reported to be critical for the proinflammatory activity [66] ( ΔsipA psipAD434A ) and ( iv ) SipA that lacks both , the actin-stabilizing and proinflammatory activity ( ΔsipA psipAD434A K635A E637W ) . Expression of these constructs was tested in the presence of SopE2 to ensure enterocyte invasion and allow the comparative analysis of the different SipA variants in respect to intraepithelial growth and microcolony formation . As expected , ΔsipA , ΔsipA psipAK635A E637W , ΔsipA psipAD434A and ΔsipA psipAD434A K635A E637W Salmonella were able to invade the epithelium ( Fig 6E ) , cause systemic infection ( Fig 6F , S9A and S9B Fig ) and induce transcriptional stimulation ( Fig 6G , S9C Fig ) . As observed before , ΔsipA Salmonella exhibited significantly reduced intraepithelial bacterial numbers and Cxcl2 mRNA expression , and failed to proliferate and form intraepithelial microcolonies ( Fig 6E , 6G and 6H ) . Infection with ΔsipA Salmonella was also associated with a moderately reduced mortality ( S9D Fig ) . In contrast , ΔsipA Salmonella complemented with psipAK635A E637W , psipAD434A , psipAD434A K635A E637W behaved indistinguishably from wild type Salmonella and readily formed LAMP1-positive intraepithelial microcolonies ( Fig 6I and 6J ) . Together , these results demonstrate the critical importance of SipA . However , in the presence of SopE2 , neither the actin-stabilizing activity nor the reported caspase 3-dependent proinflammatory activity were required for intraepithelial proliferation and microcolony formation .
Salmonella expressing SopE , SopE2 or SipA but not ΔsopE2sipA Salmonella were able to invade the epithelium indicating that the production of SopE , SopE2 or SipA is necessary and sufficient to facilitate enterocyte invasion in vivo . SopE or SopE2 activate the Rho GTPases Rac-1 and Cdc42 or only Cdc42 , respectively , leading to actin assembly , membrane ruffling and bacterial internalization [22–24 , 54 , 56] . SipA with its C-terminal domain stabilizes actin filaments , promoting bacterial invasion in the absence of prominent membrane ruffling [9–12 , 42 , 69] . Their potent activity was illustrated by the finding that the presence of only one of the two effector molecules facilitated enterocyte invasion at levels indistinguishable from wild type bacteria . Notably , also the ubiquitin E3 ligase SopA was previously shown to contribute to invasion of polarized epithelial cells in vitro [15 , 16 , 42] . Also SopB was shown to promote membrane fission and bacterial invasion [18 , 19 , 70 , 71] . It was suggested that SopB supports SopE-mediated actin filament polymerization by recruiting ARNO ( Cytohesin2 ) to the site of invasion [72] . Our in vivo results do not support a significant role for SopA or SopB in enterocyte entry . However , although unlikely , we cannot exclude that enterocyte invasion by strains expressing effectors other than sipA or sopE2 occurred but remained undetected due to rapid enterocyte apoptosis or exfoliation as observed in adult mice [29] . Consistent with previous in vitro results , enterocyte invasion was not sufficient to allow proliferation and microcolony formation despite the presence of a fully functional SPI2 locus [73] . ΔsopB , ΔsopE2 and ΔsopAE2 but not ΔsipA Salmonella were able to generate intraepithelial microcolonies assigning SipA a critical non-redundant role for intracellular growth . ΔsipA Salmonella failed to recruit LAMP1 to the endosomal epithelial compartment , confirming a recent report on the contribution of the NH2-terminal domain of SipA ( aa1-458 ) to endosomal maturation and intracellular replication [74] . SipA was recently also shown to promote intracellular proliferation via interaction with the actin nucleator family member Spire2 [69] . In our study , the SipA activity required for intraepithelial microcolony formation was independent of its actin stabilizing function or proinflammatory activity reported to depend on caspase 3 processing [66 , 67] . This might be explained by the recently described cooperative action of SipA with the SPI2 effector SifA to promote phagosome maturation and the generation of a replicative intraepithelial compartment [74] . Interestingly , intraepithelial ΔsipA Salmonella exhibited expression of the SPI2 reporter indicating that SPI2 effector expression can occur independently of SipA . Whereas both ΔsopE2 and ΔsopB Salmonella readily proliferated in enterocytes , sopBE2 mutant Salmonella were unable to form intraepithelial microcolonies . Consistently , ΔsopBE2 and ΔsopABE2 ( in contrast to ΔsopE2 or ΔsopB ) Salmonella failed to recruit LAMP1 to the endosomal compartment and to turn on SPI2 gene expression . Thus , SopB and SopE2 contributed in a redundant fashion to the generation of a replicative endosomal compartment in enterocytes . Both , SopE2 and SopB activate Rho GTPases and mitogen activated protein kinases ( MAPK ) , which might contribute to endosomal modification [22–24 , 72] . Alternatively , SopB was described to directly or indirectly lead to the accumulation of phosphatidylinositol 3-phosphate on the outer leaflet of the SCV , altering the recruitment of host cell endocytic trafficking molecules and thereby preventing SCV-lysosomal fusion [17 , 18 , 75 , 76] . Although SopE2 was shown to influence endosomal maturation and intracellular proliferation , it is currently unknown how it could compensate for the lack of SopB [77] . Enterocyte invasion was consistently associated with a transcriptional stimulation of the intestinal epithelium . In contrast , non-invasive ΔsopABE2sipA Salmonella failed to evoke a significant epithelial response despite the presence of high numbers of bacteria in the intestinal lumen . Also , the presence of a functional T3SS system in the absence of invasion in sopAE2sipA , sopBE2sipA or sopE2sipA mutant bacteria was unable to induce a significant epithelial transcriptional response . Whereas invasion led to a more than 100-fold increase in Cxcl2 and Cxcl5 mRNA expression , intraepithelial proliferation only moderately contributed to this response . Our results therefore suggest that the presence of intraepithelial Salmonella per se or , alternatively , downstream events such as stimulation of lamina propria immune cells as a consequence of penetration of the epithelial barrier drive epithelial transcriptional stimulation [67] . This is consistent with the previously reported requirement of a functional SPI1 system to evoke PMN transmigration and fluid secretion in calves and the bovine ligated loop model [32–34] . It is also in accordance with the presence of a functional SPI1 locus among all isolates from symptomatic human patients [37 , 38] . In addition to the stimulation of pattern recognition receptors the activation of host cell signaling pathways by Salmonella virulence factors has been described . For example , SopA was reported to contribute to tissue inflammation by targeting two host E3 ubiquitin ligases , TRIM56 and TRIM65 [13 , 15 , 78] . Also SopB was shown to indirectly stimulate Rho family GTPases and nuclear responses [56] . However , no significant influence of SopA or SopB on chemokine expression was observed in our study . Instead , our results suggest that SopA together with SopB and/or SopE2 may contribute to balance the adverse effects of the inflammatory activity of SipA . Additionally , T3SS-mediated translocation of SipA and SopE2 was reported to directly induce host cell activation [23 , 79] . SopE-mediated activation of the Rho family of small molecular weight GTPase Cdc42 and activation of p21-activated kinase was reported to induce mitogen-activated protein ( MAP ) kinase and NF-κB stimulation [23 , 80 , 81] . However , invasive ΔsopABsipA and ΔsopABE2 Salmonella ( in the absence of SipA and SopE2 , respectively ) still provoked potent transcriptional enterocyte stimulation in vivo . SipA ( SipA294-424 ) was additionally shown to induce PMN transmigration and tissue inflammation via PKCα-dependent secretion of the chemotactic eicosanoid hepoxillin A3 ( HXA3 ) [12 , 65 , 82] . Notably , this pro-inflammatory activity was demonstrated to be independent of actin filament stabilization and enterocyte invasion and thus differed from the invasion-mediated immune stimulation discussed above [52 , 65 , 67 , 82] . Binding of SipA to the epithelial surface molecule p53-effector related to PMP-22 ( PERP ) was shown to inhibit the phospholipid glutathione peroxidase ( GPX4 ) [12 , 65 , 67 , 68] . This effect was also observed in vivo with major influence on epithelial barrier integrity , immune cell infiltration and the outcome of the disease . Consistent with previous reports , immune stimulation was still observed in sipAK635A E637W ΔsopABE2 Salmonella despite a reduced invasiveness , supporting the idea that SipA acts extracellularly to stimulate the mucosal immune system [65 , 68] . However , no influence of this SipA-mediated immune stimulation was observed on intraepithelial proliferation . The fact that ΔsopABE2 Salmonella exhibited a more severe proinflammatory effect as compared to SipA-competent wild type bacteria suggests that SopA , SopB or SopE2 might counteract this SipA effect in vivo . Enhanced epithelial apoptosis and increased mortality were noted in the absence of SopB , consistent with a recent report that demonstrated protection from Nlrc4/ASC-mediated apoptosis by SopB in vitro [20 , 83] . SopB might additionally prevent apoptosis by other mechanisms [21 , 84] . Epithelial barrier damage after infection with ΔsopB Salmonella explains the higher bacterial load in the mesenteric lymph node . Intriguingly , enhanced disease progression following infection with ΔsopB Salmonella was absent using ΔsipAsopBE2 and ΔsopBE2 Salmonella . This suggests that the apoptosis-promoting effect is SopE2-mediated . Indeed , SopE2 has long been described to activate the c-jun NH2-terminal kinase ( JNK ) [23 , 80] and JNK signaling is known to drive ROS-induced caspase 3-dependent apoptosis [85] . Alternatively , SopE2 was recently shown to activate caspase 1 [63] . Thus , our results identify a previously undescribed role for SopB: to protect from SopE2-mediated epithelial cell damage . Despite the lack of intraepithelial microcolonies , ΔsopABsipA , ΔsopABE2 , ΔsopBE2 or ΔsipA Salmonella efficiently penetrated the epithelial barrier and spread to systemic organs , reaching levels in spleen and liver tissue comparable to wild type Salmonella . This suggests that intraepithelial replication , although considered a hallmark of Salmonella pathogenesis , does not represent a prerequisite for efficient penetration of the epithelial barrier . This is consistent with the observation by Müller et al . , who described SPI1-T3SS dependent penetration of the colon epithelium in the absence of detectable intraepithelial growth [28] . We even cannot exclude that two different bacterial populations simultaneously drive mucosal translocation and systemic spread . These results indicate that the functional relevance of intraepithelial replication and SCV formation has not been fully established and warrants further investigation . Together , we validate the new neonatal infection model and present the first detailed in vivo analysis of the host and bacterial factors required for enterocyte invasion and intraepithelial microcolony formation , hallmark of Salmonella pathogenesis ( Fig 7 , S3 Table ) . We define the redundant and cooperative function of the SPI1-T3SS effectors SopA , SopB , SopE2 and SipA for invasion of the intestinal epithelium and intraepithelial growth and characterize their influence on innate immune stimulation , mucosal translocation and spread to systemic organs . Our results thereby significantly extend our insight in the early steps of the microbial-host interplay in vivo and might reveal new targets for future preventive and therapeutic measures .
All bacterial mutants and plasmids used in this study are listed in the S1 Table . Salmonella enterica subsp . enterica serovar Typhimurium ATCC14028 were used as wild type bacteria . The sopABE2sipA quadruple mutant S . Typhimurium carrying the low copy number pWSK29 vector encoding sopA , sopB , sipA , SopE or sopE2 , or the empty pWSK29 vector as control , as well as the respective isogenic S . Typhimurium triple , double or single mutants were used to analyze individual SPI1-T3SS effector molecules . Deletions of genes encoding effector proteins were generated by Red-mediated recombination basically as described before [86] . Strains with multiple deletions of effector genes were generated by P22-mediated transduction of mutant alleles containing the aph or CAT cassette . If required to generate multiple mutations by Red-mediated mutagenesis , antibiotic resistance genes were removed by FLP-mediated recombination between FRT sites . For the generation of a strain with point mutations in chromosomal sipA a two-step scarless mutagenesis approach according to Hoffmann et al . was applied [86] . A targeting cassette from pWRG717 was amplified using sipA633 In717 For and sipA939 In717 Rev ( S2 Table ) . Salmonella WT harboring pWRG730 was induced for expression of redαβγ and transformed to kanamycin resistance . The resulting sipA mutant allele was transferred to other mutant strains using P22 transduction . The mutant allele sipA K635A E637W was amplified by PCR from plasmid p4758 target strains and the resulted DNA was used to transform MvP2511 haboring pWRG730 . Resistance to I-SceI-mediated double strand breaks was used for selection of homologous recombination basically as described by Hoffmann et al . [86] . The point mutations in resulting strain MvP2520 were confirmed by DNA sequencing . Finally , the sopE2::aph mutation was introduced by P22 transduction to yield MvP2521 . For complementation of sipA , sopA , sopB , sopE or sopE2 deletions , the corresponding genes were amplified from S . enterica sv . Typhimurium genomic DNA introducing 3’ HA tag sequences for detection of the encoded proteins by immunoblotting . Oligonucleotides for amplification are listed in S2 Table . PCR products were cloned in low copy number vector pWSK29 and E . coli DH5α was used to propagate plasmids p4041 , p4042 , p4043 and p4044 , SopA::HA , SopB::HA , SopE::HA , and SopE2::HA , respectively . Since sipA is the terminal gene of the sicAsipBCDA operon , the PsicA promoter was amplified and cloned upstream of sipA::HA to generate p4040 . Mutant strains were transformed with complementation plasmids listed in S1 Table . Synthesis and translocation of the effector proteins by S . Typhimurium was confirmed by immunolabelling of the HA tag . Furthermore , the plasmids gradually complemented the invasion defect of a multi-effector mutant strain . The function of SipA was additionally analyzed using ΔsipA Salmonella carrying the sipA gene with point mutations at specific functional positions . Vector p4758 carrying two point mutations in the sipA gene at the actin binding site ( amino acid position 635 and 637 ) , vector p4890 carrying a point mutation in the sipA gene at the caspase 3 motif ( amino acid position 434 ) , and vector p4892 carrying all three point mutations in the sipA gene were generated by site-directed mutagenesis . Site-directed mutagenesis was performed using the Q5 SDM kit according to the manufacturers’ protocol ( NEB ) . Multiple rounds of mutagenesis were performed if required for the generation of double or triple mutations using primers listed in the S2 Table . The plasmid with constitutive green fluorescent protein ( GFP ) expression ( pGFP , AmpR ) was kindly provided by Brendan Cormack , Stanford , USA . The reporter construct pM973 expressing gfp under the control of the SPI2 promoter pssaG ( AmpR ) kindly provided by Wolf D . Hardt , ETH Zürich , Switzerland was used to analyze the expression of SPI2 effector molecules by intraepithelial Salmonella . Intestinal epithelial m-ICcl2 cells were cultured as previously described [87] . Bacteria were cultured in Luria Bertani ( LB ) broth at 37°C in the presence of 100 μg/mL ampicillin , 50 μg/mL kanamycin , or 100 μg/mL carbenicillin . Overnight cultures were diluted 1:10 and incubated at 37°C for approximately 80 min until reaching the logarithmic phase ( OD600 approximately 0 . 5 ) . Bacteria were then washed three times in PBS and the OD600 was adjusted to 0 . 55–0 . 60 corresponding to approximately 2 . 0×108 CFU bacteria per mL . The bacterial suspension was subsequently diluted to obtain the appropriate infection dose . Bacteria were added to the m-ICcl2 cells ( 2×105 cells per well ) at a multiplicity of infection ( MOI ) of 1:10 . The cell culture plate was centrifuged at 300xg for 5 min and incubated at 37°C for 1 h . Cells were washed three times with PBS and cell culture medium supplemented with 100 μg/mL gentamicin ( Sigma ) was added . After incubation at 37°C for 1 h , cells were washed again three times in PBS and lyzed for 2 min at room temperature in 500 μL 0 . 1% Triton X-100 ( Roth ) in aqua dest . Viable bacteria were quantified by serial dilution and plating . All animal experiments were performed in compliance with the German animal protection law ( TierSchG ) and approved by the local animal welfare committee ( Niedersachsische Landesamt für Verbraucherschutz und Lebensmittelsicherheit Oldenburg , Germany; Landesamt für Natur , Umwelt und Verbraucherschutz , North Rhine Westfalia ) under the code 8402 . 04 . 2015A073 , 84–02 . 042015 . A067 , 84–02 . 042015 . A065 and 81–02 . 04 . 2017 . A397 including all approved changes . Adult C57BL/6J wild type and B6 . 129P2 ( SJL ) -MyD88tm1 . 1Defr/J ( MyD88-/- , stock no . 009088 ) were obtained from the Jackson Laboratory ( Bar Harbour , USA ) and bred locally under SPF conditions . Bacteria were cultured as described above . 1- and 4-day-old animals were orally infected with 100 CFU of wild type S . Typhimurium or the indicated isogenic mutants in a volume of 1 μL PBS . At various time points post infection ( p . i . ) , liver , mesenteric lymph mode ( MLN ) and spleen were collected and homogenized in sterile PBS . Viable counts were obtained by serial dilution and plating on LB agar plates supplemented with the appropriate antibiotics . Alternatively , small intestinal tissues were collected at the indicated time point p . i . and prepared for immunostaining or electron microscopy . For co-infection , 100 CFU of Salmonella wild type carrying pGFP and sopABsipA mutant Salmonella were administered orally to 1-day-old mice at a ratio of 1:1 in 2 μl . Primary small intestinal epithelial cells ( IEC ) from neonate mice were isolated as previously described [87] . Briefly , the small intestinal tissue was cut in small pieces and incubated in 30 mM EDTA/PBS at 37°C for 10 min . IEC were detached from the underlying tissue by shaking . Cells were then filtered through a 100 μm nylon cell strainer ( BD Falcon ) and harvested by centrifugation at 300xg for 10 min . The cell pellet was resuspended in 10% FCS/PBS and harvested by centrifugation at 300xg for 10 min . To obtain the intraepithelial bacterial count , IEC were treated with 100 μg/mL gentamicin for 1 h at room temperature as previously described and subsequently lyzed and plated in serial dilutions on selective LB agar plates [50] . Total RNA was extracted from isolated IEC using TRIzol ( Invitrogen ) and the RNA concentration was determined on a NanoDrop 1000 spectrophotometer ( Thermo Scientific ) . First-strand complementary DNA ( cDNA ) was synthesized from 5 μg total RNA using Oligo-dT primers , RevertAid reverse transcriptase and RiboLock RNase inhibitor ( ThermoFisher Scientific ) . RT-PCR was performed using the Taqman technology with an absolute QPCR ROX mix ( Thermo Scientific ) , sample cDNA and the Taqman probes Hprt ( Mm00446968-m1 ) , Cxcl2 ( Mm00436450_m1 ) and Cxcl5 ( Mm00436451_g1 ) ( Life Technologies ) . Results were calculated by the Δ2-CT method . For data analysis , values were normalized to the hprt housekeeping gene and were presented as fold induction over age-matched controls . Infected mice were orally administered 2 μL of a 0 . 6 mg/μL 4kDa FITC dextran solution ( TdB Consultancy ) at the indicated time point p . i . . After four hours , serum was collected and the serum concentration of FITC dextran was measured by fluorometry using a SpectraMax i3 at an excitation of 492nm ( 9 nm bandwidth ) and an emission of 518nm ( 15 nm bandwidth ) using a serially diluted FITC dextran solution as standard . 4 μm paraformaldehyde-fixed paraffin-embedded tissue sections were deparaffinized in xylene and rehydrated followed by antigen retrieval in 10 mM sodium citrate and a blocking step with 10% normal donkey serum/5% BSA/PBS . Chicken anti-GFP ( Abcam ) , rabbit anti-Salmonella O4 antigen ( Abcam ) , rat anti-LAMP1 ( Developmental Studies Hybridoma Bank ) , rabbit anti-cleaved caspase-3 ( Cell Signaling ) , rabbit anti-cleaved caspase-8 ( Cell Signaling ) , rat anti-PMN ( Ly6-6B2 , SeroTec ) and mouse anti-E-cadherin ( BD Transduction Laboratories ) antibodies as well as the indicated fluorophore-conjugated secondary antibodies ( Jackson ImmunoResearch ) were used . Fluorescein-conjugated ( Vector ) or AF647-conjugated ( Invitrogen ) Wheat Germ Agglutinin ( WGA ) was used to detect the mucus layer . Slides were subsequently mounted in DAPI mounting medium ( Vector ) and images were taken using a Zeiss ApoTome . 2 system microscope connected to a Axiocam 506 digital camera . Images were formatted using the ZEN 2 . 3 imaging software . For immune cell isolation , the intestine was cut longitudinally and incubated 2x15min in 2mM EDTA/HBSS at 37°C to remove the epithelium . The lamina propria was digested in 30μg/ml Liberase/DNAse ( Roche ) for 45min at 37°C and filtered through a 100μm nylon cell strainer to obtain a single cell suspension . The following antibodies from Biolegend were used for the FACS analysis: CD45-BV510 ( 30-F11 ) , Ly6C-PerCPCy5 . 5 ( HK1 . 4 ) , Ly6G-PE ( 1A8 ) , CD11b-APCCy7 ( M1/70 ) , MHCII-AF488 ( M5/115 . 14 . 2 ) . Data were acquired with a BD FACS Canto II and analyzed with FlowJo X . 1-day-old MyD88+/+ and MyD88-/- mice were infected with wild type S . Typhimurium and sacrificed at day 4 p . i . . Tissue samples were prepared for ultrastructural analysis as previously described [88] . After embedding , samples were post-fixed with 1% osmium tetroxide and contrasted with 2% uranyl acetate , both for 2 h . Samples were dehydrated with a graded ethanol series , followed by infiltration with epoxy resin and overnight heat polymerization . Thin , 70 nm sections were prepared using an ultramicrotome Ultracut UCT ( Leica Microsystems ) and contrasted with 0 . 2% lead citrate . Sections were analyzed with a JEM-1400 TEM microscope ( Jeol ) and images were recorded with TemCam-F216 camera using EM MENU software ( both Tvips ) . The One-way ANOVA Kruskal-Wallis test ( with Dunn's posttest ) and the Mann-Whitney test were employed for statistical analysis of bacterial counts in organ tissue and the comparative transcriptional analysis . Mortality was analyzed by log-rank ( Mantel-Cox ) test . The GraphPad Prism Software 5 . 0 was used for statistical evaluation . p values are indicated as follows: ***p<0 . 001; **p<0 . 01 , and *p<0 . 05 . | Non-typhoidal Salmonella represent a major causative agent of gastroenteritis worldwide . Hallmark of the pathogenesis is their ability to actively invade the intestinal epithelium by virtue of their type 3 secretion system that delivers bacterial virulence factors directly into the host cell cytosol . The role of these virulence factors during enterocyte entry and intraepithelial growth has only been investigated in vitro since the previously established in vivo models in small animals did not allow visualization of intraepithelial Salmonella . However , immortalized cell lines lack the overlaying mucus layer , final cell lineage differentiation , apical-basolateral polarization as well as continuous migration along the crypt villus axis and thus the role of virulence factors during the Salmonella infection in vivo has remained largely undefined . Here , we took advantage of our novel neonatal mouse infection model and for the first time systematically analyzed the importance of Salmonella virulence factors for enterocyte invasion and intraepithelial growth . | [
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] | 2018 | Minimal SPI1-T3SS effector requirement for Salmonella enterocyte invasion and intracellular proliferation in vivo |
CD8 T cells are recognized key players in control of persistent virus infections , but increasing evidence suggests that assistance from other immune mediators is also needed . Here , we investigated whether specific antibody responses contribute to control of lymphocytic choriomeningitis virus ( LCMV ) , a prototypic mouse model of systemic persistent infection . Mice expressing transgenic B cell receptors of LCMV-unrelated specificity , and mice unable to produce soluble immunoglobulin M ( IgM ) exhibited protracted viremia or failed to resolve LCMV . Virus control depended on immunoglobulin class switch , but neither on complement cascades nor on Fc receptor γ chain or Fc γ receptor IIB . Cessation of viremia concurred with the emergence of viral envelope-specific antibodies , rather than with neutralizing serum activity , and even early nonneutralizing IgM impeded viral persistence . This important role for virus-specific antibodies may be similarly underappreciated in other primarily T cell–controlled infections such as HIV and hepatitis C virus , and we suggest this contribution of antibodies be given consideration in future strategies for vaccination and immunotherapy .
Infections associated with persistent viremia include human immunodeficiency virus ( HIV ) and the hepatitis B and C viruses ( HBV , HCV ) , which affect more than 500 million people worldwide . However , available options to prevent and treat particularly HIV and HCV are unsatisfactory . To refine existing strategies aimed at combating these devastating epidemics , and to help direct future efforts , a better understanding of the immune effector pathways preventing viral persistence is of particular importance . For almost a century , lymphocytic choriomeningitis virus ( LCMV ) infection of mice has served as a primary model to study basic mechanisms of the virus–host relationship in persistent infection [1] . It has led to the discovery of several essential concepts [2] , including MHC restriction of T cells , viral mutational escape from CD8 cytotoxic T cells ( CTL ) , CTL dysfunction in persistent infection and MHC linkage of virus control . LCMV neutralizing antibody ( nAb ) responses typically appear late and remain relatively weak [1] . Accordingly , the key role of CTL in controlling and resolving systemic persistent infections has initially been described for LCMV [3–5] with subsequent extension of the concept to important human pathogens such as HIV and HCV . Declining viremia in HIV coincides with the appearance of antiviral CD8 T cells [6 , 7] , and the concept of CTL-mediated HIV control was further strengthened by the association of “protective” HLA molecules with long-term nonprogression in many so-called “elite controllers” [8] . In addition , experimental depletion of CD8 T cells in simian immunodeficiency virus ( SIV ) -infected macaques also underlined the importance of CTLs in the control of acute , as well as long-term infection [9–11] . Analogous observations were made in HBV- and HCV-infected monkeys [12 , 13] . Apart from the virtually undisputed contribution of CTLs , evidence has accumulated to suggest that other mechanisms of immune defense are also needed to contain or resolve systemic persistent virus infection . For instance , “protective” HLA alleles are also found in up to one third of individuals with poor or undetectable immune control of HIV infection [14 , 15] , suggesting that even potent CD8 T cell responses are insufficient for HIV control . Conversely , many “elite controllers” lack any of the known “protective” alleles [15] . Moreover , the recent failure of the CD8 T cell–based Merck “STEP” vaccine trial in human HIV infection has alerted the community and has sparked renewed interest in complementary mechanisms that may aid immune defenses against persistent viral disease [16] . Antibodies are among the obvious candidates to complement CTL-mediated control . However , their contribution to the resolution of primary virus infections in general , and persisting ones in particular , has remained controversial . Rapid mutational escape of persisting viruses from antibody neutralization represents a major obstacle to efficient antibody-mediated control [17–21] . Moreover , observations that patients with Bruton's agammaglobulinemia can control acute viral diseases [22] helped create a generally held notion that , unlike what applies for protection against reinfection , primary viral infections were predominantly controlled by cell-mediated immunity [22] . Experiments in mice , monkeys , and man had shown that passive administration of potent nAbs or transgenic expression of a virus-neutralizing B cell receptor ( BCR ) can prevent infection [23 , 24] , augment virus control during infection [25–27] , or prevent the establishment of persistence [28 , 29] . Still , these experimental observations did not challenge the above dogma since the experimental conditions chosen did not mimic the kinetics and magnitude of the host's spontaneous nAb response ( delayed and weak ) . Similarly , it seemed unlikely that antibodies could influence LCMV control and persistence , until B cell–deficient mice were found to control the infection only transiently , or not at all . B cell–deficient mice showed vanishing CD8 T cell function and viral recrudescence [30 , 31] , but the conclusions became doubtful when the mice were shown to have a distorted splenic microarchitecture and intrinsically defective CD4 T cell responses [32–34] . As CD4 T cells are essential to the maintenance of effective antiviral CD8 T cell responses [35] , the shortcomings in viral resistance were concluded to result from defective T help , rather than from the lack of antibody [34] . Given the outlined uncertainties , combined with the importance of such fundamental knowledge in order to refine preventive and therapeutic strategies in humans , we have readdressed the role of specific antibody responses to the control and resolution of persistent infection . We used the LCMV model to establish viral infection in genetically engineered mice that support the development of B cells , but do so only with restricted diversity and predominantly LCMV-unrelated specificity . In addition , we infected B cell–sufficient mouse models , unable to mount either serum immunoglobulin M ( IgM ) or immunoglobulin G ( IgG ) responses . Our studies reveal that virus-specific antibodies , including early adaptive IgM responses , play an essential role in reducing viral loads and ultimately determine viral clearance or persistence .
Using the murine model of LCMV infection , we aimed here at investigating the contribution of specific antibody to prevent persistent infection . To overcome the limitations intrinsic to B cell–deficient mouse models ( i . e . , distorted splenic microarchitecture with resulting defects in CD4 T cell responses ) , we first exploited two genetically engineered mouse models with a severely narrowed , predefined BCR repertoire of LCMV-unrelated specificity . T11μMT [36] carry an immunoglobulin ( Ig ) heavy chain transgene in an IgM heavy chain–deficient background , whereas VI10YEN [37] combine an Ig light chain transgene with a knockin at the endogenous Ig heavy chain locus . Both constructs render the respective B cells specific for vesicular stomatitis virus ( VSV ) that is antigenically unrelated to LCMV ( for a more detailed description of these strains , including their residual ability of generating antibody repertoire diversity , see Text S1 ) . Unlike B cell–deficient mice , these animals exhibited a normal splenic microarchitecture in immunohistochemistry , and mounted unimpaired CD4+ T cell responses against LCMV , as determined by intracellular staining of interferon γ ( IFNγ ) upon peptide stimulation ( Figure S1 and Text S1 ) . We infected B cell–deficient μMT mice [38] ( targeted deletion of the IgM transmembrane domain ) , BCR-restricted T11μMT and VI10YEN mice , and C57BL/6 control mice with 106 plaque-forming units ( PFU ) of LCMV intravenously ( i . v . ) ( Figure 1 ) . Unlike C57BL/6 mice that resolved viremia within 12 d , T11μMT mice exhibiting the lowest degree of BCR diversity failed to contain the infection and—like B cell–deficient μMT mice—remained viremic throughout the observation period of 96 d ( Figure 1A ) . Similar , albeit less-pronounced , effects were seen in VI10YEN mice displaying a more diverse BCR repertoire than T11μMT mice . Seven of ten VI10YEN mice tested in three independent experiments exhibited protracted viremia as compared to C57BL/6 wild-type mice ( Figure 1A and unpublished data ) . Even more pronounced was the impact of BCR diversity on the control of the more invasive Clone 13 strain of LCMV ( Figure 1B ) . Only C57BL/6 mice succeeded in resolving viremia , whereas BCR-restricted VI10YEN and T11μMT mice , and B cell–deficient JHT [39] mice ( targeted deletion of the immunoglobulin JH locus; JHT and μMT mice were used likewise in this study ) remained viremic throughout the observation period of 123 d . Thus , BCR diversity was essential for efficient resolution of LCMV infection . Further support for this notion came from experiments in “quasimonoclonal” ( QM ) mice [40] with a predefined nitrophenyl-specific B cell repertoire owing to knockin of a rearranged immunoglobulin heavy chain gene in combination with an immunoglobulin light chain transgene ( Figure S2 ) . Interestingly also , the requirements for BCR diversity became apparently more stringent as the infection was prone to persistence . That is , VI10YEN mice were able to clear LCMV strain WE ( LCMV-WE ) , albeit with some delay , but they failed at resolving chronic infection with LCMV strain Clone 13 . The above patterns of virus control or persistence correlated only to a limited extent with the ability of the respective mouse strains to mount a late virus-neutralizing antibody response ( Figure 1C and 1D ) . In LCMV Clone 13 infection , the appearance of neutralizing serum activity around day 45 after infection coincided with viral clearance . In contrast , a clear rise in LCMV-WE-nAb occurred only between 50 and 74 d after infection , i . e . , more than 1 mo after viral clearance from the blood . In C57BL/6 mice , this response was consistently measured although the titers varied considerably between individual animals . With further delay and barely above the detection limit of our assays , nAbs were also measured in some VI10YEN mice ( Figure 1C , not statistically significant ) , providing only partial correlation with this mouse strain's ability to control LCMV-WE infection . In contrast , nAbs always remained below detection levels in viremic T11μMT mice . The lack of temporal association , at least in LCMV-WE infection , between the appearance of nAb and clearance , prompted us to study nonneutralizing antibody ( non-nAb ) responses . The glycoprotein ( GP ) is the only surface determinant on LCMV particles . It is synthesized as a precursor protein and is posttranslationally cleaved into GP1 and GP2 subunits that remain noncovalently associated [41] . GP1 makes up an outer globular domain , whereas GP2 forms a membrane-anchored stalk [41] . Hence , GP1 is accessible on the infectious virion surface , rendering this antibody specificity of particular interest . Here , we exploited recently developed ELISA techniques [42] for measuring LCMV-WE GP1-specific antibodies . By day 12 after infection , LCMV-WE evoked a GP1-specific IgG response in C57BL/6 mice and at lower titers also in V10YEN mice , but not in T11μMT mice , correlating with virus control ( Figure 1E , B cell–deficient μMT mice shown as negative controls ) . Thus , the timing of the GP1-binding antibody response as well as the differential magnitude in C57BL/6 , VI10YEN and T11μMT mice matched best the pattern of virus clearance . Next , we assessed the individual contribution of IgM and IgG responses to virus control . All monoclonal LCMV nAbs characterized today are of an IgG isotype , and so is the late nAb response observed in the course of natural infection [27] . Hence , any potential role of antibodies in resolution of LCMV infection had previously been accredited to IgG . To test for the role of class switch-dependent isotypes including IgG , we used gene-targeted mice lacking activation-induced cytidine deaminase ( AID−/− ) [43] . AID−/− mice are unable to undergo class-switch recombination and somatic hypermutation , and in our experiments , could not resolve LCMV-WE infection during the observation period of 96 d ( Figure 2A ) . As expected , AID−/− mice displayed a complete absence of nAbs and GP1-specific serum IgG ( Figure 2C and 2E ) , suggesting that immunoglobulin class-switch recombination and IgG production together with somatic hypermutation are essential steps in the resolution of LCMV infection . To assess a potential role of IgM antibodies we exploited the sIgM−/− mouse model [44] . sIgM−/− B cells express IgM as their surface receptor and secrete IgG upon class-switch recombination but are unable to secrete the early IgM isotype . Experiments were carried out to confirm that according to expectations and unlike B cell–deficient μMT mice , B cell–competent sIgM−/− mice display a normal lymphoid microarchitecture and mount unimpaired CD4+ T cell responses ( Figure S3 ) . Surprisingly , however , LCMV-WE infection resulted in substantially prolonged viremia in sIgM−/− mice as compared to C57BL/6 control mice ( Figure 2A ) , suggesting that contrary to expectations , an antibody response of IgM isotype contributed to virus control . More strikingly even , nine of ten sIgM−/− mice failed to resolve LCMV Clone 13 infection for a period of at least 100 d , whereas all nine C57BL/6 mice had cleared viremia within 42 d after infection ( Figure 2B and unpublished data ) . The analysis of nAb responses ( measuring both IgM and IgG , Figure 2C and 2D ) , confirmed that the kinetics and magnitude of the nAb response were indistinguishable in sIgM−/− and C57BL/6 controls , and therefore , likely were of IgG isotype as previously reported . As expected , also LCMV-WE-GP1–binding IgG responses showed normal kinetics in sIgM−/− mice . Somewhat higher GP1-specific IgG peak titers in sIgM−/− mice as compared to C57BL/6 control mice were likely the result of prolonged viremia with an increased antigen burden ( Figure 2E ) . In support of this notion , differences in antibody titers became particularly apparent between day 12 and 20 when C57BL/6 , but not sIgM−/− , mice had cleared the infection . The above experiments had suggested that differences in virus loads of sIgM−/− and C57BL/6 mice were manifest as early as 1 wk after infection ( p < 0 . 01 for LCMV Clone 13 , Figure 2B ) . Additional experiments corroborated this difference in early virus loads also for LCMV-WE infection ( Figure 3A , p < 0 . 01 ) . As a likely mediator of this difference , ELISA assays detected GP1-specific IgM responses in day 8 LCMV-WE–infected C57BL/6 , but not sIgM−/− , mice ( Figure 3B ) , antibodies that were absent from naive C57BL/6 mouse serum ( Figure 3B ) . Importantly also , the GP1-specific IgM responses measured here were confirmed to be entirely antigen-specific since total serum IgM ( Figure 3C ) , unlike serum IgG [45] , remained largely unaltered after LCMV infection . A time-course analysis revealed that GP1-specific IgM was highest on day 4 and 7 after infection , followed by a continuous decline of this isotype concomitant with class switch and appearance of GP1-specific IgG ( Figure 3D ) . These assays were , however , performed with unseparated serum , and competition between IgG and IgM in ELISA may have resulted in an underestimation of IgM levels at later time points . sIgM−/− mice not only lack adaptive IgM responses but also natural IgM , which contributes to control of other viral infections [46] . For dissecting the role of preexisting natural antibodies , we reconstituted sIgM−/− mice with naive C57BL/6 mouse serum ( Figure 3E ) . Despite reaching total serum IgM levels at least equivalent to normal C57BL/6 mice , reconstitution of natural IgM in sIgM−/− mice failed to restore virus control ( Figure 3F ) . Taken together , these data demonstrated that adaptive IgM as well as IgG responses both played essential roles in the efficient resolution of LCMV infection . Interestingly , unaltered nAb kinetics in sIgM−/− and C57BL/6 control mice suggested that antiviral IgM mediated its effects by mechanisms other than classical virus neutralization . Next , we studied whether antibody therapy could restore virus control in BCR-restricted LCMV noncontroller mice . For this purpose , we infected T11μMT mice with LCMV-WE and treated them on day 4 and day 7 with either normal serum ( negative control ) or with normal serum reconstituted with GP1-specific monoclonal antibody ( Figure 4A ) . T11μMT mice treated with GP1-specific antibody eliminated LCMV as efficiently as did C57BL/6 wild-type mice , whereas control-treated T11μMT mice remained viremic , as expected ( compare Figure 1A ) . The same antibody treatment that was successful in T11μMT mice failed , however , to exert a detectable effect on virus loads when administered to TCRβ−/−δ−/− mice [47] lacking T cells owing to homozygous deletion of the T cell receptor β and δ chain loci ( Figure 4B ) . These data were compatible with the interpretation that T cells of T11μMT mice could control LCMV infection if appropriately aided by specific antibodies , whereas neither T cells nor antibody therapy was sufficient to control LCMV on its own . Exhaustion of CD8 T cell responses as a result of continued antigen exposure is a common observation in persistent viral infection [48 , 49] . Hence , we investigated whether antibody therapy could prevent CD8 T cell exhaustion in T11μMT mice . The initial LCMV-specific CD8 T cell response of T11μMT mice not only was of normal frequency and was functional in terms of IFNγ secretion ( Figure S1D ) but also displayed an unimpaired capacity for killing antigenic cells in vivo , irrespective of antibody treatment ( Figure 4C ) . Of note , virus loads were still similar in all groups when these tests were performed on day 7 ( Figure 4D ) . On the contrary , defective cytolytic activity was observed in control-treated T11μMT mice on day 35 during the chronic phase of infection . Prevention of viral persistence by antibody therapy ( Figure 4F ) restored in vivo cytotoxicity of T11μMT mice to normal levels on day 35 ( Figure 4E ) . This lent further support to the interpretation that the CD8 T cell response of T11μMT mice was intrinsically normal , and that its decline during chronic infection was merely the result of viral persistence rather than the cause thereof . Albeit less likely , a subtle intrinsic CD8 T cell deficiency of T11μMT mice cannot , however , be formally excluded . Irrespective thereof , antibody therapy may help preserve the antiviral CD8 T cell response . To evaluate the role of the classical and alternative complement cascades as major effector pathways of antibody-mediated immunity , we studied clearance of LCMV-WE in mice lacking complement components C3 and C4 ( C3−/−C4−/− mice; see Materials and Methods ) . C3−/−C4−/− mice resolved viremia as efficiently as wild-type control mice ( Figure 5A ) , whereas B cell–deficient JHT control mice remained viremic throughout . An analogous experiment was carried out in mice lacking Fc γ receptors I , III , and IV owing to deletion of the common γ chain ( FcRγ−/− [50] ) . FcRγ−/− mice cleared LCMV-WE infection as efficiently as did C57BL/6 wild-type mice , whereas B cell–deficient JHT and T11μMT mice both showed unchecked viremia throughout the observation period ( Figure 5B ) . Unlike Fc γ receptors I , III , and IV , Fc γ receptor IIB ( FcγRIIB ) expression does not depend on the common γ chain . To study the contribution of this receptor , we infected FcγRIIB -deficient mice ( FcγRIIB−/−; see Materials and Methods ) with LCMV , but found unimpaired virus control ( Figure 5C ) . Taken together , these data excluded an essential individual contribution of classical and alternative complement cascades , of Fc γ receptors I , III , and IV , and of FcγRIIB , respectively , in mediating protective antibody effects in the natural course of LCMV infection .
The present data show that virus-specific antibody responses , including early IgM , play an unexpected key role in preventing viral chronicity in the CTL-controlled murine model of LCMV infection . These observations are compatible with the rapid escape from antibody recognition seen in other primarily CTL-controlled infections , including HIV and HCV [19–21] , and indicate that specific antibody responses represent a level of antiviral pressure that tends to be underappreciated . The observed antiviral effects can only be partially accredited to antibody-mediated virus neutralization . Albeit clearance of LCMV Clone 13 in C57BL/6 mice did coincide with the appearance of nAbs ( compare Figure 2B and 2D ) , IgM effects on LCMV Clone 13 and LCMV-WE titers were evident already on day 7/8 after infection ( Figures 2A , 2B , and 3A ) at a time when nAbs were undetectable even if using virtually undiluted serum for the assays ( unpublished data ) . Similarly , LCMV-WE was cleared weeks before nAbs could be detected ( compare Figure 2A and 2C ) . Obviously , “absence of proof” for early nAb does not equate “proof of absence , ” and we recognize that “nAb consumption” during viremia or subsequent phases of protracted clearance from tissues [51] would provide an explanation for our inability to detect nAbs . However , we favor the idea that the delay in LCMV nAb detection , relative to the antiviral effects observed , rather results from the need for time-intensive affinity maturation [42] . The protective capacity of nAbs is classically explained by “virion occupancy , ” i . e . , sterical hindrance interfering with cell-surface receptor binding [52] . Non-nAbs , on the other hand , may mediate protection via a number of mechanisms , including: ( 1 ) virion occupancy by complement C1q binding to a virion-bound antibody [53] , ( 2 ) complement cascade activation , leading to further virion occupancy through covalent opsonization , ( 3 ) complement-mediated virion lysis , ( 4 ) Fc-receptor–mediated virion phagocytosis and destruction , ( 5 ) Fc-receptor–mediated stimulation of the innate immune system , ( 6 ) immune complex formation and resulting modification of tissue distribution and cellular tropism , ( 7 ) antibody-dependent cellular cytotoxicity ( ADCC ) , via antibody binding to viral surface proteins on infected cells , ( 8 ) impaired virus production , through antibody-mediated cross-linking of cell surface–expressed viral envelope protein [54] , or ( 9 ) destruction of target protein or host cells , through antibody-mediated reactive oxygen catalysis [55] . Although a full assessment of the individual contribution of each of these potential pathways lies outside the scope and intention of the present study , we do present data ruling out a major individual contribution for covalent complement opsonization and lysis , mediated through C3 and/or C4 activation , as well as for FcRγ- and FcγRIIB-facilitated mechanisms [50 , 56] ( Figure 5 ) . It remains possible that another mechanism not yet experimentally addressed here may account for most of the antibody effects observed , e . g . , Fc α/μ receptor–mediated clearance [57] could explain the observed IgM effects ( Figures 2A , 2B , and 3A ) . However , substantial redundancy in these multiple mechanisms may render it difficult to work out the contribution of individual mechanisms including the ones we have tested here , i . e . , in the absence of a specific pathway , compensation by the remaining ones may suffice for virus clearance . The present findings are of considerable importance for our understanding of virus–host relationship in persistent infection and for refining preventive and therapeutic strategies: The success of antibody therapy in T11μMT mice , but not in TCRβ−/−δ−/− animals ( Figure 4A and 4B ) , suggests a synergistic effect of cellular and humoral immune defense , at least for LCMV . Antibody therapy can apparently help preserve T cell function , and hence early administration may be most promising . Albeit our experimental therapy was administered during a phase of infection in which IgM predominates ( compare Figure 3D ) , IgG was efficient . This may be of practical importance since both vaccination and immunotherapy typically rely on IgG rather than on IgM . Owing to structural reasons , potent nAb responses against persisting viruses are generally difficult to elicit through vaccination [20 , 58] , but non-nAbs represent an attainable goal . The present data from LCMV infection in mice strongly suggest that non-nAbs , alongside antiviral CTL responses and nAbs , can determine clearance or persistence . We suggest that non-nAbs operate by blunting the infection and thereby strengthening the efficacy of other immune mediators such as CTLs and nAbs , but also NK cells [59 , 60] . In the context of the cited literature , our data support the idea that antibodies should be considered anew in vaccination strategies aimed at combating persistent viral disease , and that aside from nAbs as a vaccine goal , non-nAbs also should be induced and assessed . It has recently been shown that non-nAbs specific for LCMV GP-1 can mediate protective effects when expressed in a transgenic context [27] . In nontransgenic wild-type mice , we now show that virus-specific antibody responses , including GP-1–binding IgM , are not only generated rapidly ( see also Figure 2G ) , but also exert significant antiviral pressure ( compare Figure 2B and 2F; p < 0 . 01 ) in the days before nAbs become detectable . Although we focused in our assays on GP-1 binding antibodies , it remains entirely possible that additional non-nAbs of alternative specificities may also contribute to the observed protective effects . Defining characteristics and specificities of “protective” and “nonprotective” non-nAbs may therefore represent an important next step in the direction of exploiting the protective capacity of non-nAbs for vaccination and immunotherapy . Failure of the HIV AIDSVax trial eliciting mostly non-nAbs in the absence of cell-mediated immunity has somewhat dampened the hope that non-nAbs could help containing persistent infections [61 , 62] . Albeit non-nAbs are apparently unable to protect on their own , studies have correlated ADCC with HIV nonprogression , suggesting that non-nAbs may indeed contribute to long-term control of HIV [63] . However , much remains unclear about the overall importance of non-nAbs , and antibodies in general , to the natural course of HIV infection [64] . Moreover , the available data emphasize that the mechanisms of antibody-mediated protection do not always follow the traditional way of thinking . For instance , even a broadly HIV-neutralizing monoclonal antibody was shown to protect primarily via Fc-receptor–dependent mechanisms [65] . Of note in this context , the HIV envelope displays defective glycoproteins in great abundance [66] . Albeit unable to mediate cell entry , such defective glycoproteins are highly immunogenic and may represent efficient targets for non-nAbs . Of further importance here , non-nAbs have a relatively broad spectrum of activity against both autologous and heterologous HIV strains [67] . Taken together , the results from this study show that CD8 T cells , even if firmly established as the predominant mechanism of antiviral immune defense , need support from specific antibodies to prevail and prevent viral persistence . Given the relative ease of induction of non-nAbs ( relative to nAbs ) , combined with the observed protective effects , our findings may provide new impetus for inclusion of antibody targets in vaccines against persistent viral diseases .
C57BL/6 wild-type mice , μMT−/− [38] , JHT−/− [39] , T11μMT [36] , VI10YEN [37] , QM [40] , AID−/− [43] , sIgM−/− [44] , C3−/−C4−/− double-deficient mice ( a crossbreed of C3−/− [68] and C4−/− [69] mice ) , TCRβ−/−δ−/− [47] , and FcRγ−/− [50] were bred at the Institute of Laboratory Animal Science , University of Zurich , and were housed under specific pathogen-free ( SPF ) conditions throughout . FcγRIIB−/− mice on a pure C57BL/6 background , in which exons 4 and 5 , encoding the ligand-binding EC2 and transmembrane ( TM ) region , have been deleted by gene targeting in Bruce4 ES cells ( C57BL/6 background ) , were generated in the laboratory of Sjef Verbeek . Absence of functional FcγRIIB was confirmed both in functional in vivo and in vitro assays and at the protein level , as will be described elsewhere in more detail . Experiments with FcγRIIB−/− mice and controls were performed in a conventional mouse facility . Animal experiments were carried out at the University of Geneva and the University of Zurich with authorization by the respective cantonal authorities and in accordance with the Swiss law for animal protection . LCMV-WE was originally obtained from F . Lehmann-Grube ( Heinrich-Pette Institut , Hamburg , Germany ) and was propagated on L929 cells . LCMV Clone 13 was obtained originally from R . Ahmed ( Emory University , Atlanta , Georgia , United States ) and was grown on BHK-21 cells . Infections were performed at a standard dose of 106 PFU by the intravenous route . For therapy of T11μMT and TCRβ−/−δ−/− mice , GP1-specific monoclonal antibody KL25 [70] was administered intraperitoneally on day 4 ( 100 μg ) and on day 7 ( 1 mg ) , reconstituted in 400 μl of normal ( nonimmunized and uninfected ) C57BL/6 serum . Control animals were given 400 μl of normal serum . LCMV virus stocks and blood samples were titrated by standard immunofocus assays on MC57G cells [71] . nAbs against LCMV-WE and LCMV Clone13 were measured in an immunofocus reduction assay using the respective homologous virus as described [58] . GP1-specific IgM and IgG responses were measured by ELISA using a GP1-Fc fusion construct produced in an eukaryotic system as described [42] . In the GP1-Fc construct , amino acids 1–265 ( i . e . , the GP1 domain [42] ) of the LCMV-WE glycoprotein gene are fused to human Fc . As sole modification to the published method , anti-mouse IgM monoclonal antibody coupled to HRP ( Sigma ) was used instead of anti-mouse IgG when detecting GP1-specific IgM . Total serum IgM titers were measured in ELISA as described previously [45] . Titers displayed represent the serum dilution yielding twice background optical density values . Single-cell suspensions of splenocytes were used for intracellular cytokine assays as described [72] . Restimulation of virus-specific cells was performed for 5–6 h in the presence of the following synthetic peptides at 10−6 M concentration: KAVYNFATC ( GP33 , CD8+ T cells ) , GPDIYKGVYQFKSVEFD ( GP64 , CD4+ T cells ) , and SGEGWPYIACRTSVVGRAWE ( NP309 , CD4+ T cells ) . Cytotoxic activity of CD8+ T cells was measured in an in vivo CTL assay as previously described [73] . In brief , syngeneic C57BL/6 splenocytes were labeled with the fluorescent dye carboxyfluorescein diacetate succinimidyl ester ( CFSE ) at two different concentrations ( CFSEhigh or CFSElow ) . In addition , CFSEhigh cells were pulsed with GP33 peptide at 10−6 M concentration for recognition by antiviral CTLs . 3 × 107 cells of each population were cotransferred into virus-infected recipient mice and into naive C57BL/6 mice ( control ) . Five hours later , the percentage of CFSEhigh and CFSElow donor cells in peripheral blood mononuclear cells was determined by flow cytometry . Specific killing was calculated as: 100 − ( [ ( % CFSEhigh in test animal / % CFSElow in test animal ) / ( % CFSEhigh in naive / % CFSElow in naive ) ] × 100 ) . Histological analyses were performed on snap-frozen tissue . Sections were stained with rat monoclonal antibodies against murine B220 ( Pharmingen ) , F4/80 , MOMA1 , and ERTR9 ( all from BMA Biomedicals ) . Bound antibody was detected using a goat anti-rat antibody ( Caltag Laboratories ) and an alkaline phosphatase–coupled donkey anti-goat antibody ( Jackson ImmunoResearch Laboratories ) with naphthol AS-BI ( 6-bromo-2-hydroxy-3-naphtholic acid 2-methoxy anilide ) phosphate and new fuchsin as a substrate . The sections were counterstained with hemalum . For tissues of VI10YEN mice carrying a light-chain transgene with rat constant domains , reaction of anti-rat monoclonal antibody with the transgenic light chain was prevented by using an alkaline phosphatase conjugated Fc γ fragment–specific goat anti-rat IgG antibody as a secondary antibody ( Jackson ImmunoResearch Laboratories ) . One-way analysis of variance ( ANOVA ) with the Least Significant Difference ( LSD ) post test was used for the comparison of individual values from multiple groups . Two-way ANOVA was performed to compare antibody responses over time . ANOVA was performed with SPSS version 13 . 0 . Differences in individual values between two groups were analyzed by t-tests ( unpaired , two-tailed ) , and virus clearance kinetics were compared in log-rank tests using GraphPad Prism software vs . 4 . 0b . Viral titers were log-transformed for statistical analysis , and viral clearance kinetics were compared in a Kaplan-Meier format . p-Values < 0 . 05 were considered statistically significant; p-values < 0 . 01 were considered highly significant . | Persistent viruses such as hepatitis C virus ( HCV ) or HIV can defeat the body's defense system and cause devastating epidemics worldwide . Recent attempts at vaccinating against HIV have relied on the induction of specific antiviral killer T lymphocytes but have failed to confer protection on the host . Better knowledge about how a successful defense should operate is therefore essential for developing and refining new vaccines . Here , we have used a prototypic mouse model to investigate basic defense mechanisms required to eliminate persisting viruses . Experiments in several genetically engineered mouse models show that contrary to common belief , not only antiviral killer T cells , but also antibodies ( produced by B cells ) , are needed to prevent a virus from persisting in its host . These findings suggest that induction of antibodies , along with antiviral killer T lymphocytes , should be envisaged when devising new strategies for vaccinating against HIV or HCV . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"immunology",
"virology"
] | 2009 | Impaired Antibody Response Causes Persistence of Prototypic T Cell–Contained Virus |
NREM sleep is characterized by two hallmarks , namely K-complexes ( KCs ) during sleep stage N2 and cortical slow oscillations ( SOs ) during sleep stage N3 . While the underlying dynamics on the neuronal level is well known and can be easily measured , the resulting behavior on the macroscopic population level remains unclear . On the basis of an extended neural mass model of the cortex , we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs . As the cortex transitions from wake to deep sleep , in our model it approaches an oscillatory regime via a Hopf bifurcation . Importantly , there is a canard phenomenon arising from a homoclinic bifurcation , whose orbit determines the shape of large amplitude SOs . A KC corresponds to a single excursion along the homoclinic orbit , while SOs are noise-driven oscillations around a stable focus . The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep .
Several studies indicate a major role of slow wave sleep ( SWS ) in the consolidation of memories [1] , [2] . Especially its hallmarks , cortical slow oscillations ( SO ) , are hypothesized to be a key mechanism for the transfer of memory into the neocortical long-term storage [3] , [4] . Furthermore , it has been shown that the efficacy of memory consolidation can be improved with oscillatory transcranial electric and phase-locked auditory stimulation [5]–[7] . In the human electroencephalogram ( EEG ) SOs are defined as waves with a frequency of 0 . 5–2 Hz and a peak-to-peak amplitude >75 µV [8] , [9] . Underlying the SO is a widespread , almost synchronous alternation of neocortical networks between phases of depolarization ( active or up state ) and hyperpolarization ( silent or down state ) [10] , [11] , that behaves like a traveling wave [9] , [12] . Modeling and experimental studies indicate a role for both , synaptic mechanisms and intrinsic currents , in the generation of SOs [13]–[16] . The K-complex ( KC ) occurs at the pace of the SO [17] and is believed to be the EEG expression of the cellular slow oscillatory activity [18] . The negative peak of the KC marks the transition to the cellular up state [19] . A KC during light NREM sleep ( N2 ) was identified to be an isolated down state [20] . Furthermore , KCs show a high variability in morphology and amplitude , but are generally characterized as a negativepositive event with a sharp negative peak . Common variations of this theme are multiple peaks in the negative component or an initial positive bump before the negative-positive complex . The components of evoked KCs were found to have typical latencies , namely the P200 , N550 and P900 peaks . It was suggested that these components are not independent and share a common generation mechanism . Sometimes later components ( N1500 , P1900 ) with smaller amplitude are reported too [21] , [22] . The complexity of the brain on the structural as well as the neuronal level has , however , been challenging for theoretical studies and modeling approaches . Neural mass models , pioneered by the work of [23] and [24] , successfully described many phenomena of the human EEG , e . g . alpha and gamma rhythms , evoked responses and epilepsy [25]–[27] . See [28] and [29] for reviews . In addition to states of wakefulness sleep has been modeled within the neural mass framework , too . A parameter study by [30] revealed the importance of synaptic gains for the dominant frequency of neural mass models . Steyn-Ross et al . [31] investigated the effect of changes in the efficacy of excitatory connections and the resting membrane voltage , finding multiple stable states which they classified as sleep and wake . While those features are generated within a -local- column of neural tissue , spatial components have been shown to lead to complex interactions with the intrinsic dynamics , e . g . Turing patterns and traveling waves [32] , [33] . However , within this study we focus on the generation of KCs as well as SOs rather than their spatial propagation . Nevertheless , our model can form the basis of a network of neural masses that covers spatial aspects , such as wave propagation . Activity-dependent feedback via slow potassium channels has been suggested as a mechanism for the generation of SOs and KCs because of their sensitivity to the sleep related neuromodulator acetylcholine and their implication in the slow afterhyperpolarization [34] , [35] . Multiple studies also point out that potassium leak channels can be activated by several anesthetics [36]–[38] . In the neural mass framework additive and multiplicative adaptation mechanisms have been discussed by [39]–[41] . So far KCs were described as excursions from a stable silent state to an unstable active state and the related SOs as oscillations between those two states [42] , [43] . However , while for certain forms of anesthesia it seems plausible that the cortex undergoes a phase transition , it is not clear whether this necessarily holds for natural sleep [39] , [44] . Addressing these issues we present a neural mass model for the sleeping cortex which is extended by sodium dependent potassium current [45] , [46] . This approach links our neural mass model to modeling studies on SO generation based on single neurons as well as to experimental studies [14] , [16] . The model output resembles EEG time series of sleep stages N2 and N3 to a high degree and shows key features of spontaneous and evoked KCs . Building upon a bifurcation analysis , we characterize the dynamic repertoire of the cortex model . Our analysis indicates that cortical SOs and KCs are related but different phenomena . We suggest a route for the transition from wake to deep sleep and point out differences between natural sleep and anesthesia .
Instead of considering single neurons individually , an averaged representation of the respective neuron type describes the behavior of a whole population . The mean membrane voltage of the neural population is transformed into a firing rate via a sigmoidal mapping [25] , [47] . ( 1 ) Here , is the maximal firing rate of the respective population , while represents the firing threshold of the population and the gain or steepness of the transition . acts as a scaling factor that links the gain directly to the standard deviation of the change in firing rate . At the dendrites , incoming spikes elicit transmitter release leading to the opening of synaptic channels . At any time , the fraction of open channels of type at population can be described by a convolution with an alpha function [48] , with ( 2 ) Here , the inverse rise time determines its shape . The sum is over all spikes from different sources that arrive at the same type of synapses at population . We consider AMPAergic synapses for excitation and a generic GABAergic type for inhibition , leading to the second order differential equations ( 3 ) Here , stands for the mean number of synaptic connections of type to population k . While inhibitory populations only spread locally , there are two different sources of excitation: local inputs and background noise coming from unspecified brain structures , which is taken as uncorrelated Gaussian white noise with zero mean . To model external stimulation the mean of the background noise is elevated by representing increased incoming spike rates . The connectivity structure of our model is given in Figure 1 . It consists of an excitatory and an inhibitory population coupled all to all . An important assumption of most neural mass models is the existence of an equilibrium state the system is always close to [23] . However , this is not true for KCs and SOs and the scaling of synaptic currents with respect to the membrane voltage becomes important . This was addressed by [49] with the introduction of a weighting term . Their model can be written similar to the classical conductance based form of [50] with one leak and two synaptic currents as ( 4 ) Here , depicts the maximal conductivity , and corresponds to the Nernst potentials of the respective channel . The potential fluctuations measured in an EEG are mainly generated by pyramidal neurons [51] . Therefore , we use the membrane voltage of the excitatory population as our output variable . Similarly , multiple studies [25] , [49] , [52]–[54] used either the deviation of the membrane voltage from the resting state , , or the membrane voltage itself . As our system has no spatial extension and we only assume ohmic effects of skull and scalp , the EEG signal can be approximated by a linear scaling of the excitatory membrane voltage . When comparing experimental data and model output both time series are z-scored , because this linear transformation normalizes mean and standard deviation but preserves the other statistical properties of a signal . As we are only interested in qualitative properties of the model , e . g . the ratio between medium amplitude background oscillations and large amplitude deflections during N2 , the different sleep stages are z-scored independently . For quantitative statements the same measuring function must be used . As motivated in the introduction , we add the sodium dependent potassium current ( 5 ) to the excitatory population , see Equation 4 . The current is connected to the excitatory membrane voltage by a membrane capacity Cm = 1 µF/cm . Sodium influx responsible for activation results from spiking or activation , for which a depolarization above −60 mV is sufficient . We do not explicitly model these mechanisms but combine their effects via the Ve-determined spike rate and regard as average sodium influx per spike . Sodium extrusion is due to an active pump [55] , which is detailed in Text S1 . For simplicity , we neglect synaptic depression and other candidate mechanisms for additive feedback , like calcium dependent potassium currents . This approach is qualitatively different to changes in the firing rate function , as utilized by [39] . Gradually switching between two firing rates alters the overall shape of the sigmoid function in a multiplicative activity-dependent manner , whereas we employ an additive threshold modulation . The model was implemented in C++ and run within MATLAB [56] . The stochastic differential equations were iterated using a stochastic Runge-Kutta method of 4th order [57] with a step size of 0 . 1 ms . Simulation length was chosen as 30 s with a 5 s onset to ensure a steady state . All settings were run multiple times to check for robustness . Full model equations and parameters are given in Text S1 and Table S1 . Bifurcation analysis is done with XPPaut [58] , and a script is provided in Text S2 .
In order to characterize the dynamic repertoire of the cortical model we conducted a numerical bifurcation analysis of the noise-free system . The qualitative behavior of the model was most sensitive to changes in the inverse gain , , of the pyramidal population and the strength of the adaption , . Additionally , both parameters are known to be susceptible to changes in the neuromodulatory milieu , and the concentration of many major neuromodulators is known to change throughout the sleep-wake cycle . Cortical acetylcholine levels are lowest during slow wave sleep and highest during wake and REM sleep , whereas serotonin and norepinephrine levels are highest during wake , intermediate during SWS and lowest during REM sleep [59] . Tonic application of acetylcholine blocks leak and activity-dependent potassium currents , , , ( reviewed in [60] ) , as well as [61] . Furthermore , many studies show that can be altered by norepinephrine , serotonin , acetylcholine as well as dopamine [35] , [62]–[69] . Consequently , and were chosen as bifurcation parameters . The adaptation currents are primarily found in excitatory pyramidal cells and less so in inhibitory interneurons , which justifies the restriction of the parameter changes to the excitatory population . As can be seen in Figure 2 the dynamics of the system is shaped by two bifurcations . The first one is a fold created by two saddle node bifurcations ( black ) , that vanishes in a cusp . Between the two saddle nodes there are three equilibrium states , leading to bistability or excitability , see Figure 3a or Figure 3b . This is in good agreement with [31] and [70] , as in the case of a fixed sodium concentration is constant , and an increase in acts as a decrease in resting potential . The second bifurcation is a Hopf arising at the upper stable branch ( red ) . Importantly there is a canard explosion , where the small amplitude limit cycle of the Hopf bifurcation transitions into a high-amplitude relaxation cycle . This phenomenon was first described by [71] and is typical for systems where fast and slow subsystems interact . The relaxation cycle vanishes at the left saddle-node via a homoclinic bifurcation . At the cusp both saddle nodes coalesce and the homoclinic bifurcation turns into a second Hopf point . Based on those bifurcations we define multiple dynamical regimes , see Table 1 for a short overview . Within region I a single stable state exists at depolarized membrane voltages where the cortex shows relatively high activity ( see Figure 3 ) . Especially for small values of even large excitatory and inhibitory inputs only cause a passive response . A switch to the lower branch of the S-shaped curve in Figure 3 ( region IV , silent state ) is not possible . Because of these properties we assume the waking brain to operate within this regime . When crossing the curve of saddles to region V two new fixed points appear ( see also Figure 3a ) . The system becomes bistable , with a stable active and silent state . Positive and negative inputs can cause a switching between the two stable branches . A further increase in turns the upper branch ( active state ) unstable . However , within region VI there are still multiple equilibria leaving the system excitable . Here a stimulus can produce a large positive response , which was previously thought to be responsible for the generation of KCs as well as SOs [72] . Only after the second saddle node is crossed the upper two equilibria vanish and a single stable state remains . This state is characterized by hyperpolarized membrane voltages leading to a quiescent cortex . Region III is characterized by periodic limit cycles or relaxation oscillations and , hence , high rhythmicity . The initial Hopf bifurcation is accompanied by a canard explosion: due to an exponentially small variation of the bifurcation parameter an abrupt transition from a medium-amplitude limit cycle to a high-amplitude relaxation cycle can take place . This phenomenon was first described in [71] and is typical for systems where fast and slow subsystems interact . The corresponding one-dimensional bifurcation diagram is shown in Figure 3b . The periodic solutions vanish at the left saddle-node via a homoclinic bifurcation , and the period of the relaxation oscillations goes to infinity as one approaches the homoclinic bifurcation . Additionally , with increasing the amplitude of the limit cycle increases and approaches the form of relaxation oscillations . This explains the similarity between the limit cycles and relaxation oscillations . Both are shaped by the same homoclinic orbit . At the cusp the two saddle nodes vanish and the homoclinic bifurcation turns into a second Hopf point . Without the homoclinic bifurcation there is no canard anymore . Therefore , in region II above the cusp bifurcation only limit cycles remain , illustrated in Figure 3c , leading to high-amplitude oscillations . While the bifurcation analysis provides the basic repertoire of the unperturbed model , its responsiveness with respect to perturbations , e . g . external stimuli or background noise , is crucial for its behavior . As mentioned before , within region I the cortex shows only a passive response . However , this changes for larger values of , i . e . closer to the curve of Hopf points ( red line in Figure 2 , separating region I from II and III ) . There , positive as well as negative inputs may cause a reverse spike resembling a KC . Additionally , close to the curve of Hopf points the stable active state turns into a stable focus , i . e . the system behaves like a damped oscillator upon perturbation . In Figure 4a we show the response to artificial stimuli of varying strength , when the cortex is set close to the Hopf bifurcation between region I and III . Stimuli of low strength lead to damped oscillations whose amplitudes are considerably larger than during the wake state but smaller than KCs or SOs . However , as the strength of the stimuli increases the system is pushed into the canard explosion and the amplitude of the response increases rapidly . While in Figure 4a there seems to be a threshold separating the two types of responses , it is actually a smooth transition given sufficiently small increases in stimulation strength . The induced relaxation cycles show a good qualitative match with KCs seen during sleep . In the noise driven simulation the majority of inputs would lead to medium-amplitude oscillations , whereas only the rare outliers would trigger a KCs like response . This is in good agreement with the dynamics seen in sleep stage N2 , where medium-amplitude background oscillations are interrupted by large amplitude KCs . We assume this mechanism to be responsible for the generation of KCs during sleep stage N2 . Furthermore , this requires the cortex to be in the active state close to the Hopf bifurcation to region III , rather than being in the silent down state . This is in good agreement with multiple studies who report that during SWS of naturally sleeping animals more time is spent in up states than in down states [73]–[78] . Close to the Hopf , an increase of the inverse gain , , leads to an increase in the amplitude of the background oscillations and they approach the shape of a relaxation cycle . Beyond the cusp the canard vanishes and isolated events in the sense of KCs are not possible anymore ( see Figure 4b ) . This behavior is well reflected in what is seen during sleep stage N3 , where SOs appear as large amplitude oscillations , that are not separated from the ongoing background activity . Furthermore , it explains the high similarity between KCs and SOs , as they are both shaped by the same homoclinic orbit . We hypothesize that during sleep stage N3 the cortex is in region I close to the Hopf bifurcation to region II . Together these findings give rise to a new interpretation of the sleep/wake transition . At the transition to sleep stage N2 , the cortex approaches the Hopf bifurcation close to region III , which shifts the EEG trace to higher amplitudes and lower frequencies compared to wake activity . By virtue of a canard explosion this background activity is then interrupted by single , isolated relaxation cycles . As sleep deepens further , the cortex follows the route depicted in Figure 2 , while the amplitude of the background oscillations increases and ultimately approaches the form of a KC . However , this is in contrast with the view that the cortex undergoes a phase transition when entering NREM sleep . Interestingly , a similar model was utilized to describe characteristics of anesthesia [39] . We can reproduce similar behavior , e . g . burst suppression in region VI ( See Supplementary Figure S1 ) . To verify the ability of the model to reproduce sleep stage N2 we set the model to parameter configuration “N2” from Figure 2 ( See Table 2 ) . The chosen parameter set is within region I close to the border of region III , an example time series is shown in Figure 5 . In a region close to the chosen parameters the cortex is in the up state and shows the expected noise-driven medium-amplitude oscillations . In addition , background noise may push the model into high-amplitude deflections that closely resemble KCs seen in human EEG . Similar to the data the KCs can show a single pronounced peak or a prolonged down state , which depends on the noise . Following our route for the sleep/wake transition in Figure 2 we then moved along the Hopf bifurcation to a setting beyond the cusp and close to region II , labeled as “N3” . In Figure 6 a representative time series is shown with the parameters given in Table 3 . There the cortex shows high amplitude oscillations around 0 . 8 Hz . In contrast to the N2 stage , the cortex does not produce KCs in the sense of isolated events that differ from the background oscillations . Rather , the response increases until it approaches the form of a KC , depending on the strength of the perturbation .
We explored an extended neural mass model of the cortex and related its multiple dynamical regimes to different sleep stages . A bifurcation analysis revealed the existence of a fold as well as a Hopf bifurcation accompanied by a canard phenomenon . We argue that deflections generated by the canard explosion are identical to KCs seen in the EEG during natural sleep , leading to the spike-like nature of the KCs . Increasing the bifurcation parameter the canard vanishes , explaining the damped oscillatory behavior of SOs . Our analysis provides a clear theoretical distinction between KCs and SOs . However , as both the limit and the relaxation cycle are shaped by the same underlying homoclinic orbit , the actual transition is rather smooth even in the noise-free deterministic system ( see Figure 4 ) . Therefore , it might be challenging to find this distinction within experimental data . Based on the bifurcation analysis we identified parameter regimes that show characteristics of sleep stage N2 and N3 and showed that our model is able to reproduce the EEG of both sleep stages to a high degree . Building upon these findings we propose an alternative scenario for the sleep wake transition . Rather than entering a bistable regime the cortex stays primarily within the active state . As sleep deepens , the cortex approaches the Hopf bifurcation , leading to an increase in amplitude and slowing of noise-driven background oscillations , as well as large amplitude deflections , i . e . KCs . At the transition to sleep stage N3 the canard phenomenon vanishes due to the cusp bifurcation . The remaining Hopf bifurcation is responsible for the generation of noise-driven SOs . Isolated events as in sleep stage N2 are not possible within that regime . Parameter settings within region II or III lead to highly regular relaxation oscillations or limit cycles , that do not resemble human EEG . It is crucial that the cortex must be within region I close to region II or III to reproduce the data . In a study on resting state networks [79] found the awake brain to be in a state of criticality , which leads to an increased responsiveness . In this study , we also find the sleeping cortex close to a phase transition and suggest that the concept of criticality is not restricted to wakefulness , but carries over to sleep . However , the phase transition and computational goal are different . Due to the presence of noise bifurcations do not lead to clear-cut qualitative changes of the dynamics [43] . Noise can shift critical points or induce behavior that is not seen in the deterministic case , such as noise-induced transitions . Our work deals primarily with the characteristics of EEG signals during NREM sleep . However , the presented bifurcation analysis is useful in a broader context . Similar activity is found e . g . during non-REM sleep , anesthesia , coma and in isolated cortical preparations . It becomes increasingly clear that there exists a continuum of slow oscillatory states , which are mainly characterized by the fraction of time spent in up or down states , the temporal regularity with which state transitions occur and the response to external stimuli . The phenomenon of up and down states in intracellular recordings is commonly associated with the notion of bistability or relaxation oscillations . However , it is important to note that most results on SOs were obtained in deeply anesthetized animals or slice preparations . Under these conditions , the system is down state dominated , i . e . down states last longer than up states , the occurrence of up states is often highly rhythmic [76] , [80] or up states are infrequent and transient [81] . In our model these classical regimes are also present , namely in regions III , V and VI . Generally , SOs produced by anesthesia are much more regular than during natural sleep [76] , [82] . Under ketamine-xylazine anesthesia neurons spend twice the time in silent states compared to natural SWS [76] , and in the auditory cortex of awake rats prolonged up states are not even observed at all [83] . Furthermore , SO properties differ from one anesthetic to the other [84] . Ketamine-xylazine anesthesia produces a uniform and continuous SO state [85] , whereas with urethane epochs of stable SOs are short-lived and desynchronized periods may occur spontaneously [86] . This is similar to SWS where one finds waxing and waning of slow wave complexes interleaved with periods reminiscent of active states [74] . In contrast , [20] pointed out that a KC during light sleep is not always embedded in an ongoing SO , but is mostly an isolated event . Clearly , in N2 the active state dominates . Similarly , many studies report that during SWS of naturally sleeping animals more time is spent in up states than in down states [73]–[78] Furthermore , it has been reported that SWS contains many episodes of low-amplitude fast oscillations , lasting several seconds and resembling the active state [87] . This evidence points to natural sleep being up state dominated . Furthermore , bistability is inferred via bimodality in the distribution of individual cells' membrane potential . In local field potentials , one can observe a markedly conserved waveform of individual SO events [88] , but bimodality is already less visible . It is known that collective dynamics can exhibit , e . g . limit-cycle regimes , but at the same time emerge from irregular and high-dimensional neuronal activity , which is only apparent at small-scales [89] . The spectrum of SO phenomena cannot be fully captured by the concepts of bimodality or relaxation oscillations . Our analysis corroborates that the KC can be identified with a single , isolated relaxation cycle and slow wave activity , including prolonged episodes of low-amplitude fast oscillations , stems from noise-driven oscillations around a stable focus . Down states occur frequently in the up state dominated cortex , but they are transient . The assumption that a substantial gain change accompanies the change of sleep stages is reasonable , but still has to be clearly demonstrated experimentally for natural sleep . The only publication we are aware of that touches this issue is [73] . Our model indicates that an increase in gain can induce a bistable state when awake , moving from region I to region V . Likewise , looking at comatose states ( region IV ) a decrease in gain should induce limit cycle oscillations . Additionally , constant neural activation , i . e . arousal , causes relaxation oscillations in the model . Indeed , this phenomenon seems to occur in comatose patients , too , where one observes an increase in delta activity after stimulation [90] . This is termed paradoxical arousal and should not be confused with the paradoxical excitation/biphasic response during the induction process of anesthesia . Furthermore , given the suggested role of gain change in the transition between N2 and N3 , an altered slope of the f-I-relation of excitatory pyramidal cells could be a key factor in distinguishing wake and REM sleep . Activity-dependent and leak potassium currents ( or tonically activated extrasynaptic receptors ) are both able to promote bistability in a cortical population . However , only activity-dependent mechanisms contribute to rhythmicity . It would be interesting to see their contributions revealed for natural sleep and anesthesia . A study by Molaee-Ardekani et al . [39] showed that a similar model of slow firing rate adaptation can reproduce the effects seen under anesthesia . A comparison of our findings with their results suggest that the region of bistability ( V ) as well as the region of excitability ( VI ) are actually associated with anesthesia . A main result of this paper is that on the macroscopic level the cortex is not necessarily in a bistable regime during natural deep sleep . We argue that properties of KCs and SOs at the EEG level support the view of a monostable active cortex close to a Hopf and a saddle node bifurcation . We stress that the characterization of KCs and SOs is made on the population level . While the switching between up and down states on the cellular level points to relaxation oscillations or bistability with noise-driven transitions , relatively regular oscillation at the cellular level may appear less regular at the EEG level , due to varying spatial synchrony [82] . Relaxation oscillations in the EEG usually correspond to pathological conditions like epilepsy . We have not explicitly analyzed other adaptation mechanisms like multiplicative feedback arising due to synaptic depression or depletion of extra-cellular calcium or inhibitory modulation [91] . However , the additive activity-dependent feedback investigated here is sufficient to account for a multitude of phenomena in healthy and pathological conditions . Furthermore , we expect that the bifurcation structure of the system , i . e . presence of saddle-nodes , Hopf and homoclinic bifurcation , will persist in alternative settings . Thus , our main conclusions do not depend on the particular choice of the feedback mechanism . | In recent years , sleep has drawn increasing attention due to its multifunctional role , e . g . the involvement in the consolidation of memory . While neural mass models have been successfully employed to describe the dynamics of the awake brain , the drastic changes that arise during sleep have been challenging . As intracellular recordings point to a bistability in the membrane voltage of individual neurons , previous studies assumed a bistability to be responsible for the generation of SOs as well as KCs on the macroscopic scale . Here we present a minimal neural mass model of the cortex that we extend by a slow firing rate adaptation , which is assumed to underlie the termination of the cortical up state . A bifurcation analysis reveals the existence of a Hopf bifurcation together with an canard phenomenon . We show that these additional bifurcations are able to generate KCs as well as SOs , and reproduce the electroencephalogram ( EEG ) of sleeps stages N2 and N3 to a high degree . Based on these findings , we propose a new route for the sleep/wake transition , that is also consistent with the effect of neuromodulators on the brain . | [
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] | 2014 | Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model |
Evolutionary life history theory seeks to explain how reproductive and survival traits are shaped by selection through allocations of an individual’s resources to competing life functions . Although life-history traits evolve rapidly , little is known about the genetic and cellular mechanisms that control and couple these tradeoffs . Here , we find that two laboratory-adapted strains of C . elegans descended from a single common ancestor that lived in the 1950s have differences in a number of life-history traits , including reproductive timing , lifespan , dauer formation , growth rate , and offspring number . We identified a quantitative trait locus ( QTL ) of large effect that controls 24%–75% of the total trait variance in reproductive timing at various timepoints . Using CRISPR/Cas9-induced genome editing , we show this QTL is due in part to a 60 bp deletion in the 3’ end of the nurf-1 gene , which is orthologous to the human gene encoding the BPTF component of the NURF chromatin remodeling complex . Besides reproduction , nurf-1 also regulates growth rate , lifespan , and dauer formation . The fitness consequences of this deletion are environment specific—it increases fitness in the growth conditions where it was fixed but decreases fitness in alternative laboratory growth conditions . We propose that chromatin remodeling , acting through nurf-1 , is a pleiotropic regulator of life history trade-offs underlying the evolution of multiple traits across different species .
Organisms are faced with limited resources to invest in their growth , survival , and offspring . Because they cannot dedicate unlimited energy to all traits , they must prioritize energy distribution depending on their environment and sexual partners [1] . Trade-offs represent the combined change in fitness when a beneficial change in one trait is linked to a detrimental trait in another . For example , the benefit of increasing the number of offspring that are produced must be balanced by the cost paid in survival of the parent organism . Life-history theory seeks to understand how an organism’s life-history traits–including reproductive timing and behavior , lifespan , growth rate , and post-reproductive behavior–have been shaped by sexual and natural selection using key concepts such as trait value , trait costs , environmental predictability , and environmental stability [2 , 3] . Trade-offs are not absolute , but depend on an animal’s given environment [4] , indicating these traits should change as animals speciate and explore new niches . Empirical evidence confirms that life-history traits evolve very rapidly . Most life-history theories focus on phenotypic traits . However , given that these tradeoffs are ultimately genetically determined , it is important to understand their genetic underpinnings to understand how life-history traits are co-regulated and also how species-level differences in these traits emerge . As with most biological traits , however , few causative alleles have been found that influence life-history traits . As a more tractable model to understand how genetic variants impact a trait , we are focusing our studies on two C . elegans strains , N2 and LSJ2 , derived from the same hermaphrodite isolated in 1951 [5] . Although initially genetically identical , the two strains were separated into distinct cultures of either solid or liquid media in Ellsworth Dougherty’s laboratory in Richmond , California sometime between 1957 and 1958 ( Fig 1A ) [5] . N2 was cultured for approximately 15 years on agar plates seeded with E . coli bacteria . Bacteria are C . elegans’ natural food source [6] , so these growth conditions represent a rich environment for the animals . LSJ2 was cultured for approximately 50 years in liquid , axenic culture consisting of soy-peptone extract supplemented with beef liver extract [7] . This food source is very unnatural for C . elegans , so these growth conditions likely represent a poor nutrient environment for the animals . Both strains were eventually cryopreserved and the two genomes sequenced . We found that 94 new mutations were fixed in the N2 lineage and 188 new mutations were fixed in the LSJ2 lineage [8] . This genetic diversity is almost three orders of magnitude lower than the genetic diversity between wild strains of C . elegans [9–11] , and four orders of magnitude lower than the genetic diversity between two humans [12] , making identification of causative mutations through QTL mapping feasible . Despite this low level of genetic diversity , a large number of phenotypic differences distinguish the two strains . A total of four quantitative trait nucleotides ( QTNs ) have been identified in these strains to date , providing empirical evidence linking variation in a neuropeptide receptor activity to multimodal changes in social behavior [13 , 14] , variation in sensory gene deployment with specific chemosensory responses [5 , 8 , 15] , and identifying a source of cryptic genetic variation that affects organ development [16] . Here , we study the genetic basis of reproductive differences between the N2 and LSJ2 strains at five different timepoints . We first identify age-dependent differences in reproductive rate between these two strains . This difference is caused in part by a small deletion fixed in the LSJ2 lineage in the 3’ end of the nurf-1 gene , which encodes the ortholog to the BPTF subunit of the NURF chromatin-remodeling complex . Besides controlling reproductive timing , nurf-1 also influences additional life-history traits , including growth rate , lifespan , and dauer formation . The mutation is advantageous in the LSJ2 growth conditions , but disadvantageous in the N2 growth conditions . Finally , we map sensitivity to two unrelated anthelmintic drugs and two heavy metals to nurf-1 , suggesting that nurf-1 mutants prioritize individual survival over reproduction . Our results suggest that nurf-1 is a pleiotropic regulator of life-history traits and a target of evolutionary selection .
The timing of reproduction represents one of the most prominent life-history trade-offs [17] . In the course of routinely culturing the N2 and LSJ2 strains , we noticed a difference in egg density on bacterial plates , which we assayed quantitatively . The N2 reference strain has acquired previously described genetic variants in the npr-1 and glb-5 genes that affect a number of physiological traits [5 , 13 , 15 , 18] . To avoid studying these previously described laboratory adaptations , we utilized a strain , CX12311 , which contains ancestral alleles of these two genes backcrossed to an N2 background ( Fig 1B ) . To quantify the difference in egg-laying rates between CX12311 and LSJ2 , we measured egg-laying rates from hermaphrodites grown on agar plates seeded with E . coli bacteria starting from the fourth larval stage ( L4 ) and then twice a day for five days ( Fig 1C ) . Beginning the experiment with L4 animals allows us to bypass differences in growth rate and focus on the rate of sexual maturity and reproductive timing . These conditions resemble the standard laboratory conditions for culturing the N2 strain . The egg-laying rate for CX12311 was extremely low for the first time-point , reflecting the switch from spermatogenesis to oogenesis [19] . This rate increased for the next three time points , peaking at approximately seven eggs per animal per hour at the 36–48 hour time point and then decreasing until the last time point , when the majority of animals ceased reproduction ( Fig 1D ) . The initial increase likely reflects the accumulation of oocytes while the cessation reflects animals running out of sperm for self-fertilization [19] . For the initial four time points , LSJ2 laid fewer eggs than CX12311 animals ( Fig 1D ) . However , their rate continued to increase , resulting in a higher egg-laying rate starting from the 48–60 hour time point . These experiments indicate that new mutation ( s ) affecting reproductive timing have become fixed in the N2 and/or LSJ2 lineage . We also measured the total fecundity of each strain over the course of their reproductive life . Each LSJ2 hermaphrodite laid ~310 fertilized eggs , whereas the CX12311 hermaphrodites laid ~250 fertilized eggs ( Fig 1D ) . The total self-reproductive capacity of a C . elegans hermaphrodite is limited by the number of self-sperm that are created during the L4 stage , suggesting that these strains are born with a different number of self-sperm , however , we did not directly count self-sperm to confirm this . We have previously found that pheromones released by C . elegans act as an important selective pressure in animals grown in liquid axenic media , including the LSJ2 strain [8] . We wondered if impaired pheromone processing in LSJ2 could be involved in the difference in reproductive timing between CX12311 and LSJ2 as pheromones have been reported to impact brood size in certain environmental contexts . To test this hypothesis , we generated two strains containing deletions in the daf-22 gene in the CX12311 background using the CRISPR-Cas9 system . The DAF-22 protein is required for synthesizing the majority of pheromones released by C . elegans [20 , 21] . For the first four timepoints , daf-22 animals laid eggs at a rate almost indistinguishable from LSJ2 . For the next five timepoints , daf-22 animals laid eggs at a rate much lower than LSJ2 ( Fig 1D ) . As a result their total fecundity was much lower than either LSJ2 or CX12311 ( Fig 1E ) . These results are consistent with pheromones failing to stimulate egg-laying in LSJ2 for the first four timepoints . However , LSJ2 and daf-22 have different temporal patterns of egg laying , suggesting that daf-22 also affects total fecundity besides just the initial timing of egg production . In order to identify the causative genetic variants responsible for these differences , we performed quantitative trait loci ( QTL ) mapping using a panel of 94 recombinant inbred lines ( RILs ) [22] . The egg-laying rates of all RILs were assayed in replicate over the same five time-points ( Fig 2A and 2B ) . In total , over 250 , 000 eggs were counted . QTL mapping on this averaged data identified a highly significant major-effect QTL on the right arm of chromosome II ( QTLII ) that accounted for as little as 24% and as much as 75% of the overall phenotypic variation for a particular day ( Fig 2C and 2D ) . Interestingly , the effect of this QTL switched over the course of the animal’s life ( Fig 2D ) , changing its direction between day 2 and 3 ( i . e . sign-switching ) . Therefore , we identified a QTL on chromosome II with variable effect size that both decreases and increases the egg-laying rate over the entire reproductive life history of the animal . Additional QTLs of smaller effect were also identified at various timepoints on chromosomes IV , V , and X . The QTLII was mapped to a ~1 Mb region containing five genetic differences–single nucleotide variants ( SNVs ) in the introns of ctl-2 , Y53F4B . 26 , and nurf-1 , an SNV mutation in an intergenic region , and a 60 bp deletion in the 3’ coding region of nurf-1 ( Fig 3A ) . We verified this QTL by introgressing LSJ2 DNA surrounding QTLnurf-1 into CX12311 ( Fig 3A ) . The resultant near-isogenic line ( NILnurf-1 ) recapitulated the result of QTL mapping ( Fig 3B ) . We focused on the nurf-1 coding region deletion as a likely candidate for the causative variant . nurf-1 is an uncommonly complex locus encoding at least 16 isoforms that are orthologs of human BPTF . BPTF is a subunit of the NURF chromatin-remodeling complex , which recognizes multiple histone modifications on nucleosomes and recruits ISWI to remodel nearby nucleosomes ( Fig 3C ) [23 , 24] . In Drosophila , a long-form ( analogous to the a , c , l , m , and n isoforms ) and a 5’ short form ( analogous to the b , I , and k isoforms ) are known to exist [25] . However , in C . elegans and C . briggsae , additional isoforms covering the 3’ end of the nurf-1 gene have also been identified ( d , e , f , g , h , j , o , and p ) [23 , 26] . Little is known why so many isoforms are necessary for nurf-1 function and it is still controversial whether the long form even exists in nematodes [23 , 26] . The 60 bp deletion in the LSJ2 strain affects 13 out of 16 nurf-1 isoforms , removing the 3’ coding region of nurf-1 , the stop codon , and 8 bp of the 3’ UTR . These changes are predicted to replace the last 16 amino acids of the NURF-1 protein with 11 novel residues ( Fig 3C ) . Because the specific nurf-1 isoforms that are mutated in LSJ2 have not been shown to affect C . elegans reproduction , we first tested a 1078 bp deletion ( n4295 ) in the 3’ end of nurf-1 ( Fig 3C ) [23] . This strain was created in an N2 background , so we compared its egg-laying rate to N2 . This strain was nearly indistinguishable from the NILnurf-1 ( Fig 3B ) , indicating one or more of these eight isoforms regulate egg laying . We next asked whether the specific LSJ2 60 bp deletion was causal by using CRISPR/Cas9 combined with template-based repair to generate two independent allele replacement lines ( ARLnurf-1 ) carrying the LSJ2 allele of nurf-1 in the CX12311 background [27 , 28] . The egg-laying rates of these two ARLnurf-1 strains were significantly different from CX12311 on the third , fourth , and fifth time-points in a direction consistent with the QTL mapping and the NIL strain ( Fig 3B ) . However , these strains were also distinguishable from the NILnurf-1 strain , showing no significant difference with CX12311 at the first two time points and a smaller effect size than the NILnurf-1 during the last two time points . These results suggest that the 60 bp deletion is a causative genetic variant for egg-laying differences between N2 and LSJ2 , but additional causative genetic variants exist within the introgressed region ( Fig 3A ) . These causative genetic variants could potentially act through the nurf-1 gene ( such as the WBVar00601361 variant found in the nurf-1 intron ) , but additional work will be necessary to clarify their identity and role . We had previously found that the LSJ2 strain was defective for pheromone-induced entry to a diapause state called dauer [8] . Dauer is another example of a life-history trade-off in C . elegans [29] . Although dauer animals are resistant to a number of stressors and live 5–6 times longer than normal animals , this trade-off comes at the expense of reproduction . We tested the ability of nurf-1 ( n4295 ) and the ARLnurf-1 animals to enter dauer in response to crude pheromone extracts . n4295 is a previously generated deletion allele in the 3’ end of nurf-1 ( Fig 3C ) . Although N2 and CX12311 animals readily entered dauer , LSJ2 and nurf-1 mutant animals did not ( Fig 4A ) . C . elegans release a number of dauer pheromones , which are sensed and transduced by different genetic and neuronal pathways . We tested N2 , LSJ2 , and nurf-1 ( n4295 ) animals to three synthesized components of the dauer pheromone cocktail , ωC3 ( ascr#5 ) , C6-MK ( ascr#2 ) , and ΔC9 ( ascr#3 ) [30 , 31] . nurf-1 animals entered dauer in response to ωC3 but were reduced in their propensity to enter dauer in response to C6-MK and ΔC9 ( Fig 4A ) . This result indicates that the role of nurf-1 in dauer formation is selective for individual pheromones , suggesting a role in the neural circuit that senses and transduces the C6-MK and ΔC9 pheromones [32] . We next tested the role of nurf-1 in lifespan by examining the N2 , CX12311 , LSJ2 , nurf-1 ( n4295 ) , and ARLnurf-1 strains at 25°C . In these conditions , the average lifespan of CX12311 animals is approximately 12 . 2 days , and the lifespan of LSJ2 animals was extended by a few days ( 14 . 6 days ) ( Fig 4B ) . The ARLnurf-1 strain fell in between the two parental strains ( 13 . 3 days ) , indicating that nurf-1 has an effect on lifespan , but additional genetic variants between LSJ2 and N2 also contribute to lifespan differences . We also tested the N2 and nurf-1 mutant strain but found no significant difference between their lifespan . This suggests that the ancestral npr-1 allele is required for nurf-1’s role in regulating lifespan . Finally , we tested the growth rate of animals by synchronizing animals at hatching followed by video recordings of the animals at 72 hours . These videos were analyzed by custom software to identify the pixel area of the animals normalized to the N2 strain [33] ( Fig 4C and 4D ) . Animals increase their volume 100-fold over the course of these experiments . This analysis revealed that both LSJ2 and nurf-1 animals grew at a slower rate than N2 or CX12311 . From an evolutionary perspective , it is unexpected that an allele that reduces early reproductive rate could spread to fixation . While deleterious alleles can spread in populations with small bottlenecks [34] , many of the causative genetic variants that have become fixed in the LSJ2/N2 lineages have been shown to have a positive effect on fitness [14 , 16] . We tested the effect of the 60 bp deletion directly using competition experiments . First , we competed the ARLnurf-1 strain against CX12311 animals on agar plates ( i . e . the historical N2 growth conditions ) using nine experimental replicates consisting of five competition plates each . Competition plates were seeded with seven animals from each genotype . Once a week for six weeks , after food had been exhausted for approximately three days , 100 to 200 starved L1s were transferred to a new freshly seeded plate . Every two generations , DNA was isolated from the remaining animals following transfer . DNA from the five competition plates for each replicate were pooled together and genotype frequencies were determined using digital PCR . Fitness was then estimated by fitting linear curve to the data points and using ANOVA to determine its significance . These experiments indicated a clear selective advantage for the CX12311 strain ( s = 0 . 08—Fig 5 ) . By the end of the six-week experiment , only 25% of the animals carried the 60 bp deletion in nurf-1 . These experiments indicate that the nurf-1-influenced changes in life history are detrimental in standard laboratory growth conditions . Using a wild strain of C . elegans as an outgroup , we previously determined that the 60 bp deletion was fixed in the LSJ2 lineage We reasoned that the 60 bp mutation could have been advantageous in the axenic soy peptone- beef liver growth medium in which LSJ2 arose . To test this hypothesis , ARLnurf-1 animals were competed against CX12311 animals in axenic media . One hundred animals of each strain seeded into six initial cultures . Every two weeks , 1000 to 2000 animals were transferred to fresh media and DNA was extracted from the remaining animals . In these conditions , the 60 bp deletion resulted in a significant advantage for the animals ( s = 0 . 04—Fig 5 ) . These experiments suggest that the life-history changes induced by nurf-1 are advantageous in the environment in which they originated . Differential stress responses are frequently observed in strains with divergent fitness trade-offs [35] . A strain that commits resources to generate more robust but fewer offspring will typically have higher stress tolerance . By contrast , a strain that commits resources to generate a large number of offspring will have lower stress tolerance . We measured fecundity and population growth rate of the same panel of 94 RILs constructed between CX12311 and LSJ2 parents after exposure to anthelmintic compounds and heavy metals to assess whether these strains differed in their abiotic stress responses . In control conditions ( water or DMSO ) , we found a strong effect of nurf-1 on mean animal size ( Fig 6 ) . However , the effect of nurf-1 was almost completely abrogated in the presence of two anthelmintics ( albendazole and abamectin ) and two heavy metals ( arsenic and zinc ) ( Fig 6 ) . This strong gene-by-stress interaction ( S1 Fig ) suggests that variation in nurf-1 has generic effects in the presence of abiotic compounds . The N2 allele of nurf-1 promotes faster growth , but is less able to cope with environmental stressors . Unlike growth rate , the effect of nurf-1 on number of eggs laid was independent of abiotic perturbations ( S1 Fig ) . This suggests that the nurf-1 animals continue to deprioritize reproductive rate irrespective of their environment .
Our results indicate that a discrete shift in environment resulted in the evolution of multiple traits in LSJ2 animals , including reproductive timing , dauer formation , lifespan , survival , and growth rate . These traits are all classical life history trade-off traits that are indicators for how an organism distributes its resources . LSJ2 animals prioritize individual survival over reproductive speed , as they live longer , grow slower , and are less affected by various drugs and stressors at the cost of laying eggs later on in life . A priori , we did not expect LSJ2 to undergo life history changes . Retrospectively , however , these changes may be linked to the unnatural and poor nutritional value of liquid axenic media , where animals reproduce at an order of magnitude lower rate [7] . A strain of the related species C . briggsae that grew in the same media evolved similar changes to its life history traits , including growth rate and reproductive timing changes [36] . These observations are all consistent with the hypothesis that growth in this media creates selective pressure on life history traits . Although an extensive literature on life history differences among species exists , little is known about the genetic causes of these changes . We identified a beneficial 60 bp deletion in nurf-1 , which encodes an ortholog of human BPTF , as a large-effect , pleiotropic regulator of many of the LSJ2 life-history changes . BPTF is a subunit of NURF , a chromatin-remodeling complex that modifies transcription and promotes proliferation and differentiation of a number of tissues in an organism-specific manner [37] . To our knowledge , BPTF/NURF has not previously been described as a regulator of life-history traits . Mechanistically , there are a number of ways it could accomplish this regulation . For example , NURF-1/BPTF could control energy distributions–shunting energy towards survival naturally changes the remaining life history traits . However , in other organisms , these life history axes can vary independently , suggesting energy constraints aren’t sufficient to completely explain their coupling . Alternatively , the life history traits could be linked together in logical ways through concordant NURF-1/BPTF regulation of the different tissues/cells that control these traits . In this scenario , NURF-1 would act as a master regulator of life-history tradeoffs . This latter role is mainly speculative , however , and will require molecular and cellular characterization of nurf-1 function to determine how its regulation occurs . Orthologs of NURF-1 have been reported to regulate a large number of disparate traits , however , little is known about the underlying logic that link these traits together . Regulation of life history tradeoffs could be a useful lens to consider NURF-1/BPTF function in other species if its role as defined in C . elegans has been conserved throughout evolution . It is intriguing that many traits controlled by NURF-1 orthologs in other species could also be interpreted as life-history tradeoffs . For example , both C . elegans and the related nematode Caenorhabditis briggsae have independently evolved self-fertilizing hermaphroditism , which requires their gonads to produce male gametes before switching to female gamete production . Major alterations in the use of NURF-1 in the C . briggsae germline result in a dependence on nurf-1 for the sperm/oocyte decision [26] . This evolutionarily recent gain of function for nurf-1 can be seen as an effect on the timing of the conversion from male to female gametes as a life-history trait–it determines the total number of progeny that can be produced through self-fertilization at a cost of when reproduction can begin [38] . In Drosophila melanogaster , Nurf301 ( the ortholog of nurf-1 ) regulates heat shock response , hemocyte proliferation/development , spermatogenesis , oogenesis , and metamorphosis [25 , 39–41] . These traits are all life history traits–heat shock response and hemocyte production ( i . e . invertebrate immune system cells ) are energetic investments into organismal survival; spermatogenesis and oogenesis are energetic investments into reproduction; and metamorphosis profoundly influences mortality rates , resource intake and the ability to reproduce [17] . In mice , Bptf regulates thymocyte maturation [42] , the precursor to T-cells that form part of the innate and adaptive immune system that regulates individual survival . One of the unusual features of nurf-1 is the large number of isoforms it expresses . Changes in alternate splicing could be particularly relevant for the evolution of BPTF/NURF-1 biological function or new biological functions more generally . The orthologous relationship between human BPTF and C . elegans NURF-1 shows that there has been little evolutionary pressure to diversify its protein function . However , although human BPTF is expressed from a large number of transcripts ( 22 predicted by GenBank ) , no one-to-one relationship between NURF-1 and BPTF isoforms exists . This suggests that evolution has diversified NURF-1/BPTF function by creating/removing specific isoforms of the protein . Isoform-specific evolution combines features of both cis- and trans-regulation . Cellular expression of individual transcripts can be changed by evolution of its promoter region or by modifying the tissues where alternative splicing occurs . Evolution of new transcripts also functionally changes the protein by the addition or loss of protein residues . Why would nurf-1 need to evolve both ? This complexity could result from a combinatorial need of NURF-1 to regulate transcription in a number of different tissue types ( requiring cis regulatory evolution ) while simultaneously gaining or losing interactions with different transcription factors expressed in these tissues ( requiring trans regulatory evolution ) . While we have used the term NURF-1 very loosely for brevity , there are actually a large number of isoforms that are encoded by the nurf-1 locus . The LSJ2 deletion that was identified here is predicted to regulate 13 of these different isoforms . While most ( 12 of 13 ) of these isoforms contain the domains necessary for interacting with nucleosomes , many lack the canonical domain thought to be required for interactions with ATPase component of NURF responsible for remodeling nucleosomes . In fact , it is unclear in C . elegans whether the longest isoforms of nurf-1 ( a , c , k , and n ) , necessary for producing the full form of NURF complex , even exist . While work on the 5’ isoforms of nurf-1 have demonstrated a role for these isoforms in vulval development and fertility , this report identifies biological traits ( dauer , lifespan , reproductive rate and timing , and growth rate ) that are associated with the 3’ isoforms . Life history differences are often considered at the level of species . However , most life-history traits are extremely plastic over the course of the animal’s lifetime and can respond to the different environments animals encounter . Life-history plasticity has been observed in snails , for example , in response to the presence of crawfish predators [43] . Pheromones also regulate life-history tradeoffs: density pheromones induce C . elegans to enter a diapause state called dauer that prioritizes survival over reproduction , alarm pheromones sensed by cane toads modify their size at metamorphosis [44 , 45] , and sexual pheromones modify a number of male behaviors that result in prioritizing reproduction over individual survival . In C . elegans , pheromones also regulate reproductive recovery from stress and total lifespan [46 , 47] . We also found that daf-22 mutants , which are unable to synthesize and secrete pheromones , show differences in reproductive timing ( Fig 1D ) . Little is known about the signaling pathways connecting pheromones with many of these traits . We suggest that NURF-1 could mediate some or all of these effects of pheromones on life-history plasticity . In C . elegans , alternative developmental histories triggered by dauer pheromones result in a cellular memory encoded through histone modifications that regulates a number of life-history traits [48] . Interestingly , the particular down-regulated histone modifications , H3K4me3 and H4ac , are consistent with the canonical histone recognition sites of BPTF ( H3K4me3 and H4K16ac ) [24] . NURF-1/BPTF could act as a connection point between an animal’s development and current life-history traits activing via alternatively marked nucleosomes . In either case , the identification of nurf-1 represents a genetic handle to understand life history regulation .
Strains were cultivated on agar plates seeded with E . coli strain OP50 at 20°C [49] . Strains used in this study are: N2 , LSJ2 , CX12311 kyIR1 ( V , CB4856>N2 ) ; qgIR1 ( X , CB4856>N2 ) , MT13649 nurf-1 ( n4295 ) , PTM88 ( ARLnurf-1 ) nurf-1 ( kah3 ) ; kyIR1 ( V , CB4856>N2 ) ; qgIR1 ( X , CB4856>N2 ) , PTM93 ( ARLnurf-1 ) nurf-1 ( kah5 ) ; kyIR1 ( V , CB4856>N2 ) ; qgIR1 ( X , CB4856>N2 ) , PTM66 ( NILnurf-1 ) kyIR87 ( II , LSJ2>N2 ) ; kyIR1 ( V , CB4856>N2 ) RIL strains used in this study are sequentially: CX12312–CX12327 , CX12346–CX12377 , CX12381–CX12388 , CX12414–CX12437 , and CX12495-CX12510 . These strains were generated and described in a previous study [8] . All egg-laying assays were carried out at 20°C using standard 5 . 5 cm NGM plates seeded with the OP50 strain of Escherichia coli . Two OP50 concentrations were used to generate either transfer or experimental plates . A glycerol stock of OP50 was used to streak an LB plate and a single colony was cultured overnight . The overnight culture was used to inoculate 200 ml of LB for 4–6 hours of growth at 37°C with shaking . Approximately 1 ml of this culture was swirled around on an unseeded plate to generate a uniform lawn or 300 μl of OP50 was used for transfer plates . For experimental plates , the overnight OP50 culture was concentrated via centrifugation to an OD600 of 2 . 0 and this culture was used for seeding experimental plates with 70 μl aliquots . Both transfer and experimental plates were prepared the week of the assay and left at 22 . 5°C 18–24 hrs following seeding . Plates were then placed at 4°C until the day of the assay and warmed to 20°C for four hours before each time point . Nematodes were cultured at least three generations prior to the beginning of the assay . Six young adult hermaphrodite nematodes were then placed on multiple transfer plates two days before the assay and six fourth larval stage ( L4 ) nematodes were transferred to the first 70 μl experimental plate . For picking L4 worms , we identified animals with the "Christmas tree stage" vulvas , which corresponds with mid-L4 stages L4 . 4 , L4 . 5 , and L4 . 6 . This time of this transfer to the first experimental plate represents time 0 . For QTL mapping , L4 hermaphrodites from 94 RIL strains were transferred from the transfer plate to experimental plates and then transferred to 70 μl experimental plates between intervals . For the first two assays , three time points ( 0–14 , 14–20 , and 36–42 hours ) were measured . For the last three assays , five time points were measured . Laid eggs were allowed to develop to the L4 stage and placed at 4°C for counting . Egg-laying assays for Fig 3B were performed essentially the same way as QTL mapping . Ten replicates were assayed for each strain . For Fig 1D , animals were transferred directly between experimental plates . Six replicates were assayed for each strain . Significant differences between means were determined using unpaired , two-tailed t-tests assuming equal variance . The average of five egg-laying counts was used as the phenotype for five different time points in combination with 192 previously genotyped SNPs [8] . R/qtl was used to perform a one-dimensional scan using marker regression on the 192 markers [22] . The significance threshold ( p = 0 . 05 ) was determined using 1000 permutations . For Fig 2D , the plotPXG function was used to show the effect of the nurf-1 marker . The effect-size of the nurf-1 marker was estimated using fitqtl with a single QTL . We generated the ARLnurf-1 strain following the published co-conversion CRISPR method to simultaneously edit the dpy-10 gene ( as a visual marker ) along with nurf-1 using single-stranded oligonucleotidess as repair templates [27] . All sgRNAs were cloned into a subclone of pDD163 containing the U6 promoter to drive sgRNAs in the germline [28] . For the dpy-10 gene , we used the previously published sgRNA and repair oligo . For the nurf-1 gene , we designed an sgRNA to target the 5’-TTCGGATCAGCTGTTGCCAC ( TGG ) -3’ protospacer/PAM site found in the LSJ2 60 bp deletion . We used single-stranded oligonucleotide 5’-TCTATCAGAAAGCGTGTCCAGTCGGAAAGCCAGCGAACTGTCGACTCGTTGGATATCGATTCCTC TTGTTTTTTTATGTTTTTCGTAGTCACACAGTGACTTTTCACTTGTTACGTTGACAATGT -3’ as a repair construct . To drive Cas9 in the germline , we subcloned Peft-3::Cas9 from pDD162 into a separate vector . We injected 50 ng/ul Peft-3::Cas9 , 25 ng/ul dpy-10 sgRNA , 500 nM dpy-10 ( cn64 ) repair oligo , 25 ng/ul nurf-1 sgRNA , and 500 nM LSJ2 nurf-1 repair oligonucleotide into CX12311 animals . We genotyped 113 F1 roller animals by PCR using the primers 5’- ACATTATACGAAGTTATGTCGTCAAACTTTGCATTTG-3’ and 5’-CATCTTCATAATTCCAACGGAAACCAAG-3’ followed by digestion with PvuII ( a site which is removed by the 60 bp LSJ2 deletion ) . We identified a single PvuII resistant band , however , Sanger sequencing showed that this F1 animal contained a 10 bp deletion of 5’-AGCTGTTGCC-3’ replaced by 5’-GA-3’ , indicating that this lesion resulted from a NHEJ event that disrupted the PvuII site as opposed to our targeted HR from the nurf-1 oligo . We hypothesized that due to the 60 bp deletion , the flanking regions on the single-stranded oligonucleotide were not long enough to initiate homologous repair . We next generated a strain , PTM91 , containing an extrachromosomal array of the LSJ2 nurf-1 3’ region by injecting a PCR product generated using the 5’-GCAATTTGTGAACGACGTGA-3’ and 5’-CCGGTCTCGACACAATTTTT-3’ primers along with a Pelt-2::GFP co-injection marker into CX12311 animals . We injected the co-conversion injection mix described above into these animals and again singled 80 F1 roller or roller/dumpy animals and genotyped them as above . We identified two PvuII-resistant bands , which Sanger sequencing showed was due to presence of the LSJ2 60 bp deletion in both strains . These two strains were dumpy rollers ( indicating a conversion event along with a deletion event in the dpy-10 locus ) . We mated these two strains to CX12311 males to separate the nurf-1 deletions from the dpy-10 mutations . Dauer assays were performed as described previously [8] . Lifespan assays were performed with standard method at 25°C using NGM plates containing 25 μM FUdR seeded with OP50 . The animals were synchronized using alkaline-bleach to isolate embyros and raised on NGM plates at 20°C until they reached the young adult stage when they were transferred to FUdR plates at 25°C . The animal survival number was scored every two days . Animals were scored as dead when they no longer responded to gentle touch with a platinum wire . The date when the animals were placed on FUdR plate were defined at t = 0 . The survival statistical analysis was performed in JMP12 software by using the log-rank method in Kaplan-Meier survival . Animals were synchronized by allowing adults to lay eggs on an NGM plate seeded with OP50 bacteria for two hours and raised at 20°C . Three plates were created for each strain . At 48 and 72 hours , animals were recorded for one minute using a Videomach camera . Previously described tracking software was used to measure the area of each animal [33] . The average size of animals from each plate was normalized to the cumulative average size of the three N2 plates . The axenic liquid HS-YE-HLE stock media was prepared by mixing one volume of Heated Liver Extract ( HLE ) to nine volumes of HySoy-Yeast Extract ( HS-YE ) . The preparation method is modified from the following paper [7] . To make the HLE component , calf liver ( purchased from Corrina’s Corner ) was cut to 1 inch squares and left in 4°C cold room overnight for 24 hours . An equal amount of distilled water was added to the liver , which was then further broken down using a blender . Large particles were filtered out of the homogenate with Miracloth . The purified homogenate was then heated in a 60°C water bath until its temperature reached 52°C and heated for 6 minutes . At that point the homogenate was centrifuge and the supernatant further filtered with a 0 . 2 micron filter ( Nalgene ) . To prepare the HS-YE component , 40 g HySoy peptone ( Sigma P6463 ) and 10 g yeast extract ( Alfa Aesar H26769 ) was added to 1 L of water and autoclaved . The final HS-YE-HLE stock media also contained three antibiotics ( Penicillin G 100 U/mL; Streptomycin 100 ug/mL and Amphotericin B 0 . 25 ug/mLand was filtered with a 0 . 2 micron filter ( Nalgene ) . Competition assays between CX12311 and ARLnurf-1 ( PTM88 ) were performed on NGM plates and liquid HS-YE-HLE stock media . A SNV located on chromosome I at position 11583395 ( WS220 ) ( CX12311: T , ARLnurf-1: C ) was used to genotype and quantify the number of each strain in the competition experiments . In the competition assay on NGM plates seeded with OP50 bacteria , nine experimental replicates were performed . Each replicate included five independent populations . At the beginning of each assay , the animals were synchronized with alkaline-bleach and raised at 20°C until they developed to the L4 stage . Seven L4 animals of each strain were placed on forty-five 6 cm NGM plates and kept at 20°C for one week . At this point , populations from each plate were transferred to new NGM plates by cutting a 0 . 5 cm x 0 . 5 cm square of agar ( containing ~100 worms ) from the starved plate . Populations were continuously cultured in this way for five weeks . During the six weeks of culturing , genomic DNA was isolated from the 2nd , 4th and 6th week time points . The populations from five plates in each group were combined into a single Eppendorf tube and genomic DNA was isolated by using a Qiagen Gentra Puregene Kit ( cat . nos . 158667 ) following the supplementary protocol for nematodes and purified using Zymo Quick-DNA universal kit ( cat . nos . D4068 ) . In the competition assay in liquid HS-YE-HLE stock media , six experimental replicates were performed . Each replicate was cultured in a 10 mL HS-YE-HLE stock media in a cell culture flask . At the beginning of this assay , the worms were synchronized by alkaline-bleach . When the animals were hatched , 100 L1 animals from each line were transferred into 10 mL of HS-YE-HLE media and cultured at 20°C in vertical shaker . After two weeks , 1 mL of depleted culture ( containing ~2000 animals ) were transferred to a new cell culture flask container . Then , the populations were continuously cultured for another four weeks . The populations were transferred every two weeks and the populations’ genomic DNA was isolated at the 2nd , 3rd , 4th , 5th and 6th week time point by the same method described above . The proportion of ARLnurf-1 population size in competition assay was measured using Taqman analysis in Biorad QX200 digital PCR system to quantify the chromosome I 11583395 SNP frequency . Taqman probes were designed using standard software from Applied Biosystems . Genomic DNA from each time point was digested with SacI enzyme and purified with Zymo DNA Clean & Concentrator Kit ( cas . nos . D4004 ) . The concentration of fragmented genomic DNA was adjusted to 2 ng/uL by Qubit assay ( cas . nos . Q32851 ) . Digital PCR was performed followed the standard method provided by Biorad with the absolute quantification method . The proportion of ARL nurf-1 allele was calculated and the linear model and statistical analysis were carried out in R programming language . CX12311xLSJ2 RILs were assayed using a COPAS BIOSORT as described previously [50] . Abamectin ( 5 ng/mL ) and albendazole ( 12 . 5 μM ) were dissolved in DMSO , and arsenic trioxide ( 1 mM ) and zinc chloride ( 350 μM ) were dissolved in water . These treatments were paired with the respective solvent controls with a constant concentration of 1% volume-per-volume . The COPAS device outputs the number of objects , time of flight , extinction , and three different fluorescent parameters . These values were processed using a modified version of the COPASutils package [51] available on github . com/easysorter . The data were analyzed and plotted using R . | Sex and death are two fundamental concerns of each organism . These traits evolve rapidly in natural populations as animals seek to maximize their fitness in a given environment . For example , in mammals , lifespan , size , and fecundity vary over two order of magnitude . A key observation of evolutionary life history theory is the recognition that there are limited amount of resources available , which creates tradeoffs between competing life functions . By studying a domesticated strain of C . elegans , we identify a beneficial mutation that regulates a number of life history tradeoffs . This mutation affects a subunit of the NURF chromatin remodeling complex . Our work suggests that NURF is a master regulator of life history tradeoffs through epigenetic regulation , and a target of evolution . | [
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] | 2016 | Selection on a Subunit of the NURF Chromatin Remodeler Modifies Life History Traits in a Domesticated Strain of Caenorhabditis elegans |
HAP2 ( GCS1 ) is a deeply conserved sperm protein that is essential for gamete fusion . Here we use complementation assays to define major functional regions of the Arabidopsis thaliana ortholog using HAP2 ( GCS1 ) variants with modifications to regions amino ( N ) and carboxy ( C ) to its single transmembrane domain . These quantitative in vivo complementation studies show that the N-terminal region tolerates exchange with a closely related sequence , but not with a more distantly related plant sequence . In contrast , a distantly related C-terminus is functional in Arabidopsis , indicating that the primary sequence of the C-terminus is not critical . However , mutations that neutralized the charge of the C-terminus impair HAP2 ( GCS1 ) -dependent gamete fusion . Our results provide data identifying the essential functional features of this highly conserved sperm fusion protein . They suggest that the N-terminus functions by interacting with female gamete-expressed proteins and that the positively charged C-terminus may function through electrostatic interactions with the sperm plasma membrane .
The fusion of gamete plasma membranes is a critical event in fertilization , but despite the ubiquity of the process among sexually reproducing eukaryotes , no conserved mechanism for gamete fusion has been described . At least two factors contribute to our lack of mechanistic insight . First , many proteins that mediate binding and fusion of complementary gametes evolve rapidly , thereby reinforcing barriers to interspecific hybridization [1] . Second , gamete fusion is a transient event occurring between two cells , limiting the ability to observe fusion and to study it using biochemical methods . Genetic analysis in Arabidopsis ( Arabidopsis thaliana , At ) identified HAP2 ( GCS1 ) , a sperm-expressed gene that is essential for fertilization [2]–[4] . In flowering plants , two genetically identical haploid sperm are delivered by a pollen tube to female gametes that develop within an ovule . One sperm fuses with the egg to produce a zygote while the other fuses with the central cell to produce endosperm , a tissue that supports the developing embryo . Both fertilization events are required to initiate development of a seed ( reviewed in [5]–[6] ) . HAP2 ( GCS1 ) , for HAPLESS2 [2] , [4] and synonym GENERATIVE CELL SPECIFIC1 [3] , is required for both sperm fusion events occurring during double fertilization . The role of HAP2 ( GCS1 ) in fertilization may be widespread in eukaryotes as orthologs are present in several protist , animal , and plant genomes [7]–[8] . Loss of HAP2 ( GCS1 ) function in male gametes also blocks fertilization in Plasmodium berghei ( sperm affected [7] , [9] ) and Chlamydomonas reinhardtii ( Cr , minus gametes affected [7] ) , suggesting it plays a similar role at fertilization throughout eukaryotes . Key observations made in Chlamydomonas suggest a specific role for CrHAP2 ( GCS1 ) in gamete fusion [7]: ( i ) The Cr hap2 ( gcs1 ) loss-of-function mutation prevents fertilization , despite the ability of gametes to bind one another and bring opposing membranes into close proximity and ( ii ) CrHAP2 ( GCS1 ) is enriched at the tip of the minus mating projection just prior to fusion . All predicted HAP2 ( GCS1 ) orthologs share a common primary architecture . Each is divided into two regions by a single pass transmembrane domain and contains a HAP2-GCS1 domain of about 50 amino acids in the large region amino ( N ) -terminal to the transmembrane domain ( Figure 1A and Figure 2A ) . The carboxy ( C ) -terminus is enriched in charged residues that do not follow a defined sequence: histidine is dominant in flowering plants while other basic residues ( lysine , arginine ) are enriched in other species [3]–[4] , [7]–[8] . Primary sequence analysis of HAP2 ( GCS1 ) has not detected other known motifs or functional domains . We use quantitative molecular-genetic assays in Arabidopsis to characterize the major features of HAP2 ( GCS1 ) . We find that both regions of the protein are essential for function , and that these regions are under different selective pressures: Primary sequence from a closely related plant , not a distant relative , can replace the Arabidopsis N-terminus . Thus , while HAP2 ( GCS1 ) does not define species-level interactions between gametes , function of the N-terminus may be constrained by co-evolution with partner proteins expressed by female gametes . On the other hand , the Arabidopsis HAP2 ( GCS1 ) C-terminus retains function when replaced with sequence from a distantly related plant or mutated sequences , as long as positive charge is retained . Thus , net charge over the C-terminus is the critical feature of this region . These experiments thus establish essential characteristics of an ancient protein required for gamete fusion .
hap2-1 blocks the ability of sperm to participate in fertilization , but does not affect female reproduction [4] . This allele was generated by insertion of a T-DNA carrying two marker genes to facilitate analysis of segregation and transmission: ( i ) resistance to the herbicide Basta ( BastaR ) and ( ii ) β-glucuronidase ( GUS ) driven by the pollen-specific LAT52 promoter ( LAT52:GUS ) [2] , [4] . hap2-1 was identified in the quartet ( qrt1-2 ) background , a mutation that maintains male meiotic products in tetrads [10] . This feature , combined with LAT52:GUS expression in pollen , allows one to distinguish heterozygous hap2-1 ( hap2-1/+ ) pollen from wild-type ( Figure 1B–1F and Figure 2B ) . Self-fertilization of hap2-1/+ results in 50% heterozygous ( BastaR , two GUS+ to two GUS- pollen per tetrad ) and 50% wild-type plants ( Basta sensitive ( BastaS ) , GUS- pollen ) ; homozygous hap2-1 ( hap2-1/- ) plants are not recovered [2] , [4] , and thus hap2-1 transmission is distorted ( not the expected 1∶2∶1 segregation of wild type: heterozygous: homozygous mutant ) . Furthermore , pollination of wild-type females with hap2-1/+ pollen yields no progeny with the hap2-1 allele , e . g . all progeny are sired by wild-type pollen produced by the heterozygous father . Thus , hap2-1 cannot be transmitted though the male germline . We developed a system to test if coding sequence ( CDS ) variants of HAP2 ( GCS1 ) could restore male transmission of the hap2-1 allele ( Figure 1 ) . Transformation of hap2-1/+ mutants with a wild-type HAP2 ( GCS1 ) genomic clone [including 1 . 5 kb of HAP2 ( GCS1 ) promoter sequence] complemented the fertilization defect , and self-fertilization of hap2-1/+ mutants carrying this transgene produced hap2-1/- progeny ( BastaR , four GUS+ pollen per tetrad ) [4] . Pollen from these plants was also capable of transmitting hap2-1 to progeny when crossed to wild-type females , producing BastaR hap2-1/+ seedlings [4] . We transformed hap2-1/+ plants with a series of HAP2 ( GCS1 ) CDS variants under the control of the same 1 . 5 kb HAP2 ( GCS1 ) promoter sequence; each variant T-DNA construct carried a kanamycin resistance ( KanR ) gene . To track expression of CDS constructs and to differentiate between endogenous and introduced HAP2 ( GCS1 ) , we included sequences encoding short epitope tags ( V5 [11] and tetra-cysteine ( CCGPCC ) [12]; see Materials and Methods ) at the 3′ end of the variants ( Figure 1A ) . To determine if HAP2 ( GCS1 ) variants were capable of mediating gamete fusion , we generated hap2-1/+ transgenic lines that were homozygous for the CDS variant ( CDS/CDS , Figure 1 ) . These plants produce two pollen genotypes whose ability to fertilize female gametes could be directly compared: ( i ) HAP2 ( GCS1 ) , CDS ( BastaS , GUS- , KanR ) or ( ii ) hap2-1 , CDS ( BastaR , GUS+ , KanR ) . As with the genomic construct [4] , if the CDS variant encodes fully functional HAP2 ( GCS1 ) , the ability to fertilize wild-type females , and thus transmit hap2-1 , should be restored to hap2-1 sperm . Introduction of either the native CDS ( data not shown ) , or an epitope tagged version rescued fertility of hap2-1 ( Figure 2C–2E , top row , and Figure S1 ) . In both transgenic lines analyzed , hap2-1/- plants were recovered following self-fertilization , and segregation was restored to ∼1∶2∶1 ( 25% wild-type , 50% hap2-1/+ , 25% hap2-1/- , Figure 2D ) . When these lines were used to pollinate male sterile1 ( ms1 ) females , hap2-1 was inherited ( Figure 2E and Figure S1 ) , indicating complete or nearly complete complementation of hap2-1 by the epitope-tagged , native Arabidopsis HAP2 ( GCS1 ) CDS . These control experiments demonstrated that the addition of C-terminal epitope tags did not disrupt the function of the HAP2 ( GCS1 ) CDS and that expressing the HAP2 ( GCS1 ) CDS from the HAP2 ( GCS1 ) promoter resulted in expression of functional HAP2 ( GCS1 ) protein . We first asked if the regions N- or C-terminal to the HAP2 ( GCS1 ) transmembrane domain were essential for HAP2 ( GCS1 ) function . The amino acids encoded by exons 2-15 ( amino acid residues 62–541 , Figure 2A ) were deleted , retaining exon 1 and its signal peptide to ensure that the protein product was properly directed to the secretory pathway ( •AtC , Figure 2C ) . In a second construct , we directly fused epitope tags to the end of the transmembrane domain to test if the C-terminus was essential ( AtN• , Figure 2C ) . None of the 24 primary transformants established for either variant segregated >50% BastaR seedlings , produced hap2-1/- plants , or restored normal segregation among the progeny of self-fertilization ( Figure 2D and Figure S1 ) . Further , hap2-1/+ pollen did not produce BastaR progeny when crossed to ms1 ( Figure 2E and Figure S1 ) . Epitope tag sequences were detected in floral mRNA extracted from AtN• or •AtC lines , and the abundance of HAP2 ( GCS1 ) mRNA was higher in these flowers than in hap2-1/+ flowers ( Figure S2 ) , suggesting that failure of •AtC or AtN• variants to rescue hap2-1 was not due to lack of construct expression . Thus , the two regions of HAP2 ( GCS1 ) that lie on either side of the transmembrane domain are essential for function . We next asked if replacement of the major regions of Arabidopsis HAP2 ( GCS1 ) with sequences from plant orthologs rescued hap2-1 . We chose rice ( Oryza sativa , Os ) as a representative monocot sequence; monocots and dicots diverged at least 200 million years ago [13] . OsHAP2 ( GCS1 ) is 59% identical with Arabidopsis in the N-terminal region and 37% identical at the C-terminus [4] ( Figure S3 ) . Expression of the OsHAP2 ( GCS1 ) CDS from the AtHAP2 ( GCS1 ) promoter failed to rescue the Arabidopsis hap2-1 fertilization defect ( not shown ) . To ensure that the rice protein was properly expressed and localized in Arabidopsis sperm , we replaced Arabidopsis exons 2-15 and the Arabidopsis C-terminus with the orthologous rice sequences to maintain the Arabidopsis signal sequence and transmembrane domain ( OsN•OsC , Figure 2C and Figure S1 ) . This exchange also failed to rescue the hap2-1 defect ( Figure 2D and 2E and Figure S1 ) . In contrast , a chimera consisting of the Arabidopsis N-terminal region and the rice C-terminal region was fully functional ( AtN•OsC , Figure 2C–2E ) . Surprisingly , the reciprocal variant made by exchanging Arabidopsis exons 2–15 with the more conserved rice N-terminal sequence , was not functional ( OsN•AtC , Figure 2C–2E and Figure S1 ) . However , a similar chimera made with sequence from Sisymbrium irio ( Sisymbrium , Si , 89% identical N-terminus , Figure S3 ) , a closely related member of the same family as Arabidopsis ( Brassicaceae [14] ) , did complement hap2-1 ( SiN•AtC , Figure 2C–2E and Figure S1 ) . This result suggests that the failure of OsN•AtC to rescue hap2-1 was a consequence of primary sequence divergence . Thus , conservation of primary amino acid sequence is essential for proper function of the N-terminus , but not the C-terminus . A Sisymbrium N-terminus / rice C-terminus chimera was not functional ( SiN•OsC , Figure 2C–2E and Figure S1 ) even though each of these regions can function when paired with the complementary Arabidopsis sequence . This result suggests that the Sisymbrium N-terminus and the rice C-terminus have reduced function compared to their Arabidopsis counterparts , and that this hybrid CDS produces a non-functional protein . The ability of the AtN•OsC chimera to rescue hap2-1 implies that the greater sequence diversity in the C-terminus compared to the N-terminus [3]–[4] , [7] may be a consequence of evolutionary drift rather than the influence of positive selection , which can also produce such primary sequence diversity [1] . The drift hypothesis is further supported by the observation that the C-terminal enrichment in histidine residues is so far limited to flowering plants [3]–[4] , [7]–[8] . Thus , localized positive charge at the C-terminus of HAP2 ( GCS1 ) may be functionally more important than primary sequence . We dissected the Arabidopsis HAP2 ( GCS1 ) C-terminus to determine what features were required for function . Alignments of flowering plant C-termini representing dicots and monocots revealed a run of 13 conserved amino acids immediately after the predicted transmembrane domain followed by three histidine-rich domains . The longest histidine-rich stretch is adjacent to the transmembrane domain , and has an average pI of 12 . 5 ( Figure 3A ) . A variant composed of the complete amino terminus plus the conserved 13 amino acids was not functional ( AtN•+13 , Figure 3B–3E and Figure S1 ) . However , extending the C-terminus to include the first histidine-rich domain ( H1 ) resulted in a fully functional variant ( AtN•AtC mut Δ , Figure 3D and 3E and Figure S1 ) . Replacement of all histidines in this truncated version with other polar , charged amino acids ( arginine and lysine ) also resulted in a variant that complemented hap2-1 ( AtN•AtC mut +Δ , pI = 11 . 4 , Figure 3B–3E and Figure S1 ) . In contrast , replacing histidines with nonpolar residues ( glycine and alanine ) significantly impaired the function of HAP2 ( GCS1 ) ( AtN•AtC mut øΔ , pI = 12 . 2 , Figure 3B–3E and Figure S1 ) . When this neutralized domain was extended to include the downstream histidine-rich domains H2 and H3 , function was restored ( AtN•AtC mut ø , pI = 11 . 1 , the same as the endogenous sequence; Figure 3B–3E and Figure S1 ) . Thus , a hypomorph of HAP2 ( GCS1 ) can be made by neutralizing the C-terminus with nonpolar residues . We observed the following trend among the C-terminal variants tested . Complete removal of the C-terminus ( AtN• ) or histidine-rich region ( AtN•+13 ) abrogates HAP2 ( GCS1 ) function . C-termini consisting of the endogenous H1 or positively charged H1 variants are fully functional . However , substituting nonpolar residues for histidine in H1 domain generates a minimally functional protein , yielding only 2–4% hap2-1/- progeny from self-fertilization and 9–15% transmission of the hap2-1 allele in crosses to ms1 females ( Figure 3E and Figure S1 ) . We further characterized rare AtN•AtC mut øΔ , hap2-1/- plants to understand the effect of the nonpolar C-terminus on HAP2 ( GCS1 ) function . Two sperm were present in AtN•AtC mut øΔ , hap2-1 pollen grains ( 97–99% , n>500 per line ) , indicating gametophyte development was normal . Furthermore , AtN•AtC mut øΔ , hap2-1 pollen tubes were able to target ovules and deliver sperm , as judged by counting the number of ovules that received LAT52:GUS activity 7 . 5 hours after manual self-pollination ( Figure 4A and 4B ) . Female function was not affected in AtN•AtC mut øΔ , hap2-1/- lines , and full seed-set was obtained when pistils were pollinated with qrt1-2 pollen ( Figure 4C ) . However , when AtN•AtC mut øΔ , hap2-1/- plants were allowed to self-fertilize , only four to seven seeds formed in each silique ( ∼10% , assuming an average of 50 seeds per normal silique; Figure 4C ) . The finding that AtN•AtC mut øΔ , hap2-1 sperm were being released in nearly all ovules , yet seed formation was dramatically reduced , suggested that the HAP2 ( GCS1 ) hypomorph specifically disrupted fertilization . Analysis of embryo and endosperm development four days after self-pollination of AtN•AtC mut øΔ , hap2-1/- plants revealed normal development in 2–8% of ovules ( Figure 5A and 5B ) , consistent with the number of normal seeds observed after self-fertilization ( Figure 4C ) . We also found that 18–50% of ovules remained unfertilized ( Figure 5A and 5B ) , consistent with lack of HAP2 ( GCS1 ) function . In addition , we observed a significant number of ovules that contained either an embryo or endosperm , but not both products of double fertilization . Single fertilization events were not observed when qrt1-2 pollen was used to pollinate AtN•AtC mut øΔ , hap2-1/- pistils ( Figure 5B ) . Analysis of ovule development in ms1 pistils pollinated with AtN•AtC mut øΔ , hap2-1 pollen two days after pollination also yielded significant numbers of unfertilized and singly fertilized ovules ( Figure 5C and 5D ) . When ms1 pistils were pollinated with qrt1-2 , hap2-1/+ , or hap2-1/- carrying the functional AtN•AtC CDS , however , no single fertilization events were observed . About 25% of the ovules in pistils pollinated with hap2-1/+ pollen remain unfertilized ( Figure 5D ) , as previously reported [4] . These data suggest that neutralizing HAP2 ( GCS1 ) C-terminal charge crippled function . In the majority of cases , neither sperm was capable of fusing with the egg or central cell ( unfertilized , Figure 5 ) . However , in a significant number of ovules , HAP2 ( GCS1 ) function dropped below a critical threshold in only one of the two sperm , producing single fertilization events ( embryo-only , endosperm-only , Figure 5 ) . These results are consistent with the conclusion that AtN•AtC mut øΔ represents a hypomorph of HAP2 ( GCS1 ) .
In vivo analysis of HAP2 ( GCS1 ) variants has defined two regions that play distinct roles during HAP2 ( GSC1 ) -mediated double fertilization . The protein can be divided into N- and C-terminal regions based on the position of the transmembrane domain . Both regions are essential for function , but different evolutionary constraints are driving their roles in fertilization . We propose that an extracellular orientation of the N-terminus allows this region to regulate gamete fusion by its interaction with factors on the egg or central cell . This organization is consistent with Hidden Markof Modeling ( www . cbs . dtu . dk/services/TMHMM-2 . 0/ ) ; with the invariant conservation of cysteine residues within the HAP2-GCS1 domain that are predicted to participate in disulfide bonding in an extracellular environment; and with the successful use of N-terminal epitopes to produce antibodies that block Plasmodium reproduction [15] . The conserved HAP2-GCS1 domain could , for example , interact with another membrane-bound protein on female gametes facilitating the juxtaposition of the two plasma membranes . Our analysis of interspecific HAP2 ( GCS1 ) chimeras is consistent with an extracellular orientation of the N-terminus . Replacement of the Arabidopsis N-terminus with that of a closely related species ( Sisymbrium , 89% identical ) generated a HAP2 ( GCS1 ) variant capable of mediating fusion with Arabidopsis female gametes , but a variant generated with a distantly related sequence failed ( rice , 59% identical ) . These data are consistent with the hypothesis that the egg and central cell express a protein that interacts with HAP2 ( GCS1 ) to mediate fusion , and that this protein:protein interaction fails beyond a certain level of sequence divergence in the HAP2 ( GCS1 ) N-terminal domain . Our data also show that HAP2 ( GCS1 ) does not contribute to a species level barrier to hybridization . Wind and/or animals indiscriminately pollinate many flowering plant species , so it is important to consider mechanisms that limit hybridization . In some organisms , protein:protein interactions essential for complementary gamete binding and fusion are rapidly co-evolving to enhance reproductive isolation of one species from another [1] , [16] . We observe that the N-terminus of Sisymbrium , but not rice HAP2 ( GCS1 ) , can mediate fertilization with Arabidopsis female gametes . Arabidopsis and Sisymbrium are in the Brassica family , but belong to distinct tribes [14] . Thus , our data suggest that Arabidopsis female gametes can distinguish between the N-terminal sequences of HAP2 ( GCS1 ) from Arabidopsis and distantly related rice , but cannot discriminate Arabidopsis from closely related Sisymbrium . The recent finding that pollen tubes are attracted to ovules by small proteins with species-specific activity [17] supports a model that barriers prior to gamete-gamete interaction account for species-level discrimination in flowering plants , potentially leaving the proteins involved in gamete-gamete interactions to evolve without diversifying selection . Positive charge , not primary amino acid sequence , is the C-terminal characteristic conserved among HAP2 ( GCS1 ) orthologs and our data show that positive charge is required for function . Unlike the protein:protein interactions proposed for the N-terminus , the intracellular C-terminus may be functioning through electrostatic interactions with negatively charged molecules ( e . g . the inner face of the plasma membrane ) that favor membrane fusion . Positively charged domains located on the intracellular domain of fusion-associated small transmembrane ( FAST ) proteins have been implicated in fusion of host cells by non-enveloped viruses [18] . Flowering plant C-termini are enriched in histidine whereas other positively charged amino acids ( arginine and lysine ) are prevalent in other orthologs [4] , [7]–[8] , suggesting that selection for one class of charged amino acids over another has shaped the evolution of HAP2 ( GCS1 ) in different eukaryotes . These three positively charged amino acids were functionally interchangeable in our Arabidopsis experiments . In nature , however , differences in the composition of the C-terminal domain may have been selected to meet the unique demands of the reproductive systems that use HAP2 ( GCS1 ) . Under physiologic pH ( e . g . pH 5–7 ) , histidine exists in either a protonated or neutral form ( pKa = 6 . 08 ) whereas lysine ( pKa = 10 . 5 ) and arginine ( pKa = 12 . 0 ) are always protonated . Perhaps the difference in sperm delivery mechanisms between flowering plants and other eukaryotes selected for the bimodal charge state of histidine . Flowering plant sperm develop within the pollen cytoplasm and are delivered to the ovule by a pollen tube . hap2-1 pollen tubes have a reduced ability to target ovules compared to wild type , suggesting that in flowering plants , HAP2 ( GCS1 ) may have a role in pollen tube guidance that is distinct from its essential role in gamete fusion [4] . Future experiments will test these hypotheses by determining if HAP2 ( GCS1 ) variants with modified C-termini can complement the pollen tube guidance defect observed when hap2-1 pollen tubes compete with wild-type pollen tubes for access to ovules . Pollen tubes burst upon arrival at the ovule , exposing sperm to the extracellular environment . It will be interesting to determine if this change in environment results in a drop in sperm pH that activates HAP2 ( GCS1 ) function . hap2-1 sperm expressing a HAP2 ( GCS1 ) variant with a neutralized C-terminus ( AtN•AtC mut øΔ ) had significantly reduced fertility . Double fertilization occurred in only ∼7% of the ovules we analyzed , while many ovules remained unfertilized ( ∼40% ) . A large portion of the ovules contained products of single fertilization events ( ∼23% embryo-only , 8% endosperm-only ) that fail to complete seed development . These results highlight a unique advantage of flowering plants for the study of gamete fusion: the outcomes of two distinct fertilization events , both requiring HAP2 ( GCS1 ) function , can be observed independently . This situation provides a sensitive means to detect reduced fusion efficiency . We consistently observed fertilization of only one female gamete when two hap2-1 sperm expressing the AtN•AtC mut øΔ HAP2 ( GCS1 ) variant were delivered to an ovule , specifically detecting more single fertilizations with the egg ( embryo-only ) than the central cell ( endosperm-only ) . This suggests that sperm:central cell fusion may require more HAP2 ( GCS1 ) activity or that central cell fusion is particularly sensitive to the C-terminal charge of HAP2 ( GCS1 ) . All evidence to date indicates that HAP2 ( GCS1 ) has an essential role in fertilization [2]-[4] , [7] , [9] , [15] , but its exact function remains unknown . Observations made in Chlamydomonas suggest it is required for gamete fusion because gamete attraction and binding/juxtaposition of membranes are normal in HAP2 ( GCS1 ) loss-of-function minus gametes , yet membranes fail to fuse [7] . One hypothesis is that HAP2 ( GCS1 ) directly catalyzes membrane fusion [19] . While HAP2 ( GCS1 ) does not share primary sequence with known fusogenic proteins , it shares features with the FAST proteins of non-enveloped viruses . FAST proteins have a single transmembrane domain , a conserved , extracellular N-terminus and a variable C-terminus that is positively charged [18] . A cell expressing FAST proteins can fuse with a non-expressing neighboring cell [18] , [20] , so like HAP2 ( GCS1 ) , the requirement for FAST proteins in fusion is asymmetric . Thus , by virtue of their common attributes , HAP2 ( GCS1 ) and FAST proteins may use a similar mechanism to catalyze membrane fusion . We have mapped the key domains of HAP2 ( GCS1 ) and propose a model in which the N-terminus functions by interacting with female gamete-expressed proteins and the C-terminus is required to interact with the plasma membrane through its positive charge . By analogy to known fusogenic proteins , we propose that these interactions bring gamete membranes into close proximity , destabilize the phospholipid bilayer , and generate membrane structures favoring their fusion [19] , [21]–[23] . Future studies designed to directly assess the ability of HAP2 ( GCS1 ) to catalyze membrane fusion will be required to test this model and to elucidate the biochemical function of this ancient reproductive protein .
All seeds were plated onto solid Murashige and Skoog ( MS ) medium ( MP Biomedicals LLC , Solon , OH , USA ) supplemented with 0 . 5% sucrose containing 25 µg/mL glufosinate ammonium ( Basta; Sigma Aldrich/Riedel-de Haën , St . Louis , MO , USA ) and/or 50 µg/mL kanamycin sulfate ( Sigma-Aldrich , St . Louis , MO , USA ) . Seedlings were transplanted to sterile 2MIX potting medium ( Conrad Fafard Incorporated , Agawam , MA , USA ) and grown at 20°C , 16 day/8 night hour light cycle in a GCW30 walk-in Arabidopsis chamber ( Environmental Growth Changes , Chagrin Falls , OH , USA ) at 50–60% humidity . Plants were bottom-watered with 0 . 5X 15-5-15 ( N-P-K ) Peters Professional fertilizer ( The Scotts Company , Marysville , OH , USA ) as needed . Chimeric constructs were made using a modified Arabidopsis HAP2 ( GCS1 ) CDS . Mutations were made in the CDS to eliminate the endogenous EcoRI site at position 71 ( ‘A’ of the initiating methionine codon of A thaliana is position 1 ) , to create a second BamH I site at position 1618 that complements the endogenous BamH I site at 178 , and to create a Bmt I site at position 1740 . Each directed mutation was made using the QuickChange mutagenesis protocol ( Stratagene/Agilent Technologies , Santa Clara , CA , USA ) . Additional changes and sequence swaps were introduced through linker primers that contain both appropriate restriction sites and new sequences . All CDS variants were subcloned into a custom vector based on the pTAT backbone [24] that contains sequence encoding tandem V5 [11] and tetra-cysteine ( CCGPCC ) [12] epitope tags downstream of the multiple cloning site . The tagged CDS was then moved into pCamHap2 , a variant of pCambia2300 ( Genbank: AF234315; [25] , containing ∼1 . 5 kb of the endogenous Arabidopsis HAP2 ( GCS1 ) promoter [4] and 19S terminator flanking a modified multiple cloning site ( Figure 1 ) . Each recombinant pCamHap2 T-DNA plasmid was transformed into Agrobacterium strain GV3101 [26] and resultant colonies were expanded for floral dipping [27] . T1 plants were selected on MS plates containing both Basta and kanamyacin , but subsequent generations were selected on either Basta or kanamyacin ( Figure 1 ) . Fifteen to twenty-four T1 plants were screened , and at least 2 lines were selected for further analysis with ∼66% BastaR ( expected full rescue in T2 plants ) . In cases where complementation failed and no lines resulted in >50% BastaR , lines with the highest percentage BastaR were analyzed . Transgenic lines with a single insertion of the CDS construct were selected based on kanR data ( expect 75–83% kanR ) . Stage 12 flowers or pistils dissected 7 . 5 hour after manual pollination were fixed and stained for GUS according to previously published methods [2] , [4] . Stage 12–14 flowers were collected , frozen in liquid nitrogen , and stored at −80°C until needed . RNA was isolated from 25–50 flowers per line using Qiagen RNA Mini columns ( Qiagen Corporation , Valencia , CA , USA ) , including the optional on-column DNase treatment . Complementary first strand DNA was synthesized from 1 µg of total RNA with random hexamers and poly dT primers using the TaqMan kit ( Applied Biosystems , Foster City , CA , USA ) . One fortieth of each reverse transcription reaction was used per 25 µL quantitative real-time PCR ( qPCR ) replicate . qPCR was completed on a 7300 Real-Time PCR System ( Applied Biosystems , Foster City , CA , USA ) using Platinum Taq SYBR Green Mix with ROX ( Invitrogen Corporation , Carlsbad , CA , USA ) . Amplification was quantified over 40 cycles of 95°C , 0∶15 denaturation and 60°C , 2∶30 extension , and amplicons were evaluated with a standard dissociation step . Primers for the HAP2 ( GCS1 ) transmembrane domain ( F = 5′- TCCAACAAATGCTCGAGTTTC; R = 5′- ATTGGGAAGAGAGCGAGGAG; 101 bp ) , H3 . 3 ( At1g19890; F = 5′- ATTGCCTTTCCAACGACTTG; R = 5′- AACAACCCCACCAAGTATGC; 120 bp ) and the exogenous V5C4 dual epitope ( F = 5′- CCTAACCCTCTCCTCGGTCT; R = 5′- TCCCTTATCGGGAAACTACTCA ) were used at a final concentration of 100 nM . Ct values of triplicate reactions were averaged per sample , normalized to sperm-expressed histone H3 . 3 transcript [28]–[29] , and compared to the expression levels in hap2-1/+ flowers ( transmembrane primers ) or presented without fold-change ratios ( V5C4 epitope primers ) . This difference in data presentation is due to the nature of the targets of each primer set: The transmembrane primers ( TM ) amplify the same sequence from both endogenous HAP2 ( GCS1 ) and CDS transcripts . This primer set thus allows us to quantify how much more HAP2 ( GCS1 ) variant mRNA is present compared to hap2-1/+ . The epitope tag primers ( V5C4 ) only recognize the CDS transgene ( Figure S2D ) , thus only a normalized value may be presented against a similar amplification from plants that lack this tag . Pistils were dissected 48 ( ms1 crosses ) or 96 hours ( self-pollinated pistils ) after manual pollination , and prepared for analysis by chloral hydrate clearing [30] . The two-tailed Student's t-test was used to evaluate differences in transmission of hap2-1 . Significance was assigned based on p-values <10−5 . | Recent studies suggest that HAP2 ( GCS1 ) is a deeply conserved protein required for gamete membrane fusion , a critical yet poorly understood step in sexual reproduction . HAP2 ( GCS1 ) is present in many plant , protist , and animal genomes , and has been shown to be essential for fertilization in Arabidopsis , Chlamydomonas , and Plasmodium . The loss-of-function phenotype in Chlamydomonas suggests a direct role in gamete plasma membrane fusion . HAP2 ( GCS1 ) has no known functional domains , making it difficult to predict how it contributes to gamete fusion . We set out to map the critical features of this protein by testing a series of deletions , substitutions , and interspecific chimeras for their ability to rescue the hap2-1 fertilization defect in Arabidopsis . We found that the N-terminus does not tolerate sequence divergence , but the histidine-rich C-terminus does . We propose that the N-terminus of HAP2 ( GCS1 ) functions in part by interacting with proteins on the surface of female gametes . The key feature of the C-terminus is positive charge , a characteristic that could favor interactions with the plasma membrane that promote membrane fusion . Our studies provide a description of HAP2 ( GCS1 ) functional domains and provide an important framework for defining the role of this essential component of a conserved reproductive mechanism . | [
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] | 2010 | HAP2(GCS1)-Dependent Gamete Fusion Requires a Positively Charged Carboxy-Terminal Domain |
Rabies is invariably a fatal disease . Appropriate wound treatment and prompt rabies post-exposure prophylaxis ( PEP ) are of great importance to rabies prevention . The objective of this study was to investigate the prevalence and influencing factors of improper wound treatment and delay of rabies PEP after an animal bite in Wuhan , China . This cross-sectional study was conducted among animal bite victims visiting rabies prevention clinics ( RPCs ) . We selected respondents by a multistage sampling technique . A face-to-face interview was conducted to investigate whether the wound was treated properly and the time disparity between injury and attendance to the RPCs . Determinants of improper wound treatment and delay of rabies PEP were identified by a stepwise multivariate logistic regression analysis . In total , 1 , 015 animal bite victims ( 564 women and 451 men ) responded to the questionnaire , and the response rate was 93 . 98% . Overall , 81 . 2% of animal bite victims treated their wounds improperly after suspected rabies exposure , and 35 . 3% of animal bite victims delayed the initiation of PEP . Males ( OR = 1 . 871 , 95% CI: 1 . 318–2 . 656 ) , residents without college education ( OR = 1 . 698 , 95% CI: 1 . 203–2 . 396 ) , participants liking to play with animals ( OR = 1 . 554 , 95% CI: 1 . 089–2 . 216 ) , and people who knew the fatality of rabies ( OR = 1 . 577 , 95% CI: 1 . 096–2 . 270 ) , were more likely to treat wounds improperly after an animal bite . Patients aged 15–44 years ( OR = 2 . 324 , 95% CI: 1 . 457–3 . 707 ) , who were bitten or scratched by a domestic animal ( OR = 1 . 696 , 95% CI: 1 . 103–2 . 608 ) and people who knew the incubation period of rabies ( OR = 1 . 844 , 95% CI: 1 . 279–2 . 659 ) were inclined to delay the initiation of PEP . Our investigation shows that improper wound treatment and delayed PEP is common among animal bite victims , although RPCs is in close proximity and PEP is affordable . The lack of knowledge and poor awareness might be the main reason for improper PEP . Educational programs and awareness raising campaigns should be a priority to prevent rabies , especially targeting males , the less educated and those aged 15–44 years .
Rabies is a fatal infectious disease , which causes severe neurological symptoms that unavoidably result in death . Although human rabies is currently untreatable [1] , appropriate post-exposure prophylaxis ( PEP ) can entirely prevent rabies [2 , 3] . Such PEP , which consists of local treatment of the wound , followed by vaccine ( with or without rabies immune globulin [RIG] depending upon the type of exposure ) should be initiated immediately after a suspected rabid bite . Recommended first-aid procedures include immediate and thorough flushing and washing of the wound for a minimum of 15 minutes with soap and water , as well as disinfecting the wound with detergent or other substances of proven lethal effect on the rabies virus . Appropriate wound cleansing and disinfection can prevent one-third of rabies infections [4–6] . Modern cell-culture vaccines utilized in combination with RIG are nearly 100% effective in preventing human deaths if inoculated promptly to rabies virus-exposed victims following appropriate wound management [7] . Unfortunately , it is inexcusable that more than 70 , 000 people die from rabies annually all over the world [8] . A growing body of research has shown that appropriate and prompt PEP are not well implemented by exposed victims in rabies endemic countries . Kabete [9] reported that only 7% of animal bite victims in Ethiopia washed the wound with soap and water as first aid , with only 53% of victims seeking PEP within the first 24 hours after the bite . A similarly low proportion of wound treatment has been reported in India , with 41% of animal injury victims initiating PEP within 48 hours [10 , 11] . Moreover , only 37 . 2% of animal bite cases in Iran received timely PEP ( less than 6 hours ) [12] . Gender [12] , type of animal [12] and injury status [12] were associated with delay of initiation on PEP . The main reasons for delay of PEP included unaffordability of rabies vaccine and RIG [10 , 13] , shortage of vaccines [14] , long distance to the vaccination center [12 , 15] , lack of RPCs and shortage of medical staff [14] . Such improper wound care and delayed PEP can result in a high incidence of rabies-associated mortality [16 , 17] . Most studies reported that human rabies cases were not treated with proper wound care , and few of them received prompt PEP [18 , 19] . The odds of suffering from rabies following exposure were therefore significantly higher for those who did not receive prompt PEP ( OR = 17 . 33 , 95% CI: 6 . 39–60 . 83 ) [16] . Inadequate wound care is one of the most commonly encountered causes of PEP failure [6] . China is the world’s largest producer and consumer of rabies vaccine , and it is ranked second in the world for the number of reported rabies cases [20] . From 1960 to 2014 , China had reported a total of 120 , 913 human rabies cases , with a yearly average of 2 , 198 [21] . The number of domestic dogs and cats in China reached 150 million during 2013 [22] , and it has been increasing by 10% yearly [23] . According to the statistics provided by the Ministry of Public Health of China in 2009 , it was estimated that more than 40 million people were bitten or scratched annually in China . China’s high prevalence of animal bites makes rabies prevention an essential health priority . However , existing studies on the implementation of rabies PEP are mainly based on India [10] and African countries [16 , 24] , with related factors mostly being unaffordability and inaccessibility of the rabies vaccine . Luckily , effective anti-rabies biologics are available and affordable for Chinese animal bite victims . Hence , the above factors might not have the same influence on Chinese animal bite victims . A community-based study in Bhutan , where rabies PEP is free , showed that a knowledge gap might be the reason for an absence of PEP [25] . An examination on the level of rabies knowledge among rabies virus exposure victims may help in designing an appropriate and effective rabies prevention program for the public . To bridge this data gap , the present study focused on PEP of animal bite victims . To our knowledge , this is the first reported study to identify potential risk factors for improper wound treatment and delayed PEP in China . In this study , we attempted to provide information on the determinants of improper and delayed PEP among animal bite victims , and to develop a practical and effective rabies prevention strategy by knowledge dissemination and raising awareness .
The present study was carried out between March 1 and May 31 2016 in Wuhan city , which is one of the seven biggest cities in China , with a resident population of 10 . 6 million . It is also one of the five largest pet cities in China , with more than 130 , 000 domestic animals [23 , 26] , most of which are dogs . The Wuhan Centers for Disease Prevention and Control reported that dogs injured more than 60 , 000 people yearly , and the annual consumption of rabies vaccine was more than 100 , 000 regimens . The Research Ethics Committee in Tongji Medical College of Huazhong University of Science and Technology approved the study . The methods of the present study were implemented in accordance with the approved protocols . All participants read the purpose statement of the investigation and signed informed consents . Written informed consent was attained from all the guardians of minors ( under 18 years old ) after an explanation of the study purpose . The present study was carried out in accordance with the approved protocol . All data were anonymized and handled confidentially . A multistage sampling technique was used to select participants . Of the 15 districts in Wuhan city , three were selected by simple random sampling . Within each district , two RPCs were randomly selected and 180 eligible respondents were interviewed in each RPC . The last stage of selection of respondents within the clusters was non-random . As we know , cluster sampling is a method which could be used in the following situations: the population is concentrated in "natural" clusters ( communities , schools , hospitals , etc . ) or constructing a complete list of population elements is difficult . In the present study , as served by the same public health sector , the individuals in the same cluster share similar socio-demographic characteristic and knowledge of rabies . It is also hard to construct complete frames of animal bite victims . Therefore , cluster sampling is a suitable sampling method for our study . Of the 1 , 080 animal bite victims approached , 65 individuals did not complete the questionnaire and a total of 1 , 015 participants were interviewed ( response rate of 93 . 98% ) by experienced survey interviewers over a period of three months between March and May 2016 . If a participant was younger than 15 years old , the guardian who accompanied the minor to the RPC was asked to complete the questionnaire instead . The investigation was organized and coordinated by Huazhong University of Science and Technology and Wuhan Association of Community Health . According to the study protocol , Huazhong University of Science and Technology offered training to junior investigators who conducted the survey on animal bite victims seeking medical care in RPCs . The senior investigators checked the collected questionnaires daily to perform quality control . Data were entered double-blindly into the database by two different researchers using EpiData 3 . 0 to guarantee accuracy . The two dependent variables were: wound treatment is proper or wound treatment is improper; and the prompt initiation of PEP or the delay of initiation on PEP . We enquired from respondents on what they did after animal bite . They were asked whether they squeezed the wound , cleaned the wound with water only , cleaned the wound with soap and water , disinfected the wound with detergent , bandaged the wound , did nothing , or took other actions . Response options were as follows: 1 = “squeezed the wound” , 2 = “flushed and cleaned the wound with water only” , 3 = “flushed and cleaned the wound with soap and water” , 4 = “disinfected the wound with detergent” , 5 = “bandaged the wound” , 6 = “did nothing” , 7 = “took other actions” . This variable was recorded so that 0 = “proper wound treatment ( flushed and cleaned with soap and water or water only , as well as disinfected the wound with detergent ) ” , and 1 = “improper wound treatment” . Refused ( n = 53 ) responses were excluded . We investigated the time of injury and visiting time among the respondents . For the purpose of this study , a delay in initiation of PEP was defined as initiation of PEP more than 24 hours after potential rabies virus exposure . The variable was coded as follows: 0 = “prompt PEP” , 1 = “delay of initiation on PEP” . Refused ( n = 4 ) response were excluded . Results were analyzed to identify the distribution and ratio for each item . The chi-square test was used to determine whether there were significant differences for categorical variables . An univariate analysis was conducted for each factor using a logistic regression model . The factors analyzed were those that affected wound treatment and initiation of PEP: demographic variables , animal injury history and knowledge of rabies . Wound treatment and initiation of PEP were dependent variables . In this analysis , the results were adjusted for affordability ( family income per month ) and accessibility ( the time to the nearest RPC ) . Then , multivariate analysis was performed using a forward stepwise logistic regression model including independent variables for wound treatment and initiation of PEP . SPSS Ver . 21 . 0 ( IBM Corp , Armonk , NY , USA ) was used for all analyses . For all comparisons , differences were tested with two-tailed tests and P values less than 0 . 05 were considered statistically significant .
A total of 1 , 015 victims of animal-bites were investigated . Two thirds of respondents ( 66 . 6% ) could have an access to the RPC within 30 minutes , and nearly all victims ( 96 . 8% ) could visit the RPC within 90 minutes , while the remaining 3 . 2% of participants spent more than 90 minutes to reach the RPC . The main reason for such a long time to seek medical care was that victims did not know the clinics in their communities could supply rabies vaccine . Twenty-one ( 65 . 6% ) of the victims who did not know the nearest clinics had vaccine delayed the initiation on PEP . These data indicated that the rabies vaccine is accessible for animal bite victims . The physician categorized the animal bite wounds for further management as Category I ( 3 . 3% ) , Category II ( 41 . 1% ) and Category III ( 55 . 6% ) according to the WHO classification . Table 1 shows characteristics of the 1 , 015 animal bite victims attending the RPCs . Overall , 81 . 2% of the animal bite victims did not treat their wounds properly , with only 178 ( 18 . 8% ) victims cleaning their wounds with water and soap or water only , then disinfecting the wound . 35 . 3% of animal bite victims went to the RPCs more than 24 hours after exposure . Only 14 . 2% of the participants knew transmission routes and the incubation period . About half ( 56 . 7% ) of respondents considered rabies as infectious , and 58 . 8% had knowledge of rabies fatality . Table 1 shows the breakdown of the two dependent variable results , including differences in animal injury history , knowledge of rabies and other potential covariates . Wound treatment was related to gender ( P < 0 . 001 ) , educational attainment ( P < 0 . 001 ) , habit of playing with animals ( P = 0 . 002 ) , animal injury history ( P = 0 . 025 ) , knowledge of source of rabies transmission ( P = 0 . 003 ) , knowledge of transmission routes ( P = 0 . 006 ) , knowledge of the rabies incubation period ( P = 0 . 006 ) and knowledge of rabies fatality ( P <0 . 001 ) . Similarly , the initiation of PEP was associated with age class ( P = 0 . 001 ) , offending animal ( P = 0 . 004 ) , knowledge of transmission routes ( P = 0 . 001 ) , knowledge of the rabies incubation period ( P = 0 . 001 ) and knowledge of rabies fatality ( P = 0 . 028 ) . We then performed a multivariate logistic regression analysis to assess the risk factors associated with improper and delayed PEP . Table 2 displays the relationship between wound treatment as well as the initiation of PEP and the influencing factors . For wound treatment , those who were male ( P < 0 . 001 ) , aged 1–14 years ( P = 0 . 027 ) , were without college education ( P < 0 . 001 ) , liked playing with animals ( P = 0 . 003 ) , knew the source of rabies virus transmission ( P = 0 . 018 ) , knew the transmission routes ( P = 0 . 007 ) , knew the rabies incubation period ( P = 0 . 007 ) and knew that rabies could be fatal ( P = 0 . 001 ) tended to treat the wound improperly . Compared with those who visited RPCs promptly , those who were 15–44 years old ( P < 0 . 001 ) , hurt by domestic animals ( P = 0 . 010 ) , knew the transmission routes ( P = 0 . 001 ) , knew the rabies incubation period ( P = 0 . 001 ) and knew that rabies could be fatal ( P = 0 . 019 ) were more likely to delay the PEP . Table 2 presents the results of the stepwise logistic regression analysis , where the dependent variables were wound treatment and the initiation of PEP . Males ( OR = 1 . 871 , 95% CI: 1 . 318–2 . 656 , P < 0 . 001 ) , those without college education ( OR = 1 . 698 , 95%CI: 1 . 203–2 . 396 , P = 0 . 003 ) , those that had a habit of playing with animals ( OR = 1 . 554 , 95% CI: 1 . 089–2 . 216 , P = 0 . 015 ) , and those with a knowledge of rabies fatality ( OR = 1 . 577 , 95% CI: 1 . 096–2 . 270 , P = 0 . 014 ) were related to improper wound treatment . For the delay of initiation of PEP , the relevant variables were 15–44 years old ( OR = 2 . 324 , 95% CI: 1 . 457–3 . 707 , P < 0 . 001 ) , hurt by domestic animals ( OR = 1 . 696 , 95% CI: 1 . 103–2 . 608 , P = 0 . 016 ) , and knowledge of the rabies incubation period ( OR = 1 . 844 , 95% CI: 1 . 279–2 . 659 , P = 0 . 001 ) .
There are several strengths to these analyses that ought to be considered . Firstly , our investigation is the first clinic-based cross-sectional study to investigate the prevalence and determinants of improper wound treatment , as well as the delay in initiation on rabies PEP . Secondly , we obtained one important finding that the main obstacle to rabies PEP is neither accessibility nor affordability , but it is the lack of knowledge and poor awareness . Thirdly , these findings provide a new roadmap to control rabies . The global strategy for rabies prevention and control should be adopted in different regions . For example , vaccines should be available and affordable in less developed countries with the highest rabies disease burdens . Education and awareness-raising programs encourage victims to take proper PEP , and communities should be involved in eliminating rabies at local , national , regional and international levels . This strategy should be administered in all rabies endemic areas , particularly in developed and developing countries . Unavoidably , this study has some limitations that need to be acknowledged . First , given the limitations of the cross-sectional design , firm conclusions concerning its possible causal effect cannot be drawn . However , the findings can be valuable for providing directed public health messaging and interventions . Second , the study site is mainly in an urban area , with few ( 1 . 2% ) farmers . However , it has been reported that there was no significant difference in knowledge between participants from urban and semi-urban area [25] . Third , the affordability and availability were proxy-assessed , nevertheless , due to the universal medical insurance and general primary care in China , the rabies vaccine is affordable and available in most areas . Fourth , due to the short survey period and without reliable retrospective data , researchers were unable to explore seasonal changes that existed in animal injury cases or in the delay of PEP . In conclusion , the clinic-based study showed that a minority of rabies exposure victims treated their wounds immediately and correctly , and more than one third of them went to RPCs for PEP more than 24 hours after exposure , despite the access of PEP being convenient and affordable . The results indicated that the majority of respondents have neither sufficient knowledge nor sufficient prevention awareness . Therefore , large-scale community-based study is needed to assess the contributing factors of rabies prevention and control . The establishment of systematic and sustained programs to propagate rabies knowledge and to generate public awareness for rabies control is a priority today . | Although the incidence of animal bites is increasing in China , residents’ knowledge about appropriate wound treatment and prompt PEP is insufficient . A face-to-face interview was conducted to investigate whether the wound was treated properly and to determine the time disparity between injury and consultation to the RPCs among animal bite victims . We discovered that a minority of people treated wounds appropriately , and more than one-third of participants delayed the initiation of PEP . A stepwise multivariable logistic regression analysis was used to identify the influencing factors of improper wound treatment and the delay of rabies PEP . Males ( OR = 1 . 871 , 95% CI: 1 . 318–2 . 656 ) , residents without college education ( OR = 1 . 698 , 95% CI: 1 . 203–2 . 396 ) , respondents liking to play with animals ( OR = 1 . 554 , 95% CI: 1 . 089–2 . 216 ) , and people who knew the fatality of rabies ( OR = 1 . 577 , 95% CI: 1 . 096–2 . 270 ) , were likely to treat wounds improperly after an animal bite . Participants aged 15–44 years ( OR = 2 . 324 , 95% CI: 1 . 457–3 . 707 ) , residents bitten or scratched by a domestic animal ( OR = 1 . 696 , 95% CI: 1 . 103–2 . 608 ) , and people who knew the incubation period of rabies ( OR = 1 . 844 , 95% CI: 1 . 279–2 . 659 ) tended to delay the initiation of PEP . The results also showed that knowledge of rabies among residents is insufficient . These findings highlight the urgent need for public educational and awareness-raising programs that would improve appropriate wound treatment and prompt PEP to prevent rabies-related deaths . | [
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] | 2017 | Improper wound treatment and delay of rabies post-exposure prophylaxis of animal bite victims in China: Prevalence and determinants |
Emergence of human fascioliasis prompted a worldwide control initiative including a pilot study in a few countries . Two hyperendemic areas were chosen: Huacullani , Northern Altiplano , Bolivia , representing the Altiplanic transmission pattern with high prevalences and intensities; Cajamarca valley , Peru , representing the valley pattern with high prevalences but low intensities . Coprological sample collection , transport and study procedures were analyzed to improve individual diagnosis and subsequent treatments and surveillance activities . Therefore , a coproantigen-detection technique ( MM3-COPRO ELISA ) was evaluated , using classical techniques for egg detection for comparison . A total of 436 and 362 stool samples from schoolchildren of Huacullani and Cajamarca , respectively , were used . Positive samples from Huacullani were 24 . 77% using the MM3-COPRO technique , and 21 . 56% using Kato-Katz . Positive samples from Cajamarca were 11 . 05% using MM3-COPRO , and 5 . 24% using rapid sedimentation and Kato-Katz . In Huacullani , using Kato-Katz as gold standard , sensitivity and specificity were 94 . 68% and 98 . 48% , respectively , and using Kato-Katz and COPRO-ELISA test together , they were 95 . 68% and 100% . In Cajamarca , using rapid sedimentation and Kato-Katz together , results were 94 . 73% and 93 . 58% , and using rapid sedimentation , Kato-Katz and copro-ELISA together , they were 97 . 56% and 100% , respectively . There was no correlation between coproantigen detection by optical density ( OD ) and infection intensity by eggs per gram of feces ( epg ) in Cajamarca low burden cases ( <400 epg ) , nor in Huacullani high burden cases ( ≥400 epg ) , although there was in Huacullani low burden cases ( <400 epg ) . Six cases of egg emission appeared negative by MM3-COPRO , including one with a high egg count ( 1248 epg ) . The coproantigen-detection test allows for high sensitivity and specificity , fast large mass screening capacity , detection in the chronic phase , early detection of treatment failure or reinfection in post-treated subjects , and usefulness in surveillance programs . However , this technique falls short when evaluating the fluke burden on its own .
Fascioliasis is an important human and animal disease caused by the trematode species Fasciola hepatica and F . gigantica . At present , fascioliasis is emerging or re-emerging in numerous regions of Latin-America , Africa , Europe and Asia , both in humans and animals , a phenomenon which has partly been related to climate change [1] . Major human health problems are encountered in Andean countries ( Bolivia , Peru , Chile and Ecuador ) , the Caribbean ( Cuba ) , northern Africa ( Egypt ) , western Europe ( Portugal , France and Spain ) and the Caspian area ( Iran and neighbouring countries ) [1] . Emergence , long-term pathogenicity [2]–[4] and immunological interactions [5] , [6] prompted the WHO to include this disease among the so-called neglected tropical diseases ( NTDs ) , which are chronic , debilitating , poverty-promoting and among the most common causes of illness in developing countries . Their control and elimination is now recognized as a priority to achieve the United Nations Millennium Development Goals and targets for sustainable poverty reduction [7] , [8] . Among Andean countries , the highest human fascioliasis prevalences and intensities are encountered in the Northern Altiplano of both Bolivia [9] , [10] and Peru [11] , as well as in the Cajamarca valley ( Peru ) [12] , where F . hepatica is the only fasciolid species present [13] and children and females are the subjects most affected [1] . Within the human fascioliasis high altitude transmission pattern related to F . hepatica transmitted by lymnaeid vectors of the Galba/Fossaria group in Andean countries , two different subpatterns have been distinguished according to physiographic and seasonal characteristics [1] , [13]: a ) the Altiplanic pattern , with endemicity distributed throughout an area of homogeneous altitude and transmission throughout the whole year caused by high evapotranspiration rates leading lymnaeid vectors to concentrate in permanent water bodies , e . g . the Northern Bolivian Altiplano [14]; b ) the valley pattern , with endemicity distributed throughout an area of heterogeneous altitude and seasonal transmission related to climate , e . g . the Cajamarca valley in Peru [12] , [15] , [16] . In recent years , the availability of a very effective drug against fascioliasis , namely triclabendazole [17] , prompted the WHO to launch a worldwide initiative against human fascioliasis [18] , [19] . This initiative includes interventions in human fascioliasis endemic areas presenting different epidemiological situations and transmission patterns [1] . Bolivia and Peru are two of the countries selected for priority intervention due to the very large public health problem posed by this disease . Different pilot schemes were designed to assess the best control strategies according to the different epidemiological situations and transmission patterns . The Northern Bolivian Altiplano was chosen as an example of the Altiplanic pattern , while the Cajamarca valley was chosen as an example of the valley pattern . An alternative to coprological egg detection is the use of immunodiagnostic tests based on the detection of anti-Fasciola antibodies and/or coproantigens released by the parasite . In the last decades , several ELISA methods based on the use of polyclonal and monoclonal antibodies have been reported to be useful for detection of F . hepatica and F . gigantica in the feces of sheep and cattle [20]–[23] and also rat feces [24] . Nevertheless , surveys on human fascioliasis have usually been made through various coprological techniques verifying the presence of eggs in stools [25] and antibody detection tests to confirm the diagnosis of human fascioliasis [26] . Among these techniques , classical coprological egg detection methods are the most frequently used [27] . However , so far , the use of coproantigen detection was applied to diagnose F . hepatica infection in patients in Cuba only [28] , [29] . Enzyme-linked immunosorbent assay ( ELISA ) methods developed for determination of Fasciola coproantigens in stool samples from animals and humans provide an alternative to coprological examination [30] , [31] . One of these methods is the MM3 capture ELISA ( MM3-COPRO ) test for fascioliasis diagnosis detection of fecal excretory-secretory antigens ( ESAs ) using a monoclonal antibody ( mAb ) , whose usefulness for detection of F . hepatica and F . gigantica coproantigens in experimental and natural Fasciola infections of sheep and cattle has already been demonstrated [22] , [32] . This test proved to be highly sensitive ( confirmed by necropsy ) and specific ( no cross reaction was observed with antigens from other helminths ) , and allowed for the detection of Fasciola infections 1–5 weeks before patency in cattle . Furthermore , other researchers recently tested a commercial version of the test , and its appropriateness for the detection of F . hepatica infections in cattle was confirmed under field conditions [33] . The suitability of the MM3-COPRO method for detection of Fasciola coproantigens in both fresh and preserved stools from hospital patients has been demonstrated [34] , but its applicability for detection of F . hepatica infections in humans under field conditions has not been proved . An efficient coproantigen test for human fascioliasis diagnosis represents a valuable tool to facilitate population screening and post-treatment surveillance in control campaigns , above all in communities where people are reluctant to furnish blood samples due to ethnic/religious aspects . The aim of the present study is to evaluate the coproantigen technique MM3-COPRO ELISA under field conditions for human fascioliasis diagnosis in human hyperendemic areas of Andean countries , using classical coprological techniques for egg detection for comparison purposes ( rapid sedimentation and Kato-Katz ) . Thus , two endemic areas were chosen: Huacullani ( Bolivia ) representing the Altiplanic pattern with high prevalences and intensities , and the rural areas of Cajamarca ( Peru ) , representing the valley pattern with high prevalences but with low intensities . Results of the pilot intervention implemented in Huacullani to assess the feasibility of a strategy of large-scale administration of triclabendazole , with a focus on safety and efficacy , are included in another article [35] .
In Bolivia , the study was approved by the Comisión de Etica de la Investigación of the Comité Nacional de Bioética . In Peru , it was approved by the Comité Institucional de Etica of the Universidad Peruana Cayetano Heredia and the Comité de Ética of the Instituto Nacional de Salud . All subjects involved provided written informed consent . Samples from children were obtained after consent from the children's parents , following the principles expressed in the Declaration of Helsinki . Consent was also obtained from the local authorities of the communities and heads and teachers of the school . In Huacullani , activities were performed in collaboration with the Servicio Departamental de Salud La Paz and the Unidad de Epidemiología of the Bolivian Ministry of Health and Sports ( MSyD ) . In Cajamarca , the study was done in cooperation with the Dirección Regional de Salud of Cajamarca , and the Estrategia Nacional de Zoonosis , Dirección General de Salud de las Personas , Ministerio de Salud ( MINSA ) , Lima . Coprological studies were carried out in the locality of Huacullani , which belongs to the municipality of Tiwanaku , third section of the province of Ingavi of the Departamento de La Paz , Bolivia . This locality is situated 85 km from the capital La Paz , at the western end of the so-called Tambillo-Aygachi corridor of the Northern Bolivian Altiplano . Huacullani has 2525 inhabitants , according to the last 2005 census of the Bolivian Instituto Nacional de Estadística . Stool collection was performed in the school of the locality and samples were obtained from a total of 436 children . Previous surveys in that locality showed very high prevalence rates of 38 . 2% in the year 1992 , 31 . 2% in 1993 , and 34 . 8% in 1996 in children , and 18 . 4% in 1996 and 11 . 8% in 1997 in total community surveys ( children plus adults ) [10] . Stool samples were also obtained in the Departmento de Cajamarca , Peru , which covers an area of around 35 , 400 km2 in the northern Andean part of Peru and is inhabited by 1 , 416 , 000 people . This Department comprises 13 provinces and the province of Cajamarca in turn includes 12 districts [12] . A total of 362 fecal samples were obtained from children of the schools of Escuela de Varones del Distrito ( Jesus district ) , Santa Rosa de Chaquil ( La Encañada district ) , and Andres Avelino Caceres ( Baños del Inca district ) . Previous surveys showed very high prevalences in that endemic area , with a mean of 24 . 4% and the maximum prevalence of 47 . 7% in Santa Rosa de Chaquil , the hitherto highest local prevalence detected in Peru [12] . Classical coprological techniques for egg detection were used for qualitative ( rapid sedimentation and Kato-Katz ) and quantitative ( Kato-Katz ) diagnosis . The combined use of highly specific techniques has been reported as a means of compensating the low sensitivity of the Kato-Katz technique [36] . Thus , identification of true positive and true negative cases was carried out by using two criteria: i ) finding of F . hepatica eggs in feces; ii ) egg finding plus COPRO ELISA test results . Applying the Kato-Katz technique , eggs were detected in fresh stools after analysis of three Kato-Katz slides ( Helm-Test , AK test , AK Industria e Comércio Ltda , Belo Horizonte , Brasil ) per sample , depending on the concentration of Fasciola eggs following WHO recommendations , using a template delivering about 41 . 7 mg of feces [37] . The average egg output was calculated as eggs per grams of feces ( epg ) . Parasitological analysis was done microscopically by a trained parasitologist . Intensity of infection , measured as eggs per gram ( epg ) , was used as an indicator of F . hepatica burden in infected subjects . Kato-Katz was used in both study areas and rapid sedimentation was an additional test done in Cajamarca . In the case of the Huacullani samples , a single Kato-Katz slide was used for each sample . In the case of the Cajamarca samples , the rapid sedimentation procedure was applied and those fecal samples positive for the MM3-COPRO ELISA were also quantitatively analyzed by three Kato-Katz slides . Children were not included in the study if they presented any chronic or acute hepatic disease , pregnancy , breast-feeding , any acute infection within a week of enrolment , or receiving treatment for any other disease or condition . In Huacullani , at the time of the baseline survey ( April 2008 ) , the school population consisted of 459 children aged 5 to 14 years , who were all considered eligible for an interventional treatment study . A total of 447 children returned the plastic container . From these , 437 fecal samples from an equivalent number of children were examined ( four children returned an empty plastic container , and six other children provided insufficient stool quantities to apply both Kato-Katz slide and COPRO ELISA ) . Thus , fecal samples were obtained from 437 children ( 220 males and 217 females ) of 5–16 years of age ( mean ± SD = 8 . 8±2 . 3 ) . A clean , plastic , wide-mouthed , numbered container with a snap-on lid was given to every participant . All subjects were then asked to try to fill the container with their own feces and to return it immediately . One stool sample per subject was collected and personal data ( name , sex , and age ) were noted on delivery of the container . Samples were transported to the parasitological laboratory of the Faculty of Pharmacy , Universidad Mayor de San Andrés ( UMSA ) , La Paz , within 1–3 h after collection . One aliquot was used to carry out the MM3-COPRO ELISA and another was preserved at 4°C to make the Kato-Katz slides . All Kato-Katz slides were made at the Laboratory of Parasitology of the Faculty of Medicine , UMSA , and were initially examined within 1 h of preparation to avoid overclarification of some helminth eggs . In Cajamarca , at the time of the baseline survey ( December 2007 ) , the target population was 616 school children ( age range 6–15 years old ) , with a coverage of 4 . 25% of the school children population and 0 . 86% of the overall population from the three aforementioned districts . Thus , in the present study , fecal samples were obtained from 362 children ( 264 males and 98 females ) , 7–15 years of age ( mean ± S . D . = 9 . 9±2 . 2 ) , by similar procedures . Samples were transported to Cajamarca city within 1–3 h after collection and stored at 4°C until being sent to the Laboratory of Parasitology at the Instituto de Medicina Tropical Alexander von Humboldt , Lima , where coproparasitological analyses were carried out . Both ELISA and Kato-Katz slides were applied to two aliquots of the material preserved at 4°C . A third aliquot was preserved in 10% formalin solution ( 1∶3 ) for subsequent egg detection by means of the rapid sedimentation technique [38] . To assure quality standards and possible handling differences , procedures in the two laboratories were implemented by the same personnel of the Valencia team in addition to the respective local personnel of each laboratory . In Cajamarca , stool samples were distributed into two groups according to the 400-epg threshold used for identifying high intensity infections [18]: a high burden group ( ≥400 epg ) and a low burden group ( <400 epg ) . However , in Huacullani , as precautionary measure , a lower threshold ( 300 epg ) was requested to be applied by Bolivian health responsibles to distinguish between samples whose respective infected children were in need to be hospitalized for prevention follow up of potential post-treatment colics , and samples whose respective infected children were not hospitalized and were treated on an out-patient basis [35] . Statistical analyses were done using PASW 17 software . For the evaluation of categorical variables , the chi-square test or Fisher's exact test was used . Bivariant correlations ( Pearson's correlation ) were calculated to assess the relationship between optical density ( OD ) and epg of F . hepatica . A P value below 0 . 05 was considered significant . Theoretical positive predictive values ( PPV ) and negative predictive values ( NPV ) were calculated from sensitivity and specificity values obtained using only classical coprological tests for the identification of F . hepatica eggs in feces as “gold standard” . The following formulas were used for their calculation: The MM3-COPRO ELISA kits were prepared and tests performed as previously described [22] , [32] , [34] . Kits were provided by Dr . F . M . Ubeira ( University of Santiago de Compostela , Spain ) . Briefly , polystyrene microtiter 1×8 F strip plates ( Greiner Bio-One GmbH , Frickenhausen , Germany ) were coated overnight with 100 µL/well of a solution containing 10 µg/mL of rabbit anti-Fasciola polyclonal IgG antibody in phosphate buffered saline ( PBS ) ( wells from odd-numbered rows ) , or with 100 µL/well of a solution containing 10 µg/mL of IgG polyclonal antibodies from non-immunized rabbits ( wells from even-numbered rows ) . Uncoated sites were blocked with 1 . 5% of sodium caseinate in PBS for 1 h at RT , and each fecal supernatant ( 100 µL ) was then added in quadruplicate ( 2 odd-numbered wells plus 2 even-numbered wells ) , and incubated overnight at 4°C . After washing 6 times with PBS containing 0 . 2% Tween-20 ( PBS-T ) , 100 µL of a solution containing 0 . 3 µg of biotinylated MM3 antibodies in PBS-T plus 1% bovine serum albumin ( PBS-T-BSA ) was added to each well and incubated for 1 hr at 37°C . After washing as above , bound MM3 antibody was detected by incubation , first with peroxidase-conjugated neutravidin ( Pierce , Rockford , Illinois; dilution 1∶2000 in PBS-T-BSA ) for 1 hr at 37°C , and then with the substrate ( buffered H2O2 and o–phenylenediamine [OPD] , Sigma-Aldrich , Madrid , Spain ) . After incubation for 20 min at RT , the reaction was stopped by addition of 3N H2SO4 . Finally , OD was measured at 492 nm . The OD value for each sample was calculated as OD1–OD2 , where OD1 is the mean for the 2 even-numbered wells ( coated with anti-Fasciola polyclonal antibodies ) , and OD2 is the mean for the 2 odd-numbered wells ( coated with irrelevant polyclonal antibodies ) . The OD value for each sample was calculated by subtracting the OD of the blank well from the OD of the test well using the cut-off point 0 . 097 [34] .
Huacullani positive cases were globally 24 . 77% using MM3-COPRO ELISA and 21 . 56% applying an egg detection technique ( Kato-Katz ) . No significant differences were encountered between either % ( P = 0 . 093 ) . In this Bolivian locality , using Kato-Katz as gold standard , sensitivity and specificity were 94 . 68% and 98 . 48% , respectively , and using Kato-Katz and COPRO-ELISA test together as gold standard , sensitivity and specificity were 95 . 68% and 100% , respectively . Of 436 samples assayed , 94 showed the presence of eggs through the Kato-Katz technique ( 21 . 56% ) . MM3-COPRO ELISA was positive in 108 samples ( 24 . 77% ) , which included samples with Fasciola eggs ( 89 ) and without Fasciola eggs ( 19 ) , i . e . 82 . 40% of the children who were positive for the MM3-COPRO ELISA were also positive through the Kato-Katz procedure . It should be emphasized that there were five children shedding eggs with emissions of 48 , 72 , 96 , 120 and 1248 epg , whose MM3-COPRO ELISA results were negative ( 1 . 14% ) . The stool sample showing 1248 epg was repeatedly re-analyzed and a negative result was always obtained with the MM3-COPRO ELISA test . The geometric mean egg content in F . hepatica positive samples was 142 . 17 epg , and the arithmetic mean was 334 . 98 ( with SD of ±92 . 56 ) , with a range of 24 to 8088 epg ( Table 1 ) . In these samples from Huacullani , epg data were distributed into two groups: a high burden group ( ≥400 epg ) and a low burden group ( <400 epg ) of samples . The OD values obtained for individual F . hepatica positive and negative fecal samples from Huacullani are shown in Figure 1 . Positive samples with F . hepatica eggs showed OD values above the cut-off value except in five cases ( determined by the Kato-Katz technique ) . In children who were positive in egg emission , the bivariant correlation between OD and epg data from low and high burden groups was carried out separately . A significant positive correlation was detected only between OD and low burden ( r2 = 0 . 20 ) ( Figure 2 ) , but no significant positive correlation was detected when considering OD and high burden ( r2 = 0 . 01 ) ( Figure 3 ) . Theoretical PPVs and NPVs vs fascioliasis prevalence are represented in Figure 4A , showing the expected PPVs and NPVs depending on whether the test was used in low , medium or high prevalence scenarios in this Altiplanic highly endemic locality . Cajamarca positive cases were globally 11 . 05% using MM3-COPRO ELISA and 5 . 60% employing egg detection techniques ( rapid sedimentation and Kato-Katz ) . Significant differences were detected between both % ( P = 0 . 007 ) . Differences between the two local patterns were detected , i . e . significant differences were found when comparing MM3-COPRO ELISA positive cases % from Huacullani and Cajamarca ( P = 0 . 0025 ) , and also when comparing egg detection positive cases % from Huacullani and Cajamarca ( P = 0 . 001 ) . In Cajamarca , using rapid sedimentation and Kato-Katz together as gold standard , sensitivity and specificity were 94 . 73% and 93 . 58% , respectively , and using rapid sedimentation , Kato-Katz and copro-ELISA together as gold standard , results were 97 . 56% and 100% , respectively . In this Peruvian locality , of 362 samples assayed , 19 showed the presence of eggs through the rapid sedimentation and Kato-Katz techniques ( 5 . 24% ) , whereas MM3-COPRO ELISA was positive in 40 samples , which included the samples with Fasciola eggs ( 18 ) and without Fasciola eggs ( 22 ) , i . e . 45 . 0% of the children who were positive by MM3-COPRO ELISA were also positive through coprological egg detection procedures . Interestingly , one child shed eggs ( by the rapid sedimentation technique ) but was negative by MM3-COPRO ELISA . The remaining 321 MM3-COPRO ELISA negative samples , however , included 237 negative samples , and 84 positive samples for parasitic infections other than Fasciola . They involved one or more parasitic protozoans ( Blastocystis hominis , Chilomastix mensnilii , Giardia intestinalis , Entamoeba histolytica/E . dispar/E . moshkovskii , E . coli , Endolimax nana , Iodamoeba buetschlii ) and helminth species ( Strongyloides stercoralis , Ascaris lumbricoides , Trichuris trichiura , Enterobius vermicularis and Hymenolepis nana ) . The geometric mean egg content in F . hepatica positive samples from Cajamarca was 89 . 80 epg , and the arithmetic mean was 116 . 47 ( with SD of ±84 . 80 ) , with a range of 16 to 376 epg ( Table 1 ) , i . e . samples were all considered as belonging to the low burden group as their epg counts were <400 . The OD values obtained for individual F . hepatica positive and negative fecal samples from Cajamarca are shown in Figure 5 . Positive samples with F . hepatica eggs showed OD values above the cut-off value except in one case ( determined by the rapid sedimentation technique ) . In children who were positive in egg emission , the bivariant correlation between OD and epg data ( low burden ) was carried out . No significant positive correlation between OD and low burden ( r2 = 0 . 05 ) was detected ( Figure 6 ) . Theoretical PPVs and NPVs vs fascioliasis prevalence are represented in Figure 4B , showing the expected PPVs and NPVs depending on whether the test was used in low , medium or high prevalence scenarios in this Peruvian highly endemic locality .
Sensitivity is defined as the proportion of people with the disease who have a positive test for the disease . A sensitive test will rarely miss people with the disease . Specificity is the proportion of people without the disease who have a negative test . A specific test will rarely misclassify people as having the disease when they do not [39] . Knowing true positive and true negative cases is essential when calculating sensitivity and specificity , respectively . The identification of true positive and true negative cases was carried out using classical coprological tests for the identification of F . hepatica eggs in feces . Nevertheless , in the case of human fascioliasis , the application of the rapid sedimentation or Kato-Katz techniques may result in false negative cases . The ethiological diagnosis based on egg detection in stools is complicated because parasite eggs are not found during the prepatent period [27] , [40] , when juvenile worms migrate through the intestinal wall to the peritoneal cavity ( at one week ) , penetrate the liver parenchyma ( at five to seven weeks ) , and pass into the biliary tract where they ultimately reach maturity ( at two months or more ) . Previous studies have even estimated a period of at least three to four months to be necessary for F . hepatica flukes to attain sexual maturity in humans [27] , [41] . Once the worms have matured , diagnosis still remains difficult because commonly employed microscopic techniques for quantitative diagnosis of Fasciola eggs are very specific but rather insensitive . In addition , in some cases diagnosis is also difficult during the biliary stage , due to the intermittent excretion of parasite eggs . Fecal egg counts are known to follow inter- and intraindividual variations in fascioliasis [42] , [43] . In our case , we used the Kato-Katz technique as a “gold standard” because it is considered the best available for quantitative analysis , although taking into account that it is admittedly rather imperfect . Therefore , results from the rapid sedimentation were also considered to improve the first gold standard in Cajamarca , and the combination of results from both coprological methods and COPRO ELISA were used for both study areas . When liver-flukes are located in the bile ducts , excretory-secretory ( ES ) products are released , being eliminated via feces . The detection of these products by means of a sandwich-ELISA reflects the installation of flukes in the bile ducts and the presence of the biliary stage of the disease [30] . No statistically-significant differences were detected between prevalence results obtained using egg detection techniques and the MM3-COPRO ELISA in Huacullani , where egg intensities are higher according to the typical feature of the Altiplanic pattern . On the contrary , such differences were detected in Cajamarca , probably as a consequence of the low egg intensities characteristic of the valley pattern , i . e . in Cajamarca low burdens are common and therefore the higher probability of infected subjects intermittently shedding very few eggs is higher , with the consequence that such cases go unnoticed . Five and one cases of egg emission were negative using the MM3-COPRO ELISA in Huacullani and Cajamarca , respectively , including one case of very high egg count ( 1248 epg ) in the Bolivian locality . Such cases pose a question mark . This result raises the question as to whether these false negative cases may be interpreted as being inherent to the kit design , or due to external factors not attributable to the ELISA kit . However , considering that there is broad experience in detecting Fasciola coproantigens in ovine and bovine samples , and that animals with egg emission were not found to be negative with the MM3 ELISA , it is unlikely that these false negative results were due to kit construction . Furthermore , a recent study has shown that the monoclonal antibody used in the MM3 assay recognizes L1 and L2 cathepsins [44] , as does the ES78 in the FasciDig test [20] , and there were no observations of false negative results with this test either . Three possible explanations include ( i ) an intermittent release of the ES products from the liver to the intestine through the bile ducts , ( ii ) spurious infections , and ( iii ) the existence of food remains in the intestine masking or interfering with the detection of the fluke ES antigens . The first does not seem to be the case , as previous studies using this and other kits do not indicate the emission of cathepsins L1 and L2 in either human or animal species to be intermittent ( unlike with eggs ) . A spurious infection was excluded after meticuluous study of the aspect of eggs in each one of these children . A potential negative influence of high temperatures during the transport or/and an inadequate handling of the samples at a given moment throughout the whole procedure cannot be ruled out , although the relatively short storage period does not suggest a considerable denaturation of the L-cathepsins to have occurred . In both Huacullani ( representing the fascioliasis Altiplanic pattern ) and Cajamarca ( representing the fascioliasis valley pattern ) , cases of coproantigens present in the feces of humans without F . hepatica eggs in stools were detected . Previous time-course studies in animals on the detection of F . hepatica coproantigens by ELISA indicated that coproantigens were detectable prior to patency [45] . Furthermore , a marked increase in the levels of these coproantigens at the beginning of fecal egg output was observed [32] . Considering the positivity/negativity of MM3-COPRO ELISA and the presence/absence of eggs in feces , two situations were established in the current study: the Altiplanic pattern with a correlation between positivity of MM3-COPRO ELISA and the presence of eggs , and the valley pattern with a larger number of positive cases applying MM3-COPRO ELISA but without presence of eggs in feces . The Altiplanic pattern , characterized by higher prevalences and intensities , showed no statistical differences between the percentage of children who were positive in coproantigens and eggs in feces . Thus , it may be concluded that the majority of children with liver-flukes in the biliary ducts shed eggs . Nevertheless , in the valley pattern , characterized by high prevalences but low intensities , differences were detected between the percentage of children who were positive to coproantigens and the reduced number of these children that shed eggs in feces . This suggests that children did not shed eggs or only a much reduced , undetectable number even despite presenting parasites in their biliary canals . In Europe , for instance , the diagnosis of human fascioliasis is frequently established using serological tests , because the detection of F . hepatica eggs in stools is not always possible . Thus , in an epidemiological survey from 1970 to 1999 to record cases of human fascioliasis detected in the Limousin region ( central France ) , egg detection in stools was positive in only 27 . 6% of a total of 711 persons with fascioliasis [46] . Future studies are needed in Cajamarca ( and other endemic areas in valleys of the Andean countries ) to verify whether in these cases the non-detection of eggs implies that the parasite ( i ) has not reached the biliary ducts or is located in the bile-ducts but oviposition has not yet started ( suggesting a more or less recent infection ) or ( ii ) oviposition is taking already place but with only very low egg numbers or with intermittent shedding ( indicating that subjects present only one or a very few flukes in the chronic stage ) . Negative results by the MM3-COPRO ELISA after treatment , which occurs approximately one to three weeks in animals , is usually accepted when determining the efficacy of anthelminthic treatment of biliary fascioliasis [22] . Contrarily , serological methods have limitations when determining the efficacy of anthelminthic treatment because the presence of antibodies indicates previous exposure to the parasite rather than the existence of a current infection . Additionally , after successful anthelminthic treatment , several months have to pass for serological antibody-detection tests to become negative . Hence , the detection of specific antigens in feces allows for the confirmation of a current infection , whereas antibody detection tests need to be complemented by another technique to confirm the results obtained in treated subjects . Future studies should be carried out to determine the time required for negativization of MM3-COPRO ELISA results after effective treatment in humans . The MM3-COPRO ELISA is also a reliable method for detecting F . gigantica coproantigens in fecal samples from experimentally infected sheep [32] . Although most reported cases of human fascioliasis are caused by F . hepatica , infections by F . gigantica have also been reported [25] . The fact that the MM3-COPRO ELISA can detect infections by both species may be of great value to ensure diagnosis of human and animal fascioliasis in countries where F . gigantica predominates , or where both species of Fasciola are present [25] , [34] . Determining a patient's parasitic burden is crucial given the necessity to monitor drug treatment in order to prevent a hepatic colic as the consequence of the massive expulsion of liver-flukes [18] , similar to other helminth diseases [47] . The Kato-Katz is usually employed as a coprological quantitative technique . Nevertheless , this technique has a low sensitivity , and the elaboration of several slides from the same individual stool sample is indispensable . The application of the Kato-Katz technique in community surveys becomes problematic because ( i ) it is pronouncedly time consuming when the number of samples is high , ( ii ) microscopic egg count is also time consuming in cases of heavy egg burdens , and ( iii ) it requires an additional technique to increase the sensitivity in areas where subjects shed a very low number of eggs in an intermittent way . Results obtained in the samples from Huacullani showed that the concentration of coproantigens in feces is correlated with epg in the low burden group ( <300 epg ) . This result agrees with a previous study using the MM3-COPRO ELISA in cattle , which showed that the concentration of coproantigens in feces is also correlated with the number of flukes found in the livers of animals collected after slaughter [22] , as well as with the results of positive correlation found with another coproantigen test in fascioliasis infected patients in Cuba [30] . Nevertheless , our findings in the high burden group ( ≥300 epg ) showed that the concentration of coproantigens in feces is not correlated with epg . This result agrees with the absence of any correlation between egg shedding in human samples from Hospital patients , measured by the Kato-Katz technique , and coproantigen concentration , measured by the MM3-COPRO ELISA [34] . One possible explanation for this discrepancy may be that the positive cases analyzed in Cuba [30] probably corresponded to recent infections with less than a year of age ( early chronic stage ) , whereas our samples were from patients with chronic infections , in which egg excretion is probably more erratic . It must be kept in mind that fasciolid flukes may survive for up to 13 . 5 years in humans , and the pattern of egg shedding is not linear but fluctuates between maximum and minimum values [43] . By comparison , the kinetics of coproantigen release versus the kinetics of egg shedding showed a similar pattern but with a two-week time lag in epg [32] . In Cajamarca , chronic fascioliasis in valley samples , coproantigen levels did not show a good correlation with epg . Therefore , the use of only one coproproantigen technique appears to be insufficient to evaluate the fluke burden . In these hyperendemic areas , the number of subjects who participate in surveys of this kind is very large , which implies the problem of transporting and preserving the fecal samples , as the coproantigen degrades at ambient temperature within a few days and the fecal material cannot be treated with any classical fixative . The monoclonal antibody MM3 recognizes a single conformational epitope , located in Fasciola cathepsins L1 and L2 , which are the main cysteine proteases produced by adult flukes gut [44] . The stability of the antigen was observed during a period of 5 weeks , except for samples preserved in CoproGuard , which were observed for 17 weeks . Comparison of the different preservation conditions revealed that even when maintained at 37°C , only the antigenicity of coproantigens in the samples diluted with CoproGuard did not vary throughout the observation period . In contrast , biocides such as sodium azide and thimerosal did not preserve the antigenicity , as the start signal decreased to approximately 30% by the end of the observation period . When the samples were maintained at 4°C , the F . hepatica coproantigens retained about 70% of their initial antigenicity after 5 weeks . However , the antigens are relatively stable in some stools . This suggests that degradation of MM3-recognized Fasciola coproantigens depends on the presence of particular protease species , or other factors , which differ for each patient [34] . Other studies have also referred to the stability of Fasciola coproantigens . The monoclonal antibody F10 recognizes a 26–28 kDa antigen which is a monomeric proteoglycan secreted and excreted from the tegument and the gut of the flukes . The antigenicity of that coproantigen was noted to be stable or even enhanced by the action of proteolytic enzymes found in the digestive tract and under a variety of standard laboratory storage conditions . Storage at various temperatures resulted in some break down of the protein . The storage of the purified protein at room temperature overnight gave rise to several new bands ranging from 8 kDa to 20 kDa . Incubation of the purified coproantigen at 4°C for two months resulted in a major band at 8 kDa and a minor band at 20 kDa which decreased in size with longer incubation . Storage of ES for more than three years resulted in a major band at 8 kDa not seen in fresh ES . All these bands were recognized by the monoclonal antibody . The 26–28 kDa band was always detectable and the smaller bands are lower in intensity , suggesting that the coproantigen is relatively stable during storage . Thus , that degradation probably represents a loss of carbohydrate , since antigenicity is maintained [48] , [49] . One possible alternative would be freezing the samples at −20°C , but this poses the additional problems of ( i ) difficult and expensive transport of frozen samples to the laboratory where determination is to take place , and ( ii ) the non-appropriateness of frozen samples for the diagnosis of other parasite species present in coinfections . Another solution is the use of Coproguard , which has been demonstrated to be convenient for sample preservation in this kind of surveys including the application of a coproantigen-detection test [34] . In Huacullani and Cajamarca , the PPVs calculated for diverse epidemiological situations are very different . PPVs in hyperendemic situations were very high , making this test recommendable for such situations . Contrarily , NPVs calculated for diverse epidemiological situations are similar . Current efforts for the control of human fascioliasis need diagnostic techniques which allow for high sensitivity and specificity , large mass screening , detection in the chronic phase , early detection of treatment failure or reinfection in post-treated subjects , and usefulness in surveillance programs . Our results indicate that a coproantigen-detection test such as MM3-COPRO ELISA fulfils all these aspects . It provides a good tool to detect biliary fascioliasis in humans under field conditions in Andean hyperendemic countries , including a higher sensitivity than egg detection techniques , especially in areas where burdens are usually low , such as in areas of the valley transmission pattern . Hence , the MM3-COPRO ELISA appears to be not only useful for individual diagnosis in hospitals , but also in human surveys in fascioliasis endemic areas characterized by low to high parasitic burdens . The present MM3-COPRO ELISA validation is expected to facilitate the improvement of human fascioliasis diagnosis in endemic areas ( a commercial version of the MM3-COPRO ELISA is today available ) . The practical application of this sensitive and convenient method for large scale surveillance in the control programs in the Northern Bolivian Altiplano and Cajamarca could improve screening of human fascioliasis in these endemic areas by detecting infected humans in the biliary stage of the disease , as a large number of samples can easily be processed . Keeping in mind that most affected subjects are usually children , the attainment of fecal samples is easier and faster than taking blood samples , which is considered invasive . The former does not pose difficulties for community elders , school head teachers and parents who usually give their consent . Moreover , to many of these indigenous communities , blood extraction is culturally not acceptable . Furthermore , our experience in Huacullani and Cajamarca indicates that MM3-COPRO ELISA offers the easiest and fastest way to adequately face large mass screenings , by initially applying the coproantigen technique to all the coprological samples obtained in the community survey and thereafter applying the Kato-Katz technique only or first in coproantigen-positive samples . It is recommended to treat subjects with coproantigen-positive samples but with negative egg detection . This allows for a quick selected treatment action , lending the positive effects of ( i ) fast response in the communities surveyed that verify that infected subjects are treated within a few days after the survey , and ( ii ) reducing the probability of drug resistance appearance . The remaining coproantigen-negative samples may finally be analyzed for the eventual detection and subsequent selected treatment of very few subjects shedding eggs , although this last step will unavoidably be time-consuming . Given the aforementioned advantages a coproantigen-detection test offers , one wonders why there are only relatively few of such tests for parasitic diseases affecting the digestive system available: amebiasis [50] , giardiasis [51] , opisthorchiasis [52] , taeniasis [53] , trichinelliasis [54] , strongyloidiasis [55] , hookworm infection [56] . Developing and/or improving highly specific coproantigen-detection test for diseases in which coprological diagnosis requires specialized personnel and time-consuming microscope work would evidently be welcome . | A coproantigen-detection technique ( MM3-COPRO ELISA ) was evaluated in 436 and 362 schoolchildren of Huacullani , Bolivia , and Cajamarca valley , Peru , respectively . Classical techniques for egg detection were used for comparison . In Huacullani , using Kato-Katz as gold standard , sensitivity and specificity were 94 . 68% and 98 . 48% , respectively , and using Kato-Katz and COPRO-ELISA test together , they were 95 . 68% and 100% , respectively . In Cajamarca , using rapid sedimentation and Kato-Katz together , these results were 94 . 73% and 93 . 58% , respectively , and using rapid sedimentation , Kato-Katz and copro-ELISA together , results were 97 . 56% and 100% , respectively . There was no correlation between coproantigen detection by optical density ( OD ) and infection intensity by eggs per gram of feces ( epg ) in Cajamarca low burden cases ( <400 epg ) , nor in Huacullani high burden cases ( ≥400 epg ) , although there was in Huacullani low burden cases ( <400 epg ) . Six cases of egg emission appeared negative by MM3-COPRO , including one with a high egg count ( 1248 epg ) . The coproantigen-detection test allows for high sensitivity and specificity , fast large mass screening capacity , detection in the chronic phase , early detection of treatment failure or reinfection in post-treated subjects , and usefulness for surveillance programs . However , this technique falls short when evaluating the fluke burden on its own . | [
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] | 2012 | Field Evaluation of a Coproantigen Detection Test for Fascioliasis Diagnosis and Surveillance in Human Hyperendemic Areas of Andean Countries |
The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity . Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined , obtained from a cycle ergometry cohort study . In total , 110 metabolites ( within the classes of acylcarnitines , amino acids , and sugars ) were measured through a targeted metabolomics approach , combining tandem mass spectrometry ( MS/MS ) with the concept of stable isotope dilution ( SID ) for metabolite quantitation . Biomarker candidates were selected by combined analysis of maximum fold changes ( MFCs ) in concentrations and P-values resulting from statistical hypothesis testing . Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting . Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis . Kinetic shape templates were characterized , defining different forms of basic kinetic response patterns , such as sustained , early , late , and other forms , that can be used for metabolite classification . Acetylcarnitine ( C2 ) , showing a late response pattern and having the highest values in MFC and statistical significance , was classified as late marker and ranked as strong predictor ( MFC = 1 . 97 , P < 0 . 001 ) . In the class of amino acids , highest values were shown for alanine ( MFC = 1 . 42 , P < 0 . 001 ) , classified as late marker and strong predictor . Glucose yields a delayed response pattern , similar to a hockey stick function , being classified as delayed marker and ranked as moderate predictor ( MFC = 1 . 32 , P < 0 . 001 ) . These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology , such as β-oxidation of fatty acids , glycolysis , and glycogenolysis . The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies .
Basic principles in reaction kinetics of biomolecules were described by the work of Guldberg & Waage [1–3] more than 150 years ago and recently resumed by Voit et al . , 2015 [4] in their perspective article "150 years of mass action" . The underlying concept is the law of mass action , describing the quantitative aspects of a chemical reaction under ideal conditions . If a substance C is formed by the reaction of substance A and substance B , the production of C can be described by the following equation ProductC=k*A*B ( 1 ) where A , B , and C are concentrations changing over time , and k is a rate constant describing the speed of the reaction . Probably the most widely known and used modification of the original model in biochemistry is the Michaelis-Menten rate law ( MMRL ) introduced by Michaelis & Menten in 1913 [5] v=VmaxSKm+S ( 2 ) where v is the reaction rate , Vmax the maximum reaction rate , S the concentration of the substrate , and Km the Michaelis constant ( the substrate concentration at half of the maximum reaction rate ) . The Michaelis-Menten model describes the reaction kinetics of an enzyme-catalyzed single-substrate reaction , in which the conversion of a substrate S into a product P takes place via the formation of an intermediate complex ES , where k1 , k2 and k3 denote reaction rates [4] E+S←k2→k1ES→k3E+P ( 3 ) Guldberg and Waage also examined the fact that biochemical systems tend to remain in homeostasis , which is described by the equilibrium constant [6] Keq=[C]c[D]d[A]a[B]b ( 4 ) Keq is the equilibrium constant in the general reaction aA + bB↔cC + dD , where a , b , c , d are the number of molecules of A , B , C , D participating , and [A] , [B] , [C] , [D] are the molar reaction concentrations of the reaction components at equilibrium [7] . When analyzing regulatory mechanisms of metabolite kinetics , a key question addresses the effect of external perturbations disturbing homeostasis , e . g . , caused by environmental influences , nutrition , drug interventions ( pharmacodynamics ) or physical activity ( studied in this work through clinical exercise testing ) . These effects can be measured and examined by longitudinal cohort studies , which investigate dynamic changes in metabolite concentrations over time . In chronic toxicity testing , which occupies a central position in the analysis of dynamic time-course metabolic data , studies are performed to explore the influences of toxic substances on human or animal metabolism . Mechanisms of metabolite kinetics are analyzed , e . g . , by investigating the effect of pesticide exposure on children [8 , 9] , by in-vitro examination of drug induced effects in neurotoxicity using brain cell cultures [10] , or by analysis of toxic effects of polymers or nanoparticles to the water flea daphnia magna [11 , 12] . In biotechnological process monitoring , metabolic interactions are analyzed , e . g . , in studying the sensitivity of the biocatalyst Clostridium thermocellum to ethanol stress [13] , in exploring the forced ageing process of Port wine [14] or by the examination and optimization of cell culture media , as e . g . , of Chinese hamster ovary ( CHO ) cells [15–17] . In pharmacodynamics , time-course data are collected , e . g . , to study the effect of continuous exposure of breast cancer cells to an anti-cancer chemotherapy drug on the metabolic level [18] or to explore the metabolism of albumin in patients with systemic inflammatory response syndrome after continuous venovenous hemofiltration [19] . Research questions on kinetic mechanisms in physical exercise cover fundamental work , e . g . , on studying the influence of improved metabolic health on patterns in plasma metabolites [20] or analyzing the effects of aerobic exercise on oral glucose tolerance [21] . In this work , in response to an incrementally increased physical load by cycle ergometry and depending on the underlying metabolic regulatory mechanisms , metabolites are expected to show specific kinetic signatures and shape patterns . Expected kinetic response patterns include: a sustained response ( mainly constant concentration over time , overlaid with biological or instrumental noise ) , an early response ( main decrease/increase of concentrations shortly after start of activity ) , a halving interval response ( major change in concentration at half time of physical activity , e . g . , a sigmoid behavior with a plateau ) , a late response ( strongest decrease/increase of concentration towards the end of physical activity ) , and a delayed response pattern ( first mainly sustained metabolite concentration , then showing a strong reaction after the end of activity during the recovery phase , respectively ) . Regarding computational and mathematical aspects of characterizing kinetic regulatory mechanisms , different approaches of fundamental models for the analysis of metabolic processes have been described in the literature: qualitative models for topological network analysis , models of flux balance analysis using stoichiometric network construction and detailed kinetic models representing metabolic processes using ordinary differential equations ( ODEs ) [22 , 23] . Furthermore , different intermediate approaches do exist , e . g . , the approach of structural kinetic modeling ( SKM ) , approximating local biochemical mechanisms within a metabolic network by a parametric linear representation [23] . An overview on different "approximative kinetic formats used in metabolic network modeling" is given by Heijnen , 2005 [24] . An example for the dynamic simulation of kinetic mechanisms in metabolism—by simulating the mitochondrial fatty acid β-oxidation—is presented by Modre et al . , 2009 [25] . Further examples for theoretical network models as well as dynamic kinetic simulations can be found in the context of the e-cell project [26] , e . g . , models for drosophila [27] or the metabolic simulation of red blood cell storage [28] . With respect to the analysis of dynamic metabolic data , Smilde et al . , 2010 [29] distinguish between six groups of methods: methods based on fundamental models , predefined basic functions , dimension reduction , multivariate time series models , analysis-of-variance ( ANOVA ) type models , and methods based on imposing smoothness . Analyses of periodic or oscillating data can be performed using methods such as Fourier analysis , wavelet transformation or principal component analysis ( PCA ) with wavelets [29 , 30] . Hidden Markov models were presented as a way for using basic functions , allowing flexibility and adaptation in modeling [29 , 31] . In particular , in gene-expression analysis orthogonal polynomials were introduced for qualitative and quantitative modeling [32 , 33] . Alternative methods for the analysis of longitudinal metabolic data , typically used in nuclear magnetic resonance ( NMR ) spectroscopy , comprise weighted principal component analysis ( WPCA ) [34] or analysis of variance ( ANOVA ) simultaneous component analysis ( ASCA ) [35] . A statistical framework for metabolic biomarker discovery in NMR data was presented by Berk et al . , 2011 [36] , introducing a smoothing spline mixed effects ( SME ) model , combined with an associated functional test statistic . Mishina et al . , 1993 [37] suggested analyzing the kinetics of biomolecules by fitting differential equations for the application in pharmacodynamics . A method for investigating between-metabolite relationships by simultaneous component analysis with individual differences constraints ( SCA-IND ) was presented by Jansen et al . , 2012 [38] . A new method for combined analysis of proteomics and metabolomics data using integrative pathway analysis was introduced by Stanberry et al . , 2013 [39] . As an example for a web-based , freely accessible online service , Metaboanalyst [40] offers the profiling of longitudinal time-course data on the basis of a multivariate empirical Bayes approach . Metabolic biomarkers play an essential role in clinical diagnostics because of their ability to provide specific insights by being functional endpoints of human molecular interactions [41] . The general process for the discovery , verification , and validation of metabolic biomarker candidates was described by Baumgartner & Graber , 2008 [42] . This process ranges from experimental study design , over clinical study execution , execution of bioanalytical methods and acquisition of data , consolidation and integration of data , application of bioinformatics algorithms and data mining methods for the identification of biomarker candidates , up to an independent validation of putative biomarkers by clinical trials . In their review article , Baumgartner et al . , 2011 [43] give a comprehensive survey of computational data analysis strategies for the discovery of biomarker candidates from metabolic data . A milestone in clinical application of metabolic biomarkers was set by establishing routine newborn screening programs for inherited metabolic disorders [44] . The search for novel metabolic biomarkers in disease covers a wide range of clinical application areas , e . g . , the identification of metabolic markers in prostate cancer by a rule-based feature selection algorithm [45] , the search of early markers as well as late markers in planned and spontaneous myocardial infarction [46 , 47] , the investigation of metabolic mechanisms in diabetes [48–50] or the discovery of putative biomarker candidates in chronic kidney disease [51–53] . In this article , we present a computational methodology , aimed at the modeling and characterization of kinetic regulatory mechanisms and the discovery of dynamic metabolic biomarker candidates in physical activity . Dynamic time-course metabolic concentration data are generated from a longitudinal biomarker cohort study by standardized cycle ergometry experiments . In total , 110 metabolites ( including metabolite classes of acylcarnitines , amino acids and sugars ) are quantitated by a targeted metabolomics approach utilizing mass spectrometry . After a thorough examination of the measured concentration data in terms of data quality assurance and reliability , we selected a set of 30 metabolites relevant in exercise physiology and considered them for data analysis and modeling in this work . Metabolite concentrations of 47 individuals , showing different lengths in their concentration time curves ( depending on the individual’s maximum physical load ) , are made comparable by means of data preprocessing . Biomarker candidates are selected depending on maximum fold changes ( MFCs ) ( the amplitude of changes in concentrations ) and the corresponding P-values resulting from statistical hypothesis testing . Kinetic signatures of metabolites are quantified by a mathematical modeling approach using polynomial fitting , specifying the dynamic response patterns of analyzed metabolites during physical activity . A similarity measure for characterized metabolite kinetic signatures is obtained through specification of groups of metabolites by hierarchical cluster analysis . Kinetic shape templates are identified , specifying common kinetic response patterns and enabling the classification of dynamic metabolic biomarker candidates according to their kinetic patterns . Findings are verified and interpreted through biochemical and metabolic pathway analyses associated with physical activity .
Putative dynamic biomarker candidates are selected from the pool of analyzed metabolites by combined analysis of MFCs in concentrations and corresponding P-values from statistical hypothesis testing ( see section Maximum fold changes and statistical hypothesis testing ) . Results for this data analysis step are visualized as a volcano plot ( Fig 1 ) . The plot demonstrates log2 values of MFCs compared to-log10 values of P-values . A significance level of 0 . 001 was chosen for the selection of statistical hypothesis testing results ( horizontal blue line ) . Moderate biomarker candidates are classified with a MFC greater than 1 . 20 ( vertical blue line ) . Strong biomarker candidates are classified with a MFC greater than 1 . 40 ( vertical green line ) . Detailed data of all analyzed metabolites , including MFCs , log2 ( MFCs ) , P-values , and-log10 ( P-values ) , are summarized in Table 1 . For the analyzed classes of metabolites , putative biomarker candidates could be selected and ranked according to MFCs and P-values . As strong biomarker candidates , acetylcarnitine ( C2 , MFC = 1 . 97 , P <0 . 001 ) , showing the highest values in the entire set of analyzed metabolites , propionylcarnitine ( C3 , MFC = 1 . 52 , P < 0 . 001 ) and alanine ( MFC = 1 . 42 , P < 0 . 001 ) were identified . Valerylcarnitine ( C5 , MFC = 1 . 38 , P < 0 . 001 ) , arginine ( MFC = 1 . 36 , P < 0 . 001 ) , glucose ( MFC = 1 . 32 , P < 0 . 001 ) , butyrylcarnitine ( C4 , MFC = 1 . 27 , P < 0 . 001 ) , methylmalonylcarnitine ( C3-DC-M , MFC = 1 . 26 , P < 0 . 001 ) , hydroxyvalerylcarnitine ( C5_OH , MFC = 1 . 26 , P < 0 . 001 ) , and octadecadienylcarnitine ( C18:2 , MFC = 1 . 21 , P < 0 . 001 ) were ranked as moderate biomarker candidates . Kinetic signatures of analyzed metabolites are expected to show specific characteristic regulatory patterns , in response to the incremental increase of physical activity using a cycle ergometry stress test . Kinetic patterns of the selected 30 metabolites , characterized by a polynomial fitting approach ( see section Mathematical modeling ) , are visualized in Fig 2 ( acylcarnitines ) , Fig 3 ( amino acids ) and Fig 4 ( glucose ) . For standardized visualization of profiles , the vertical axis is normalized to a range of-20% to 40% of relative concentration . Note that acetylcarnitine ( C2 ) exceeds this specified range , showing a maximum increase in relative concentration of 67% . Different kinetic response patterns were observed . The majority of metabolites show a sustained response , e . g . , threonine , with basically constant behavior in concentration over time , however overlaid with biological or instrumental noise . An early response pattern is shown with valerylcarnitine ( C5 ) with an early decrease in relative concentration ( of approx . -16% ) after starting exercise followed by an increase in relative concentration ( to a maximum of 13% ) . Methionine could be identified as a metabolite showing a halving interval response pattern with characteristics similar to a sigmoid function , showing first a sustained reaction , then an increase in relative concentration at half time of physical activity ( by approx . 13% ) and followed by a plateau ( at approx . 9% of relative concentration ) towards the end of physical exercise . Metabolites showing a late response pattern are e . g . , acetylcarnitine ( C2 ) with a slight decrease ( -10% ) and then a strong continuous increase in relative concentration ( up to 67% ) or alanine with a continuous increase ( of approx . 32% ) up to the end of exercise . Glucose shows a delayed response pattern ( similar to a L-curve / hockey stick function , see section Mathematical modeling ) with a minor increase in relative concentration ( approx . 2% ) at the beginning of exercise , followed by a continuous decrease ( down to-12% ) and a major steep increase in relative concentration ( up to 13% ) after the end of exercise during the recovery phase . Groups of metabolites , showing similar kinetic patterns with response to physical exercise , were identified by hierarchical cluster analysis ( see section Hierarchical cluster analysis ) , resulting in a set of seven distinct clusters . Metabolites and their corresponding cluster affiliations are summarized in Table 2 . Cluster 1 consists of the two amino acids alanine and arginine . Cluster 2 and cluster 3 comprise a multitude of metabolites of similar metabolite kinetics , which show roughly sustained response patterns . In cluster 4 , the metabolites octadecadienylcarnitine ( C18:2 ) and glucose are clustered together . Cluster 5 consists of only acetylcarnitine ( C2 ) , the metabolite showing the strongest response . In cluster 6 , propionylcarnitine ( C3 ) and butyrylcarnitine ( C4 ) are grouped together . Cluster 7 represents valerylcarnitine ( C5 ) , a biomarker candidate showing an early response pattern . Kinetic shape templates , serving for the classification of similar metabolite dynamics , could be specified based on the median concentration curves of each identified cluster ( see section Hierarchical cluster analysis ) . Identified shapes and their characteristics are summarized in Fig 5 , based on relative concentration changes in reference to the initial concentration at rest . Identifiers of kinetic shape templates hereby correspond to identifiers of resulting metabolite clusters from hierarchical cluster analysis . Templates for sustained response patterns , observed in the majority of metabolites , are specified by shapes 2 and 3 . Shape 7 specifies a template for dynamic biomarker candidates , showing an early response pattern ( valerylcarnitine ( C5 ) ) . Shape 1 describes a template showing a late response pattern with a continuous increase in concentration ( alanine and arginine ) . Shapes 5 ( acetylcarnitine ( C2 ) ) and 6 ( propionylcarnitine ( C3 ) and butyrylcarnitine ( C4 ) ) define further templates for late response patterns , differing in their dynamics in concentration time courses and maximum concentration changes . Shape 4 demonstrates a template for a delayed response pattern , showing characteristics similar to a L-curve / hockey-stick function ( glucose and octadecadienylcarnitine ( C18:2 ) ) . Dynamic metabolic biomarker candidates are identified and classified through a two-step analysis procedure: first , by analysis of MFCs in concentrations and statistical hypothesis testing , and second , by reviewing and characterizing specified metabolic response patterns and kinetic shape templates . The majority of metabolites show a sustained response pattern , staying within an interval of relative MFC of less than 20% , being ineligible as putative biomarker candidates . Valerylcarnitine ( C5 ) , yielding an early response pattern , was classified as early marker and moderate predictor ( MFC = 1 . 38 , P < 0 . 001 ) . Methionine shows a halving interval response pattern with a sigmoid behavior , but having a moderate amplitude in concentration ( MFC = 1 . 16 , P > 0 . 001 ) and was therefore not selected as a biomarker candidate . A late response pattern with weak early decrease in concentration was observed with propionylcarnitine ( C3 ) ( strong predictor , MFC = 1 . 52 , P < 0 . 001 ) , and butyrylcarnitine ( C4 ) ( moderate predictor , MFC = 1 . 27 , P < 0 . 001 ) , both classified as late biomarker candidates . Alanine ( strong predictor , MFC = 1 . 42 , P < 0 . 001 ) and arginine ( moderate predictor , MFC = 1 . 36 , P < 0 . 001 ) showed a late response pattern with a continuous increase in concentration from the beginning of exercise and were classified as late markers . Highest concentration changes yielded acetylcarnitine ( C2 ) , demonstrating a late response pattern with a very strong increase towards the end of exercise . C2 was ranked as strong predictor ( MFC = 1 . 97 , P < 0 . 001 ) and classified as late marker . Showing basic delayed response patterns , glucose ( MFC = 1 . 32 , P < 0 . 001 ) and octadecadienylcarnitine ( C18:2 ) ( MFC = 1 . 21 , P < 0 . 001 ) were identified as moderate predictors and classified as delayed markers . Thanks to an elaborate body of knowledge in biochemistry , a peculiarity within the process of data analysis in metabolomics lies in the dedicated biochemical interpretation of results [54] . This knowledge is nowadays annotated in public databases , e . g . , the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [55] , and eases the interpretation of findings in the context of annotated biochemical pathways . In exercise physiology , various biochemical reactions in metabolism play an essential role , predominantly in carbohydrate metabolism ( glycolysis and glycogenolysis ) , in lipid metabolism ( β-oxidation of free fatty acids ) and amino acid metabolism [6] . During a cycle ergometry stress test , an individual increasingly consumes adenosine triphosphate ( ATP ) ; to compensate this energy consumption and maintain homeostatic levels of ATP , its production is up-regulated , first primarily by aerobic processes ( respiration ) , and then anaerobic fermentation . Under the low-impact conditions chosen in this study ( low initial output of 50 Watt ( W ) and slow increase of 25 W every three minutes ) , the metabolic data demonstrate that the body uses both glycolysis and β-oxidation of fatty acids as readily available energy sources , before protein catabolism contributes in a substantial manner . Of course , the pools of monosaccharides and free fatty acids have to be replenished by glycogenolysis and lipolysis , respectively . The findings of this work , i . e . , identified biomarker candidates of exercise metabolism , and characterized metabolite signatures via specified kinetic shape templates , can be explained through the metabolic regulatory mechanisms in physical activity . Significant changes in concentrations of acetylcarnitine ( C2 ) and closely related short-chain acylcarnitines ( C3 , C4 , and C5 ) arise from their involvement in the β-oxidation of free fatty acids with acetylcarnitine ( the single most significant finding ) representing the actual end-point of the β-oxidation of even-numbered fatty acids which constitute the vast majority of dietary fatty acids and of fatty acids in the body's adipose tissue . The strong increase in concentrations of alanine and arginine are representative for an increased production of glucogenic amino acids through high glycolytic activity . This connection is most obvious for alanine , which is the corresponding amino acid of the alpha-keto acid pyruvate and is , thus , a direct mirror of glycolytic or gluconeogenetic flux [48] . The third major finding , the overproduction of glucose after the end of the exercise , is due to the inertia of metabolic regulation . In order to supply the glycolysis with enough fuel , glucose has to be released from its storage by glycogenolysis . At the abrupt end of the exercise , the increased activity of the glycogenolytic machinery cannot be stopped immediately and , therefore , leads to overcompensated glucose levels .
In this work we have presented a computational modeling and statistics approach for the identification of dynamic metabolic signatures through characterization of kinetic patterns of circulating metabolites from a physical exercise study . Dynamic time-course metabolic concentration data were obtained through clinical exercise testing using a cycle ergometry stress test . The data of 47 individuals from four different groups were analyzed: male and female test persons , with either average physical activity or competitive athletic activity . Lactate concentrations were measured for all individuals as a gold standard for profiling physical activity . Metabolite concentrations were quantitated by a targeted metabolomics approach , combining mass spectrometry analytics with the concept of stable isotope dilution . From the initial set of 110 metabolites ( including classes of acylcarnitines , amino acids and sugars ) , we selected a reliable and quality assured set of 30 metabolites for data analysis playing a possible role in exercise physiology . Based on the generic process for biomarker discovery in metabolomics , a computational approach for the analysis of longitudinal metabolic concentration data was developed . Computational tools were implemented in R [56] for automating the data analysis workflow . The source file ( R script file ) and the underlying dataset ( Microsoft Excel file ) are provided as supporting information ( S1 File and S2 File ) . Individual workload curves , differing in the number of measurements due to variability in the individual's physical capacity and exertion , were made comparable by data preprocessing steps including rescaling and linear interpolation of concentration-time curves . Putative dynamic biomarker candidates for physical activity were selected by combined analysis of MFCs in concentrations and P-values of statistical hypothesis testing . Kinetic patterns of analyzed metabolites were characterized based on a mathematical modeling approach utilizing polynomial fitting as the method of choice . Metabolite groups , showing similar kinetic response patterns , were obtained by applying hierarchical cluster analysis to the set of characterized metabolite kinetic patterns . Kinetic shape templates could be specified according to the identified clusters , defining basic kinetic response patterns used for classification of dynamic biomarker candidates . The following kinetic response patterns could be defined: sustained response ( basically constant concentration over time , overlaid with biological and instrumental noise ) , early response ( significant change in concentration at the beginning of exercise ) , late response ( continuous decrease/increase towards the end of activity ) , and delayed response ( first basic sustained response , with a strong response and steep decrease/increase in concentration after the end of the exercise during the recovery phase ) . The selected two-step data analysis and modeling strategy including MFCs in concentrations and statistical hypothesis testing , and the modeling of kinetic shape templates led to the identification and classification of dynamic metabolic biomarker candidates for profiling physical activity . The highest values for MFCs and P-values in the analyzed set of metabolites were shown for acetylcarnitine ( C2 ) ( MFC = 1 . 97 , P < 0 . 001 ) , yielding a late response pattern , and being classified as strong predictor and late marker . Alanine showed the highest values in the class of amino acids ( MFC = 1 . 42 , P < 0 . 001 ) and yielded a late response pattern , being classified as strong predictor and late marker . The only considered sugar , glucose , yet playing a key role in physical activity , yielded a delayed response pattern classified as moderate predictor ( MFC = 1 . 32 , P < 0 . 001 ) and delayed marker . In terms of biochemical interpretation , findings were verified and interpreted according to their function in metabolic pathways , associated primarily with physical exercise ( β-oxidation of fatty acids , glycolysis , and glycogenolysis ) . Interestingly , biomarker candidates , identified with the highest predictive value , yielded late response patterns . This might be seen in the context that lactate ( also a key indicator for profiling physical activity ) first shows an almost sustained response pattern before yielding an exponential increase in concentration up to a maximum physical load . The primary occurrence of late response patterns can be interpreted as a consequence of evolutionary developed regulatory mechanisms in metabolism to keep the individual's metabolic system in homeostasis after external perturbations such as spontaneous physical activity . Using our computational approach we were able to select and classify dynamic metabolic biomarker candidates and to characterize physiologically plausible metabolite kinetic patterns in physical activity , combining the strengths of statistical testing ( hypothesis testing ) , mathematical modeling ( curve fitting ) and empiric data analysis ( hierarchical cluster analysis ) . Experimental limitations and confounders in the analyzed data may result from uncertainties about the nutrition of test persons before exercising ( recorded in questionnaires but not objectively verifiable ) , varying individual motivations and consequently different levels of exertion , potential issues during sample taking ( e . g . , incomplete removal of sweat at the point of puncture ) , or from general limitations of the analytical approach based on dried blood spots [57] . It should be noted , that at least two test persons obviously consumed nutritional supplements in the form of branch-chained amino acids , influencing the measurement values of xleucine ( sum of leucine and isoleucine ) . With reference to the selected cohort , it should be noted that the study participants formed a heterogeneous group , i . e . , they differed in their level of physical activity and status of training . Therefore , the baseline concentrations and the kinetic patterns may , to a certain extent , depend on the volunteers' differences in physical fitness , or other confounding factors such as anthropometric measures or dietary habits . Although this paper is primarily focused on the methodology for deriving kinetic patterns and not so much on the discovery of exercise-related biochemical mechanisms , the results should be seen with these limitations in mind . In terms of data preprocessing , the presented data analysis strategy reveals strong indifference towards the handling of outliers because median concentration values are selected from rescaled and interpolated concentration curves . Cut-off values for the selection of metabolic biomarker candidates ( utilizing MFCs and P-values ) were chosen empirically by reviewing obtained results and assuming that responses , showing changes in concentration within a range of-10% to +10% , are accepted as biochemically and analytically-caused data variability . For kinetic modeling , an empirical approach ( instead of applying pre-defined mathematical basic functions ) based on polynomial fitting was chosen , allowing for a more physiological characterization of metabolite kinetics . Looking at the complete set of characterized metabolite kinetic signatures , the user can choose an appropriate polynomial degree after visual inspection or by developing a proper statistical quality measure e . g . , based on an estimation of the residuals . In a few cases , minor artifacts of approx . 3% in concentration values of the fitted polynomials do occur , obviously resulting from a slight overfitting of curves due to the chosen polynomial degree . Identification of groups of similarly behaving metabolites by hierarchical cluster analysis is somewhat affected by the number of interpolated points in the concentration curves and by the degree chosen for fitted polynomials . A higher number of interpolation points as well as different degrees of polynomials were tested , showing high stability in cluster analysis , however , at a lower node height of the dendrogram the arrangement of single metabolites changes slightly between the clusters . Note that the selection of clusters basically depends on the chosen height ( cut-off ) of the hierarchical tree . Depending on the selected cut-off value , two metabolites , i . e . , methylmalonylcarnitine ( C3-DC-M ) and hydroxyvalerylcarnitine ( C5-OH ) might also be classified as additional biomarker candidates , interesting for further investigation . Specification of kinetic shape templates finally builds upon the number of specified clusters , depending computationally on the selected cut-off in hierarchical cluster analysis and biochemically on the eligibility and meaningfulness of clustered templates in terms of metabolite kinetics . Metabolic concentration data used in this study have served as a database for the development and validation of novel data mining and biomarker discovery strategies in previously published studies by our group . In Netzer et al . , 2011 [58] we presented a two-step network-based approach for the identification of metabolic biomarkers , classifying alanine , acetylcarnitine ( C2 ) , propionylcarnitine ( C3 ) , and glycine , as strong , and arginine , citrulline , and lysine as moderate biomarker candidates , represented as major hubs in the dynamic network . These findings show high accordance with identified dynamic metabolic biomarker candidates in physical activity using the approach presented in this work , again selecting alanine , acetylcarnitine ( C2 ) , propionylcarnitine ( C3 ) as strong predictors , and arginine as moderate marker candidate . In a second paper [59] we introduced a method for biomarker identification by inferring two different types of networks , i . e . , correlation networks and ratio networks . This more theoretical approach calculates scores to prioritize features using topological descriptors . Groups of obese test persons ( with a body mass index ( BMI ) > 30 ) and healthy controls were compared in this study , which identified highly discriminatory biomarker candidates , i . e . , histidine , ornithine , acetylcarnitine ( C2 ) , and proline . In this article , we have presented a computational methodology for dynamic biomarker classification and modeling of kinetic metabolic patterns in physical activity . Insight into kinetic regulatory mechanisms could be provided by characterizing specific kinetic signatures for selected key metabolites within the groups of acylcarnitines and amino acids , and for glucose . A new data analysis strategy for the characterization and classification of dynamic biomarker candidates was introduced . We were able to specify common kinetic shape templates , identified from groups of metabolites showing a similar characteristic in dynamic time-course responses . Findings demonstrated high accordance with previously published data and established biochemical knowledge , e . g . , the response of glucose , showing a behavior similar to a hockey stick function with a delayed increase in concentration after the end of physical exercise during the recovery phase . Due to the selected study design of a cycle ergometry experiment , in which physical exercise was increased incrementally ( every 3 minutes by 25 W ) , known kinetic patterns could be partly confirmed by our observations , in particular in response to the selected workload protocol . Major impact of the presented methodology can be seen in the fact that kinetic mechanisms in metabolism could be qualified and quantified not only through a “strong” mathematical model , but by an empiric deduction and description of de facto kinetic response patterns from quantitated metabolic time-course concentration data , measured under in-vivo experimental conditions . A further direction of research might be the analysis of additional classes of metabolites and the description and interpretation of kinetic patterns subsequent to active exercise in the recovery phase . Especially for glucose—which increases rapidly in concentration within the analyzed interval of the recovery phase—a prolonged examination time would be highly interesting , since glucose might be expected to be classified as strong predictor . From the computational viewpoint , a very challenging task would be the development of in-silico pathway models , integrating the identified kinetic signatures into a theoretical mathematical model for hypothesis generation and verification ( see e . g . , Teusink et al . , 2000 [60] ) . The development of a kinetic model based on an ordinary differential equations ( ODEs ) description including kinetic parameters selected from our research might be an aim for additional research which , however , is beyond the scope of this article . The approach presented in this work also shows high potential for contributing to other application areas such as pathophysiology and pharmacodynamics . In pharmacodynamics and toxicology ( particularly in chronic toxicity testing ) , for instance , it might be applied to assess treatment effects more accurately by profiling metabolite levels over time instead of looking at end-points only ( see [29] ) . In many complex diseases , the dynamic analysis may well identify more meaningful biomarkers and reveal a deeper insight into the actual pathomechanisms . To name one important example that is actually very close to the present study: in chronic obstructive pulmonary disease ( COPD ) , physical exercise—and bicycle ergometry in particular—is commonly used to assess the severity of the disease and also to model exacerbations of the patients’ condition [61 , 62] . In this setting , a dynamic depiction of the metabolic changes clearly has the potential to resolve regulatory mechanisms and distinguish cause and effect of the observed alterations ( Christian Schudt , personal communication ) . This is especially plausible for the pathway leading to the synthesis of inflammation mediators such as prostaglandins , leukotrienes , thromboxanes etc . , which is closely associated with the pathology of the disease and depends on the release of polyunsaturated fatty acids from phospholipids in a stoichiometric manner [63–66] . In this article , main focus was put on the development of a computational methodology to examine longitudinal metabolic concentration data and to present a basic approach for the mathematical modeling and statistical analysis of dynamic kinetic metabolic mechanisms . As previously stated ( see section Methodology ) , individual metabolic response patterns are partly influenced by different factors such as physical fitness and training status , anthropometric parameters or dietary habits . Because of limitations in the specification and verification of the observed metabolic kinetic patterns , a further research goal might be to systematically investigate the underlying metabolic and physiological regulatory mechanisms by conducting additional hypothesis-driven prospective cohort studies . Furthermore , an extension of this paper is planned that will compare specific groups of interest , e . g . , defined with regard to training status ( response in lactate increases ) or anthropometric characteristics . Referring to the practical execution of exercise physiology experiments , it should be noted that most commonly only one blood sample is collected , usually after the end of exercise . However , the results of the presented work clearly demonstrate that characterized metabolites show a very differential kinetic characteristic during physical activity . Consequently one-point measurements may lead to misinterpretations and emphasize an obvious need for multiple measurements in exercise physiology ( typically before , multiple times during , and after exercise ) .
This study was conducted in full accordance with the principles expressed in the Declaration of Helsinki . Written informed consent was obtained from all study participants , together with a detailed questionnaire on nutrition and health status . In addition , a physician subjected all individuals to a detailed examination to ensure that they could undergo the cycle ergometry test without health risks , and this physician was also present at all times during the exercise to monitor the electrocardiogram ( ECG ) that was continuously recorded . All laboratory work and data analysis was conducted anonymously . In this work , longitudinal metabolic concentration data were obtained through clinical exercise testing using a cycle ergometry stress test . General guidance for clinical exercise testing can be found in "Guidelines for Clinical Exercise Testing Laboratories" [67] and "Recommendations for Clinical Exercise Laboratories" [68] . General recommendations for cycle ergometry studies were described by Driss & Vandewalle , 2013 [69] , providing technical and clinical protocols including limitations for study design and execution . The overall cycle ergometry experiment was designed as a longitudinal biomarker cohort study , with 47 persons divided into 4 different groups , i . e . , male and female individuals , with either average physical activity or competitive athletic activity . Study participants included amateur endurance athletes ( 16 males / 8 females ) and professional alpine skiers ( 11 males / 12 females ) . The anthropometric characteristics of the study participants ( age , body mass index ( BMI ) , height , and weight ) are summarized in Table 3 . Detailed information on anthropometric data , the general training status , and the physical load during the cycle ergometer experiment are provided as supporting information ( S3 File ) . The workload of the cycle ergometry test was increased incrementally by 25 W every 3 minutes up to the individual’s maximum physical load ( the basic scheme of the study protocol is depicted in S1 Fig ) . The initial workload level of 25 W was skipped for all individuals , starting the exercise with a workload of 50 W . The lowest observed maximum workload was 150 W ( one individual ) , and the highest workload level was 425 W , also reached by one individual . From each individual blood samples for metabolite profiling were taken ( i ) at rest ( directly before starting the exercise ) , ( ii ) with each new workload level up to individual’s maximum physical load , and ( iii ) after a short recovery phase of five minutes after the maximum workload ( highest Watt level ) . In addition , for all test subjects , lactate concentrations were measured as a gold standard and reference for assessing physical activity . Concentration-time curves of preprocessed lactate data are visualized in S2 Fig . Median values of lactate concentrations were roughly 1 . 2 mM at rest , 8 . 5 mM at maximum workload , and 7 . 2 mM after recovery . According to the study protocol , lactate samples were taken at 1:30 min , samples for metabolite profiling at 2:30 min after starting a new ergometry workload level . All samples were taken from the earlobe , collected as dried blood spots ( DBS ) [57] and analyzed under standardized study conditions . In metabolomics , two basic conceptual approaches are used: untargeted and targeted metabolite profiling methods . Untargeted metabolomics seeks to create a holistic picture of metabolism by trying to identify a comprehensive set of metabolites as a snapshot of a metabolic state , while targeted metabolomics aims at a quantitation of pre-selected metabolites defined by a priori knowledge [70 , 71] . The two state-of-the-art technologies for analyzing metabolites are nuclear magnetic resonance ( NMR ) spectroscopy [72] and mass spectrometry ( MS ) [73] . Dynamic time-course metabolic concentration values , building the basis for data analysis and modeling in this work , were gathered from a targeted metabolomics approach [70 , 74 , 75] , using triple quadrupole tandem mass spectrometry ( MS/MS ) [76] coupled with the concept of stable isotope dilution ( SID ) [77] for metabolite quantitation . Longitudinal metabolite concentration data were quantified for three classes of metabolites: acylcarnitines , amino acids , and sugars . In total , 110 metabolites were measured: 40 acylcarnitines , 18 amino acids , and 52 sugars . Quantitated concentration data of all measured metabolites were thoroughly examined with respect to data quality assurance and reliability . Metabolites either below the detection limit ( LOD ) of 50 nM , measurements with lots of missing values or wide variabilities were excluded from this analysis . As result , targeted concentration data of a selected set of 30 metabolites are considered for data analysis in this work: 11 acylcarnitines , 18 amino acids , and 1 sugar . Analyzed acylcarnitines include: carnitine ( C0 ) , acetylcarnitine ( C2 ) , propionylcarnitine ( C3 ) , methylmalonylcarnitine ( C3-DC-M ) , butyrylcarnitine ( C4 ) , valerylcarnitine ( C5 ) , hydroxyvalerylcarnitine ( C5-OH ) , hexadecanoylcarnitine ( C16 ) , octadecanoylcarnitine ( C18 ) , octadecenoylcarnitine ( C18:1 ) , and octadecadienylcarnitine ( C18:2 ) . Amino acids are: alanine , arginine , aspartic acid , citrulline , glutamic acid , glycine , histidine , lysine , methionine , ornithine , phenylalanine , proline , serine , threonine , tryptophan , tyrosine , valine , and xleucine ( the sum of leucine and isoleucine ) . Analyzed metabolite within the class of sugars was glucose . Collected data were almost complete , except some missing data at individual’s maximum load ( twelve individuals , however lactate could be measured after 1:30 min for all of them ) , and at 150 W for one test person ( no . 9 ) . Central steps of the selected data analysis workflow include the technical validation of raw data , preprocessing of data , selection of putative dynamic biomarker candidates , mathematical modeling and characterization of metabolite kinetic patterns , identification of metabolite groups with similar kinetic behavior , specification of observed kinetic shape templates , classification of dynamic biomarker candidates and the biochemical interpretation of findings . A flowchart of the used data analysis workflow is shown in Fig 6 , representing the whole data-driven process for the discovery of biomarkers in metabolomics . Results from the different steps of the data analysis workflow are exemplarily shown and visualized for glucose , a key analyte , playing a central role in metabolism of exercise physiology and demonstrating a very specific kinetic pattern in response to physical activity . Raw data of the cycle ergometry experiment were test-wise reviewed and visualized in two different basic ways to obtain a better understanding about the nature of the metabolic time-course data . Concentration data were initially analyzed by building subsets of data , referring to the levels of each individual’s maximum physical load . For each subset a box plot was generated , visualizing the specific measurements ( data points of the horizontal axis ) versus the metabolite concentrations ( see section Clinical study execution ) . In S3 Fig , resulting box plots for glucose are exemplarily shown . Eight box plots were generated , where the lowest value of individual maximum workload ( 150 W ) resulted in 7 data points ( 1 test person ) and the highest value ( 425 W ) in 18 measurement points ( 1 test person ) . Second , analyzed metabolites were visualized as raw concentration curves ( exemplarily shown for glucose in S4 Fig ) , illustrating differences in individual workload and time of exercise of examined test persons . The horizontal axis hereby represents time points of measurements in minutes . Different lengths of metabolic concentration-time curves , resulting from the variability of each individual’s maximum physical load , were made comparable by rescaling the data in time ( S5 Fig ) . Measurement at rest was defined as 0% , maximum workload of each individual as 100% and recovery value as median value of 117%—resulting in an aligned workload curve to a uniform length . This requires additional data points added to the concentration curves using a linear interpolation approach ( Fig 7A ) . Metabolic concentration-time curves underwent simple descriptive analysis by generating a box plot representation from rescaled concentration curves ( Fig 7B ) . In a next step , median concentration values were extracted from interpolated concentration curves ( S6 Fig ) , serving as a basis for mathematical modeling by curve fitting ( see section Mathematical modeling ) . This approach perfectly treats the problem of outliers in the data without the need of applying additional methods for outlier detection and removal . However , a small set of extreme outliers was observed that was manually removed after careful visual inspection ( in test person no . 14 all data points at recovery , in test person no . 35 all data points at 175 W and in test person no . 42 the data point for glucose at rest ) . Regarding missing concentration values it should be noted that our dataset was almost complete , except missing values at individuals’ maximum workload in 12 test persons and at 150 W in one individual ( no . 9 ) , representing the last data points in the concentration time curves . Maximum fold changes in metabolite concentrations and P-values of statistical hypothesis testing serve as a score for the ranking of putative biomarker candidates ( see section Selection of dynamic biomarker candidates ) . The combination of fold changes and P-values , visualized using a volcano plot , is described in the literature as method of choice for the analysis and visualization of significant changes ( e . g . , on microarray data [78 , 79] or in diverse metabolomics applications [80–82] ) . As a general approach , especially in genomics studies , this method is usually used for data comparing the starting and end point of dynamic processes such as regulation of gene expression . In this work , utilizing longitudinal time course concentration data , MFCs are calculated by the difference between observed minimum and maximum concentration values of a metabolite , independently from their timely occurrence . MFCs are calculated based on median concentration values extracted from interpolated concentration curves ( see section Data preprocessing ) . Measurement indices are determined , and consequently , if the minimum concentration occurs earlier in the time course , the ratio of maximum concentration to minimum concentration is calculated and vice versa . This modality is summarized in the following pseudo-code: if ( conc_min_index < conc_max_index ) maximum_fold_change=conc_max/conc_min ( 5 ) else maximum_fold_change=conc_min/conc_max ( 6 ) P-values of statistical hypothesis testing are calculated in a similar way , first by determining measurement index positions of minimum and maximum median concentration values of interpolated concentration curves and in a subsequent step , by extracting interpolated individual concentration values at identified index positions as basis for statistical hypothesis testing . Interpolated minimum and maximum concentration values of all 30 metabolites were assessed with respect to their density distribution by visual inspection using graphical methods such as histogram analysis [83] and quantile-quantile plots [84] . A Shapiro-Wilk Normality test was applied for normality testing of both minimum and maximum concentration data ( significance level P = 0 . 01 ) [85–87] . Metabolites hereby yielded inhomogeneous distributions ( e . g . , normal distribution for histidine , octadecanoylcarnitine ( C18 ) or glycine , non-normal distribution e . g . , for xLeucine , citrulline or proline , and partly differences in distributions between minimum and maximum concentrations , e . g . , for arginine ) . To ensure comparability between metabolites , a Wilcoxon Signed Rank Test [88] ( non-parametric hypothesis test for paired samples ) was used for the calculation of P-values ( significance level P = 0 . 001 ) . Since ranks are used for paired hypothesis testing , identical P-values are partly shown for some metabolites . Finally , calculated P-values were adjusted according to the false discovery rate ( FDR ) correction for multiple comparisons [89] . The initial goal of our work was the mathematical modeling of metabolite kinetic patterns and shape templates , utilizing a set of predefined mathematical basis functions [29] . However , the introduction of predefined basic functions for the analysis of dynamic metabolomics data is and remains a challenge as also discussed by Smilde et al . , 2010 [29] . Note that putative basic functions in this work are associated with kinetic patterns in response to linear increasing physical activity and can be basically classified into the following set of shape templates: Fitting the above-introduced basic functions to measured concentration-time curves was thoroughly examined and tested with the goal to characterize kinetic response patterns according to these theoretical models . In this analysis curve fitting was performed using median metabolite concentration values , extracted from interpolated concentration-time curves ( see section Data preprocessing ) . Our preliminary results demonstrated that the approach of fitting the pre-defined set of mathematical basis functions was not feasible for the measured response curves caused by an incremental increase of physical workload . We therefore revised our initial concept by utilizing polynomial fitting of preprocessed data . This modality enables us to design kinetic response patterns that are physiologically reasonable and relevant . Polynomials of degree n are defined by following equation: f ( x ) =∑i=0naixi ( 13 ) After testing different polynomial degrees , we decided for a degree of nine , showing the best results in terms of curve/shape representation and smoothness ( S7 Fig ) . To ensure comparability of analyzed metabolites after polynomial fitting , relative concentration values were calculated ( in percentage of concentration changes with respect to the initial concentration at rest ) ( see Fig 4 ) . Note that there are multiple applications in metabolomics using polynomial fitting , e . g . for baseline correction [92 , 93] , prediction of germination curves [94] , calculation of mass correction profiles [95] or in spectrum deconvolution [96] . Metabolite groups , showing similar kinetic response patterns , were examined and identified using hierarchical cluster analysis [97] . Cluster analysis was performed based on the concentration values of the fitted polynomials of 9th degree ( see section Mathematical modeling ) . Results are visualized as a heatmap in Fig 8 . Relative workload values of the x-axis are displayed in linear order . Red colors indicate lower values in dynamic time-course concentrations of specific metabolites , lighter colors indicate higher concentration values . The resulting cluster dendrogram is separately shown in S8 Fig . Clusters of metabolites , showing similar dynamic behavior , were empirically identified by cutting the hierarchical tree at a threshold of 35 , resulting in seven different metabolite clusters ( see section Identification of metabolite groups with similar patterns ) . Descriptive statistical analysis for each cluster was performed and corresponding box plots were generated ( S9 Fig ) . Median concentration curves of each cluster , allowing for an accurate representation and specification of kinetic shape templates , were selected ( S10 Fig ) ( see section Specification of kinetic shape templates ) . | Human metabolism is controlled through basic kinetic regulatory mechanisms , where the overall system aims to maintain a state of homeostasis . In response to external perturbations , such as environmental influences , nutrition or physical exercise , circulating metabolites show specific kinetic response patterns , which can be computationally modeled . In this work , we searched for dynamic metabolic biomarker candidates and analyzed specific kinetic mechanisms from longitudinal metabolic concentration data , obtained through a cycle ergometry stress test . In total , 110 metabolites measured from blood samples of 47 individuals were analyzed using tandem mass spectrometry ( MS/MS ) . Dynamic biomarker candidates could be selected based on the amplitudes of changes in metabolite concentrations and the significance of statistical hypothesis testing . We were able to characterize specific kinetic patterns for groups of similarly behaving metabolites . Kinetic shape templates were identified , defining basic kinetic response patterns to physical exercise , such as sustained , early , late and other shape forms . The presented approach contributes to a better understanding of ( patho ) physiological biochemical mechanisms in human health , disease or during drug therapy , by offering tools for classifying dynamic biomarker candidates and for modeling and characterizing kinetic regulatory mechanisms from longitudinal experimental data . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity |
Rift Valley fever is an acute , zoonotic viral disease of domestic ruminants , caused by a phlebovirus ( Bunyaviridae family ) . A large outbreak occurred in Madagascar in 2008–2009 . The goal of the present study was to evaluate the point prevalence of antibodies against Rift Valley Fever Virus ( RVFV ) in cattle in the Anjozorobe district , located in the wet and temperate highland region of Madagascar and yet heavily affected by the disease , and analyse environmental and trade factors potentially linked to RVFV transmission . A serological study was performed in 2009 in 894 bovines . For each bovine , the following variables were recorded: age , location of the night pen , minimum distance from the pen to the nearest water point and the forest , nearest water point type , and herd replacement practices . The serological data were analyzed using a generalized linear mixed model . The overall anti-RVFV IgG seroprevalence rate was 28% [CI95% 25–31] . Age was statistically linked to prevalence ( p = 10−4 ) , being consistent with a recurrent RVFV circulation . Distance from the night pen to the nearest water point was a protective factor ( p = 5 . 10−3 ) , which would be compatible with a substantial part of the virus transmission being carried out by nocturnal mosquito vectors . However , water point type did not influence the risk of infection: several mosquito species are probably involved . Cattle belonging to owners who purchase animals to renew the herd were significantly more likely to have seroconverted than others ( p = 0 . 04 ) : cattle trade may contribute to the introduction of the virus in this area . The minimum distance of the night pen to the forest was not linked to the prevalence . This is the first evidence of a recurrent transmission of RVFV in such an ecosystem that associates a wet , temperate climate , high altitude , paddy fields , and vicinity to a dense rain forest . Persistence mechanisms need to be further investigated .
Rift Valley fever ( RVF ) is an acute , zoonotic viral disease , caused by a phlebovirus belonging to the Bunyaviridae family [1] . It mainly affects domestic ruminants such as sheep , goats and cattle [2] . The main clinical signs of the disease are high mortality rates , especially in new-born sheep and goats , and abortion in pregnant animals . Humans can develop RVF after exposure to tissues , blood or body fluids or through the bite of an infected mosquito . Infection in humans is usually associated with moderate influenza-like illness , but severe complications occur in a small proportion of patients in which the death rate may be high . RVF virus ( RVFV ) is transmitted from ruminant to ruminant either by mosquitoes – the main mosquito vectors being from the Aedes and Culex genera [3] , or theoretically , but never demonstrated , through direct contact . The respective contribution of both transmission routes remain unevaluated and probably vary from one ecological context to another . Veterinary inactivated and attenuated vaccines exist , but they are not widely used , and there is no treatment , either for humans or domestic animals . The disease is endemic in numerous African countries . A large epidemic occurred in 2006–2007 in the Horn of Africa , first in Kenya [4] , Tanzania and Somalia [5] , then in Sudan [6] . The last outbreaks occurred in Madagascar in 2008 [7] and South Africa in 2010 [8] . Sporadic animal cases were also reported in Botswana [9] and Namibia [10] . The epidemiology of RVF is complex and only partially understood . The disease was reported in three epidemiological systems: ( i ) dambo areas ( East , and some parts of Southern Africa where there are referred to as pans ) , ( ii ) semi-arid areas , and ( iii ) irrigated areas . Dambos are shallow depressions , often located near rivers , which fill with water during the rainy season . In these regions , a correlation between heavy rainfall and RVF outbreaks was clearly demonstrated [11] . Transmission from one mosquito generation to another , namely “vertical transmission” has been demonstrated with Aedes ( Neomelaniconion ) mcintoshi [12] . In addition , the virus may survive in desiccated eggs during inter-epizootic and/or dry/cold periods . Thanks to these two mechanisms , and to extreme rainy events , the disease may re-emerge every 5 to 15 years with only few seroconversion signs or reported clinical cases during the inter-epizootic period [13] , [14] . The semi-arid areas in which the disease has been reported are characterized by temporary water points , such as found in northern Senegal or Mauritania . In these areas , the virus persistence mechanisms remain unclear . They could be related to the survival of the virus in Aedes mosquitoes , as demonstrated in East Africa , or to the regular introduction of the virus by nomadic herds coming from neighbouring endemic areas . Neither possibility is mutually exclusive [15] . The irrigated areas concerned include the Nile delta ( Egypt ) and the Senegal River valley ( Senegal , Mauritania ) , where permanent water bodies favor the development of Culex populations , and thus year –long viral transmission [16] . In some ecosystems such as South Africa or Zimbabwe [17] , [18] , virus circulation also could be maintained between mosquito vectors and wild small or large mammals in sylvatic cycles . In Madagascar , RVFV was isolated for the first time in 1979 from pools of mosquitoes captured during the rainy season in the primary rain forest of Perinet , Moramanga district [19] . Human and animal RVF outbreaks occurred during the rainy season in Vavatenina and Fenoarivo Antsinanana districts in March 1990 and around Antananarivo , the capital , from February to April 1991 [20] . Antigenic and molecular analysis of isolates showed that RVFV strains obtained in 1979 were closely related to both Egyptian 1979 isolates and Zimbabwean 1974 isolates , while those isolated in 1991 were closer to eastern/central African strains [20]–[22] . The first human RVF case of the 2008 outbreak was reported in January in Tolagnaro city , southern Madagascar , from specimen collected at the sentinel surveillance site . By 15 June 2008 , the Ministry of Health of Madagascar had reported 417 suspected RVF cases , 59 laboratory confirmed human cases , and 19 deaths suspected to be due to RVF infection [7] . Most regions of the island were infected . Anjozorobe district was heavily affected by the outbreak ( Reynes JM , personal communication ) . This region , located 80 km north of Antananarivo , is part of the wet and temperate highland region of Madagascar . It is composed of a dense , evergreen forest and an agricultural zone , where there are rice fields favorable to Culex mosquito populations and livestock farming is widespread . Due to a rather cool weather during winter , a continuous transmission of the virus between mosquitoes and cattle is unlikely . As suspected in other parts of the world ( e . g . , bats in Guinea [23] and rodents in Senegal and South Africa [17] , [24] , [25] ) , the existence of a wild reservoir located in the forest may explain the persistence of the virus during inter-epizootic periods and the recurrence of the disease in this region . Alternatively , livestock trade may be involved in this resurgence given that the Anjozorobe region is connected to most of the important breeding areas in the country . The goal of the present study was to evaluate the point prevalence rate of antibodies against RVFV in cattle in the Anjozorobe district and identify environmental and trade factors potentially linked to RVFV transmission to infer epidemiological implications of RVFV circulation and persistence in this area .
The study area is located within the Anjozorobe district , 80 km north of Antananarivo , the capital of Madagascar Island ( defined by the geographical coordinates of the Figure 1 ) . This region holds some of the last large and unfragmented remnants of the central highland's natural ecosystems , including highland forests , watersheds and lakes ( Figure 1 ) . The study area , mainly composed of wetlands , rice fields , and crop fields lies beside the Anjozorobe forest corridor which is one of the last vestiges of dense rain forest in Madagascar . Two types of forest are present: high altitude humid forest ( over 1 , 500 m ) and mountain humid forest ( 800–1 , 500 m ) . The climate is temperate and wet , characterized by a cold season with frequent but slight rainfall , from April to September , and a warm , wet season with high rainfall , from October to April . The average annual temperature is 18°C . November is the warmest month , with an average maximum temperature of 27°C , and August the coldest with an average minimum temperature of 9°C [26] . The forest corridor is on the continental divide line between the east and west side of Madagascar Island . The region is crossed by many water systems that constitute an important water resource irrigating the surrounding regions [26] . In this area , livestock farming , largely of cattle , is crucial for the local population's subsistence , contributing directly and indirectly to food security and nutrition . Livestock provide products ( milk and meat ) for consumption , and is a source of valuable goods and services , e . g . transport , manure for fertilizing , ploughing , rice stamping and income from trade of products . Cattle are also slaughtered regularly for religious feasts and are used as a form of savings . In collaboration with the Malagasy Veterinary Services , an exhaustive census of cattle herds was performed in the study area in May 2009 . Meetings were organized with farmers to explain the goals of the study and the decision to participate was taken at the village level . Informed consent was given orally and documented in questionnaires . For cultural reasons , written consent could not be obtained . The size of the cattle population in this area was estimated by the Veterinary Services to be 2 , 000 animals . Thus , considering a design effect of 2 that takes into account the village clustering , and to estimate a point prevalence of 20% with a 95% level of confidence , we needed to sample at least 1 , 020 animals ( exact error 3% ) . In each participating village , blood samples were collected from randomly chosen cattle . Each participating owner was the source of data collected in a standardized questionnaire . The age of each sampled animal was recorded . The potential role of 3 environmental risk factors was investigated: the minimum distance from the night pen to the nearest water point , the type of the nearest water point , and the minimum distance from the night pen to the nearest forest boundary . The exact locations of the night pens and the distances from these night pens to the nearest water point and nearest forest boundary were recorded and calculated using a Global Positioning System ( GPS ) device . With regards to the type of water point , 3 modalities were recorded , namely “pond” , “rice field” and “river” . In addition to the 3 above–mentioned parameters , owners were questioned about their herd replacement practices . The binary variable -auto-renewal vs purchase- was recorded . When purchased , the exact origin of the cattle could not be obtained . However most of them were bought in the Anjozorobe area ( H . Rasamoelina , pers . com ) . In the field , blood samples were centrifuged after collection , then transported to the Institut Pasteur in Madagascar ( Antananarivo ) and stored at −20°C until they were analysed . Samples were tested for anti-RVFV immunoglobulin ( Ig ) M and IgG using a previously described ELISA test [7] , [27] . The ELISA assays were completed by using inactivated RVFV-infected vero E6 cell antigens and uninfected Vero E6 cell antigens . Each serum was 4-fold diluted , namely 1∶100 , 1∶400 , 1∶1600 and 1∶6400 . Samples were considered positive only if the adjusted sum of optical densities , defined for each dilution as the difference between the cumulative sum of optical densities minus the background absorbance of uninfected control Vero E6 cells , and the titers were above pre-established conservative cut-off values , respectively ≥0 . 75 and ≥400 for IgM and ≥0 . 95 and ≥400 for IgG . The serological data were analyzed using a generalized linear mixed model ( glmmML library , R software ) , where the individual serological status was the binomial response , and the previously mentioned variables ( age , minimum distance from the night pen to the nearest water point type , minimum distance from the night pen to the nearest forest boundary , type of the nearest water point , and herd replacement practices ) were the explicative factors . The breeder was included as a random effect to take into account the clustering of sampled animals . The significance of the cluster effect was tested using a bootstrap approach ( n = 2000 ) [28] .
Due to field constraints , the provisional sampling could not be achieved: a total of 894 bovines were sampled between early May and mid-June 2009 , belonging to 258 breeders coming from 43 villages of 51 villages existing in the area ( See online information file , Table S1 ) . Cattle ages ranged from 1 to 18 years , with the majority of sampled animals less than 8 years old ( Figure 2 ) . Overall anti-RVFV IgG seroprevalence rate was 28% [IC95% 25–31] ( See online information file , Table S1 ) . This rate varied among villages , from 0 to 71 . 4% ( See online information file , Table S1 ) . The overall anti-RVFV IgM seroprevalence rate was 0 . 8% [IC95% 0 . 0–1 . 0] . The 7 anti-RVFV IgM positive animals were distributed among herds from 6 villages and 5 of the animals belonged to breeders that do not purchase new animals to renew their herd . The IgG seropositivity rate of animals was statistically linked to age ( p = 0 . 0001 ) with an OR of 3 . 4 for an age difference of 5 years suggesting a recurrent and intense RVFV circulation in this area ( Table 1 ) . The minimum distance to the nearest water point ranged from 10 to 3 , 000 meters . This distance was a protective factor ( p = 0 . 005 ) since prevalence rate was negatively correlated to the distance . The odds of seropositivity were divided approximately by 10 when the distance to the nearest water point was increased by 500 meters ( OR: 0 . 08 , Table 1 ) . Five hundred thirty three bovines belonged to breeders that did not purchase any animal . The anti-RVFV IgG seroprevalence within this population was 27 . 8% . The anti-RVFV IgG seroprevalence of bovines belonging to breeders that purchase to renew their herd was 28 . 1% . In the multivariate model , belonging to owners who buy animals to renew ( at least partially ) their herd was a risk factor ( p = 0 . 04 ) . The minimum distance of the night pen to the forest ranged from 100 to 10 , 000 meters . This latter parameter as well as the water point type had no effect on the prevalence rate . The breeder random effect was not significant ( p = 0 . 06 ) .
The overall observed anti-RVFV IgG prevalence was concordant with a serosurvey performed after the 1991 outbreak in Mangamila , located 20 kms south of Anjozorobe [29] . Similarly , a national serosurvey was performed after the 2008 outbreak: the seroprevalence rate was estimated to be 25 . 8% and 24 . 7% respectively in cattle ( n = 3437 ) and small domestic ruminants ( n = 989 ) [30] . Only 7 bovines were found positive for IgM against RVFV . In the majority of cases , anti-RVFV IgM antibodies do not persist beyond the 50th day after infection [31] , [32] . The sampling of the anti-RVFV IgM positive bovines was performed between early May and mid-June 2009 . This suggests that these infections most probably occurred between early February 2009 , and mid March , corresponding to the middle of the wet , warm season ( October to April ) and the apparent end of the second transmission wave . A high herd immunity level induced by the first outbreak in 2008 associated with an early elimination of IgM might explain this small number of new infections . Five of these 7 anti-RVFV IgM positive bovines belonged to breeders that do not purchase to renew their herds: these 5 infections were caused by local viral activity . The first potential risk factor was the minimum distance to the nearest water point . The main known RVFV vectors are from Culex and Aedes genera whose main activity period is crepuscular and nocturnal [33]: given that cattle come back from field in late afternoon and spend the night in pens , we assume that the pens are where infection by mosquito bites occurs . The second potential risk factor was the minimum distance to the forest . The existence of a sylvatic cycle between mosquitoes and wild reservoirs living in the forest could explain the persistence and the re-emergence of the virus in the area . In that case , bovines living close to the forest would be more exposed to infectious mosquito bites than others . The water point type was identified as a third potential risk factor . Indeed , the ecology of Culex and Aedes mosquito vectors is rather different and closely related to the water point filling and drying rhythm . Aedes females lay their eggs on the muddy banks of ponds . These eggs may survive several years in desiccated mud . When flooded again during pond filling , there is a massive hatch of eggs . In contrast , Culex eggs cannot survive to desiccation , and need to be permanently in water to develop and hatch [33] . An increased distance to the nearest water point appears to be a protecting factor , suggesting that a substantial part of the virus transmission could be carried out by mosquito vectors . As a matter of fact , 6 mosquito genera , namely Aedes , Anopheles , Coquillettidia , Culex , Eretmapodites and Mansonia have been proven to be capable of RVFV infection and transmission in the laboratory and/or were found infected in the wild [34]–[36] . These genera are all present in Madagascar [19] , [37] . Among them , unfed females of 3 species have been found infected by RVFV in another part of the highlands , the Fianarantsoa region , located 400 km far from the Anjozorobe area: An . coustani , An . squamosus , and Cx . antennatus [38] . An . coustani and An . squamosus were found infected in Madagascar in 1979 [37] and Cx . antennatus in Kenya from 1981 to 1984 [12] . However vector competence was experimentally demonstrated only for Cx . antennatus in Egypt [39] . According to our results , the type of water point has no effect on the prevalence rate . This corroborates the assumption that several mosquito species with different biology and ecology may be involved in the transmission cycle in this area: paddy fields are favourable to An . coustani and Cx . antennatus [40] whereas water-filled hoofprints in the stream bank favour the development of An . squamosus [41] . Further entomological studies are needed to confirm this assumption and the involvement of these mosquito species in the RVF epidemiological cycle in Madagascar highlands . The potential role of small mammals as a RVFV reservoir , especially rodents , has been suspected but never demonstrated . A high mortality rate among rodents ( Arvicanthis abyssinicus nairobae and Rattus rattus kijabius ) was observed on farms affected during the 1930 epizootic in Kenya [2] . The existence of viraemia was demonstrated in Arvicanthis abyssinicus after inoculation with RVFV [42] . In Egypt , RVFV was detected by RT-PCR in the blood of 29 Rattus rattus individuals among 300 sampled [43] . Serological evidence of RVFV infection also was observed in Mastomys sp . , Arvicanthis niloticus and Aethomys namaquensis in Senegal [24] . In South Africa , serological and experimental studies showed that Aethomys namaquensis can act as an amplifying host for RVFV during inter-epizootic periods [17] . Given high biodiversity of rodents and small mammals in the Anjozorobe forest corridor , including an important Rattus rattus population [26] , the persistence and the resurgence in 2008 of the RVFV in this particular ecosystem could be explained by the existence of a wild reservoir and a sylvatic cycle involving vectors that preferentially feed on rodents and occasionally feed on cattle , thereby acting as bridge vectors . However , our results clearly show that livestock living close to the forest or even grazing in the forest have the same level of exposure as livestock that do not live close to or graze in the forest . To date no molecular or serological signature was detected on rodents or small mammals of the area , but ongoing research is examining the hypothesis . Ruminant trade has often been associated with local , regional , even continental dissemination of RVFV , as described from Sudan to Egypt during the 1970s [44] , and from the Horn of Africa to the Arabian Peninsula in 2000 [45] . Regarding the Anjozorobe area , bovines belonging to owners who replace their herds by purchasing animals were significantly more antibody-positive than others: animal introduction in a herd is a risk factor and the virus may , conceivably , be introduced by a viraemic animal , coming from either another village in the study area or a more distant location . In both cases , the transmission to the cattle in the herd may occur either by a direct or vectorial route . Due to the lack of data on bovine origins , the extent to which these introductions participate in the maintenance of the RVF cycle in the Anjozorobe area remains unknown . The spatial clustering of sampled bovines was taken into account including a breeder random effect in the model . Indeed we considered that the level of exposition to infection of bovines parked in the same night pen was correlated , whether this infection occurs by mosquito bites or direct contact . Statistical analyses showed that this effect was not significant . This is the first serological assessment of RVFV transmission mechanisms in such an ecological context , which associates a wet , temperate climate , high altitude with mountainous reliefs , paddy fields , and vicinity to a dense rain forest . The epidemiological cycle probably involves several vectors – at least from Aedes , Culex , and Anopheles genera - and a combination of different mechanisms for virus persistence and diffusion , their respective importance varying with the season , the prevalence rate of the cattle , and the dates of religious festivals that increase the cattle trade flow . As shown in previous studies [7] , [30] , the disease circulates in different ecozones of the country , including a Sahel-like ecosystem in the south , to the very moist lowlands of the eastern coast , the moist lowland of the northwest region and the temperate climate of the central highlands . Jeanmaire et al . ( 2011 ) suggested that RVFV circulation was endemic in both the southern and north-western areas , and that these two areas may act as a virus source for the rest of the country [30] . The large distribution of the disease would then be explained by a large diffusion of the virus through the trade of bovines which is known to be extensive and sometimes uncontrolled in the island . Our results strongly suggest that RVFV circulation is also recurrent in the Anjozorobe area , suggesting a third RVF epidemiological system . Each epidemiological system may be linked to the others by the animal trade network . A global and yearlong circulation on the whole country could then be maintained by this network , itself possibly linked with other East-African countries , as suggested by recent molecular epidemiology results [46] . The reason why the disease re-emerged in 2008 in this area remains unknown and the risk of a new outbreak there has not been evaluated . Further studies should be carried out to describe and model this cycle in order to implement relevant surveillance , risk prediction and control measures . | Rift Valley fever ( RVF ) is a viral disease of domestic ruminants , which may affect humans . The RVF virus ( RVFV ) may be transmitted either by mosquitoes or through direct contact with vireamic body fluids or products . Until now , this disease had been described in arid , hot and irrigated or tropical areas . Performed in the year following the 2008–2009 RVFV outbreak in Madagascar , this study demonstrates for the first time a regular and intense transmission of this disease in a temperate and mountainous region . The area chosen as a pilot project shows that cattle are regularly and heavily affected in the highlands of Madagascar . Statistical analyses suggest that ( i ) a substantial part of the transmission is due to mosquito vectors; ( ii ) many mosquito species such as Culex and Anopheles , are probably involved in the transmission; ( iii ) cattle trade , by a regular introduction of the virus via herds coming from infected areas of the island , may explain the recurrence of the disease in this region . Further investigations are needed to understand the mechanisms of transmission of the disease , and design and implement appropriate surveillance and control measures in this area . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"veterinary",
"science"
] | 2011 | An Unexpected Recurrent Transmission of Rift Valley Fever Virus in Cattle in a Temperate and Mountainous Area of Madagascar |
Despite extensive genetic analysis , the evolutionary relationship between polar bears ( Ursus maritimus ) and brown bears ( U . arctos ) remains unclear . The two most recent comprehensive reports indicate a recent divergence with little subsequent admixture or a much more ancient divergence followed by extensive admixture . At the center of this controversy are the Alaskan ABC Islands brown bears that show evidence of shared ancestry with polar bears . We present an analysis of genome-wide sequence data for seven polar bears , one ABC Islands brown bear , one mainland Alaskan brown bear , and a black bear ( U . americanus ) , plus recently published datasets from other bears . Surprisingly , we find clear evidence for gene flow from polar bears into ABC Islands brown bears but no evidence of gene flow from brown bears into polar bears . Importantly , while polar bears contributed <1% of the autosomal genome of the ABC Islands brown bear , they contributed 6 . 5% of the X chromosome . The magnitude of sex-biased polar bear ancestry and the clear direction of gene flow suggest a model wherein the enigmatic ABC Island brown bears are the descendants of a polar bear population that was gradually converted into brown bears via male-dominated brown bear admixture . We present a model that reconciles heretofore conflicting genetic observations . We posit that the enigmatic ABC Islands brown bears derive from a population of polar bears likely stranded by the receding ice at the end of the last glacial period . Since then , male brown bear migration onto the island has gradually converted these bears into an admixed population whose phenotype and genotype are principally brown bear , except at mtDNA and X-linked loci . This process of genome erosion and conversion may be a common outcome when climate change or other forces cause a population to become isolated and then overrun by species with which it can hybridize .
Despite polar bears' clear morphological and behavioral adaptations to their arctic environment [1] , [2] , their genetic relationship to brown bears remains unclear [3] , [4] , [5] , [6] . Analysis of maternally inherited mitochondrial DNA ( mtDNA ) shows that polar bears fall within the range of variation of brown bears . Extant brown bears from Alaska's ABC ( Admiralty , Baranof and Chichagof ) Islands , some extinct brown bears from Ireland and mainland Alaska , and two ∼115 , 000-year-old polar bears share the mtDNA haplotype of all extant polar bears [3] , [7] , [8] , [9] , [10] , [11] . The time to most recent common ancestor ( TMRCA ) of this mtDNA haplotype has been estimated at ∼160 thousand years ago ( kya ) ( Figure S7 ) [3] , [6] , [9] , [10] . Recent analysis of data from a panel of brown and polar bears at 14 nuclear loci showed that polar bears are generally distinct from brown bears , with genomic TMRCA averaging ∼600 kya [4] . Under a simple population split model without subsequent admixture , the population divergence should be more recent than average genomic divergence and thus polar bears became a distinct species more recently than 600 kya . A separate recent genome sequencing survey concluded that brown bear and polar bear lineages are much older . Miller and colleagues concluded that the lineage that would become polar bears diverged from that which would become brown bears more than 4 million years ago , followed by admixture that continues to the present [6] . Consistent with this , the past and present geographic ranges of both species overlap at their margins ( Figure 1 ) , and fertile hybrids are known in both captive and wild populations [2] , [12] . The current consensus is that mtDNA and perhaps other polar bear loci are the result of past introgressions from brown bears into polar bears [3] , [4] , [6] . One scenario that has been proposed to reconcile the complicated discordance between the mtDNA trees and the species trees requires at least two instances of hybridization [3] . The first , which must have occurred before ∼115kya , passed the mtDNA haplotype from polar bears into brown bears , including the ancient Irish brown bears and ancestors of the ABC Island brown bears . The second passed this mtDNA haplotype back into polar bears , after which it came to fixation in all extant polar bears . This convoluted scenario is necessary if , in fact , polar bears derive their mtDNA haplotype and other loci from brown bears . Unfortunately , this prevailing consensus has gone unquestioned . Here , we present an analysis of published and newly generated genome-wide data for brown bears and polar bears . We find extensive evidence of previous admixture , from polar bears into brown bears , especially of X-linked genes .
To more fully delineate the genetic relationship between polar bears and brown bears , we sequenced random genomic shotgun libraries from seven polar bears , two brown bears and one black bear to learn the ancestral state for alleles ( Figure 1 , Text S1 ) . We mapped these reads to the assembled genome scaffolds of polar bear ( Text S1 ) [13] . Because the sequence coverage of each bear was uneven and too low to reliably call heterozygous sites , we down-sampled the sequence data from each bear to 1× . That is , we randomly picked a high-quality base from amongst all reads that mapped reliably at each position in the bear genome . In this way , we generated a composite haplotype for each bear and used these data for further analysis . To gauge the level of diversity within and divergence between bear species , we made pairwise comparison between each bear , in 50 kb windows , across the bear genome ( Figure 2 ) . In agreement with previous reports [4] , [14] , we find that polar bears are remarkably homogeneous: polar bear alleles differ at ∼4 sites in 10 , 000 . In contrast , brown bears have roughly four times as much genetic diversity , differing at ∼17 in 10 , 000 sites . We note that the level of diversity among brown bears is nearly as high as the divergence between brown and polar bears . As expected , polar bears and brown bears show similar pairwise genomic divergence from the black bear . Likewise , the polar bears , brown bears , and black bears all show similar genomic divergence from the giant panda ( Ailuropoda melanoleuca ) [15] . We quantified admixture between brown and polar bears using the D-statistic [16] . In brief , D is the excess fraction of derived alleles shared between one of two conspecific individuals with a candidate admixing individual ( Figure 3 ) . Note that both incomplete lineage sorting ( ILS ) and admixture can lead to sharing of derived alleles , in this case between polar bears and brown bears . ILS , being a stochastic process , will result in equivalent numbers of shared , derived alleles between any two brown bears and a polar bear . Admixture , on the other hand , will result in more shared , derived alleles in the more admixed bear . Thus , under the null model of no admixture , D = 0 . A significant non-zero value of D indicates more admixture with one of the two individuals . Comparison of any two polar bears for admixture with brown bears found little evidence for admixture . All D-statistics comparing two polar bears to a brown bear were statistically indistinguishable from 0 ( Figure 3 , top and middle panels ) . Conversely , D-statistic comparisons between the ABC Islands and mainland brown bears for polar bear admixture were consistently and equivalently non-zero ( Figure 3 , bottom ) , regardless of the polar bear used in the comparison ( D = 0 . 016 , which translates to roughly 0 . 75% of the genome; Z-score = 1 . 24 ) . Remarkably , when the analysis is restricted to the 12 scaffolds ( ∼74 Mb of sequence ) identified as X-chromosome ( Text S1 ) , D = 0 . 22 , or ∼6 . 5% of the X-chromosome ( Z-score = 4 . 52 ) ( Figure S2; Tables S3 , S4 , S5 ) . We find this same enrichment of the X chromosome , compared to the autosome , for admixture with polar bears when analyzing genome sequence data from two additional , recently published ABC Islands brown bears ( Figure S3 , Table S6 ) [6] . The ABC Islands bears therefore share not only their mtDNA but also a significant portion of their X-chromosomes with polar bears . A parsimonious explanation for these observations is that the same admixture event that resulted in sharing of the polar bear mtDNA haplotype with ABC Island brown bears also results in sharing of much of the X-chromosome . To test the direction of X-chromosome gene flow between polar bears and the ABC Islands bear we simulated the effect of having 6 . 5% ancestry ( roughly the amount estimated above ) in either polar bear or mainland brown bear X chromosome from the reciprocal species ( Figure 4 , Figure S5 ) . The simulation was carried out by randomly selecting 6 . 5% of the X-chromosome of the candidate recipient species to be replaced by sequence from the candidate donor species ( Figure S4 , Text S1 ) . We then measured the distribution of pairwise divergences that would result following this simulated admixture . Given the low genetic diversity within polar bears , this amount of brown bear ancestry would be clearly identifiable as an excess of deeply diverging regions between polar bears , even in unphased data from which a random allele is chosen at each site . Conversely , simulating 6 . 5% polar bear ancestry in the mainland brown bear X-chromosome is more consistent with the observed level of genomic regional divergence between brown bear X-chromosomes . Thus , we deduce that the direction of gene flow was from polar bear into the ABC Islands brown bear X-chromosome . Recently published genome sequence data from a ∼115ky polar bear [6] allow us to further probe when and in which direction admixture might have happened . Using this ancient polar bear in the D-statistic test gives nearly identical results to the extant polar bears ( autosome D = 0 . 015; X-chromosome D = 0 . 212 ) . That is , ABC island brown bears are equally enriched for polar bear matching derived alleles , even when this ∼115ky polar bear is used in the comparison . Therefore , if the admixture was from the ABC Island brown bears ( or a closely related population ) into polar bears , it must have occurred prior to ∼115ky . Furthermore , no significant subsequent admixture could have occurred , since the modern polar bears are nearly homogeneous for the ABC Islands brown bear D-statistic signal . Finally , if gene flow was from brown bears into polar bears , it would had to have been from a population of brown bears that lived more than ∼115kya that today finds itself restricted to a group of islands that only became habitable for brown bears since the end of the last glacial maximum , about ∼16kya . Given the unlikeliness of this scenario and the incompatibility of polar bear X-chromosomes genetic divergence with brown bear ancestry , we conclude that the direction of gene flow was from polar bears into the ABC Island brown bears .
The genome-wide analysis presented here indicates that ( 1 ) polar bears are a remarkably homogeneous species and show no evidence of brown bear ancestry , ( 2 ) the ABC Islands brown bears show clear evidence of polar bear ancestry , and ( 3 ) this polar bear ancestry of ABC Islands brown bears is conspicuously enriched in the X-chromosome . ABC Islands brown bears show a simple positive correlation between how maternally biased a genetic locus is ( mtDNA>X chromosome>autosomes ) and how much polar bear ancestry is present ( 100% , 6 . 5% , 1% ) . Given this observation , and our knowledge about the natural history of these islands through the Pleistocene and Holocene , we present the following model . During the peak of the last ice age , brown bears were likely absent from the region that now comprises the ABC Islands . Although fossil remains dating to this period are abundant on the more southerly islands of the Alexander Archipelago , brown bears are not among the species present during the period spanning 26-12kya , when glacial conditions were at their peak [17] , [18] , [19] , [20] . Geological and climatological data suggest that if any habitat suitable for brown bears persisted on the ABC Islands during the LGM it would have been limited to the western part of Baranof Island , the most distant of the ABC Islands from the Alaskan mainland [17] . By itself , however , this potential refugium would have been too small to support viable populations of brown bears [21] . Polar bears , alternately , would likely have colonized the sea ice adjacent to the ABC Islands as the ice advanced southward . Notably , marine mammals dominate the fossil remains dating to this interval [19] , including ringed seals , an ideal food source for polar bears [2] . As the climate warmed and ice retreated , polar bears may have been stranded on or near the ABC Islands . As the habitat became increasingly hospitable to brown bears [17] , the early colonizers from the mainland would have been predominantly the more peripatetic sub-adult males [14] . Admixture involving an influx of mostly or exclusively male brown bears with the stranded polar bears would have resulted in a gradual erosion of the polar bear genome within the isolated population . The sex bias of admixing brown bears would have made genomic erosion more rapid in the autosomes , confining the vestiges of polar bear ancestry in extant ABC Islands bears primarily to matrilineal-biased genetic loci ( Figure S12 ) . Our simplified model - little or no brown bear ancestry in polar bears and matrilineal-biased polar bear ancestry in the ABC Islands brown bears - is consistent with several important comparative genomic observations . First , mtDNA and nuclear genome diversity within both extant and a ∼115kya polar bear is extremely low . This low level of polar bear diversity is consistent with no admixture from brown bears . Brown bears , in contrast , show much higher levels of diversity including many deep genetic lineages that have not completely sorted since their population divergence from polar bears . The ABC Islands brown bears show genome-wide evidence of admixture with polar bears concentrated on the X chromosome . Importantly , the level of admixture inferred from D-statistic analyses is only compatible with polar bear admixture into the ABC Islands brown bear X chromosomes and not the other way around . Conveniently , this model explains the presence of the polar bear mtDNA haplotype in all ABC Islands brown bears: the mtDNA haplotype of the male brown bear immigrants is lost , regardless of how many male brown bear immigrants arrived . The model for historic admixture proposed here is distinct from the traditional framework for admixture , including the scenario involving early humans and Neandertals for which the D-statistic analysis was originally developed [16] , [22] . Usually , the goal is to find the signal of a potentially small amount of admixture from a single or few admixture episodes that took place many generations ago ( Figure S8 ) . While such a model is consistent with the ABC Islands brown bear autosomal D-statistic results , it is insufficient to explain the large difference in the X-chromosome or the fixation of the polar bear mtDNA haplotype in the ABC Islands brown bears ( Text S1 ) . In fact , reasonable parameter values for a model that assumes a single episode of admixture from polar bears into brown bears do not result in a ratio of D for the X and autosomes that exceeds 2 . 7; our observed ratio is ∼14 . Alternately , a long process of sex-biased immigration of brown bears into what was initially a polar bear population can result in much higher ratios of polar bear ancestry for the X and autosomes ( Table S8; Figures S9 , S10 , S11 ) , consistent with the empirical observations presented here . Spatially explicit modeling has been used to probe the dynamics of gene flow from introgression during species expansions [23] . These simulations have yielded insight into the often non-intuitive patterns seen in various loci such as the apparent asymmetry in gene flow from the native species into the invading species . An extension of this approach to incorporate a migration barrier to female , but not male , gene flow and a dwindling native population of polar bears , may more fully reveal the demographic details of the brown bear invasion . Of particular note , there is evidence that brown bear migration between the mainland and ABC Islands may be ongoing . Analysis of variation at 17 rapidly evolving microsatellite loci indicated that brown bears from Admiralty Island , the closest of the ABC Islands to the mainland , are more similar to mainland Alaskan brown bears than were bears from Baranof and Chichagof Islands [14] . Assuming no disruption of the salient features of this migration , its final state , which has not yet been realized , would be complete conversion of the population , i . e . , the fixation of brown bear alleles in all genomic loci in the ABC Island bears except the strictly maternal mtDNA . We note that our data cannot resolve the timing of the origin of polar bears as a distinct lineage . Such an estimate has been hindered mainly by the paucity of preserved ancient polar bear remains [5] , [24] , and consequent lack of fossil calibrations . However , our data do provide insight into the relative timing of divergence between the three bear lineages sampled here . To generate a hypothetical scenario for the timing of the origin of polar bears , we apply several previously suggested calibration strategies to our data ( Table 1; Figure 2B ) . Regardless of the calibration strategy applied , our data support a long interval between the initial divergence between black bears and the brown bear/polar bear lineage , and the later divergence between brown bears and polar bears . This is similar to that observed by Hailer et al [4] , and in contrast to the scenario predicted by the model of Miller et al [6] . From analysis of the data presented here , we infer that polar bears most likely became a distinct lineage sometime during the Pleistocene . This timing is consistent with previous molecular ( Table 1 ) and morphological [5] estimates . Polar bears and brown bears were clearly established as a morphologically distinct species by at least ∼115kya – the age of the oldest known polar bear fossil [10] , [24] . Regardless of this timing , our data suggest that polar bears have remained a small , distinct lineage since their origin ( Figure S6 ) , with lineage-specific adaptations reinforced by the ecological constraints of their extreme environment ( Text S1 , Table S7 ) [6] . Brown bears , in contrast , have had a larger effective population size ( Figure S6 ) , with segregating polymorphism that often predates their split with polar bears ( Figure 2B ) . The process of genomic erosion we propose here may not be unique to the stranded ABC Islands polar bears . Past changes in the distribution of polar ice , for example , may have also stranded polar bears or hybrids on present-day Ireland , explaining the appearance of polar bear mtDNA in the remains of extinct Irish brown bears [3] . Long-term climate change may often strand populations on islands or island-like habitats , such as lakes or mountain plateaus . If these stranded populations then hybridize with closely related immigrants , we predict substantial variability in the apparent level of admixture indicated by D-statistics . Furthermore , in the case of sex-biased immigration , the ratio of D-statistics for the X and autosomes will be highly dependent on the rate and duration of immigration .
We extracted DNA from nine of the ten bears in a modern DNA laboratory using the DNeasy Blood & Tissue Kit ( Qiagen ) according to the manufacturer's specifications . The historic Lancaster Sound polar bear ( Smithsonian Natural History Museum ID 512133; Table S1 ) was extracted in a dedicated ancient DNA laboratory at Penn State University that is geographically isolated from modern molecular biology research , using a column-based extraction protocol for ancient DNA [25] . We physically sheared the DNA of the modern bears using a Diagenode Bioruptor UCD-200 instrument . Fifty µl of each of the six modern polar bear extracts were transferred into 1 . 5 ml tubes and exposed to four rounds of sonication for 7 min , using the energy setting “HIGH” and an “ON/OFF interval” of 30 seconds . To attain a longer insert size , we slightly modified the procedure to include two 7-min rounds and one 5-min round of sonication for the brown bears , black bear , and second round of sequencing for two polar bears ( West Hudson Bay X3249106A; and Chukchi Sea UP08 . 010; Table S1 ) . We then purified and concentrated the extracts using the Agencourt AMPure XP PCR purification kit , according to manufacturer's instructions , and eluted in 20 µl of 1×TE , with 0 . 05% Tween20 . The historic bear sample was already fragmented due to degradation , and was not sonicated . We prepared indexed Illumina libraries using 15 µl of each extract following the protocol described in [26] , with reaction volumes scaled to total volume of 40 µl . To verify final DNA concentration and the distribution of insert sizes , we ran each library on an Agilent 2100 Bioanalyzer . We then sequenced each polar bear on a separate lane of an Illumina HiSeq 2000 instrument using 100 base-pair ( bp ) paired-end chemistry at the UC Santa Cruz Core Genomics Facility . We sequenced one lane each of the two brown bears , the black bear , and an additional lane for two polar bears ( Table S2 ) using an Illumina HiSeq 2000 instrument with 150-bp paired-end chemistry at the Vincent J . Coates Genomics Sequencing Laboratory at UC Berkeley . From the Illumina sequence data , we removed the index and adapter sequence and merged paired reads using a script provided by M . Kircher [27] . We then trimmed each read to remove low quality bases by trimming inward from the 3′-end of the read until detecting a base with quality score ≥13 ( ∼95% confidence ) . We mapped the resulting data to the draft polar bear genome [13] using BWA [28] . We removed duplicated reads created by PCR amplification using rmdup program from samtools [29] . We then applied GATK's [30] base quality score recalibration and indel realignment , and performed SNP genotyping across all samples simultaneously using default settings in GATK [31] . Total coverage is shown in Table S2 . | The evolutionary genetic relationship between polar bears ( Ursus maritimus ) and brown bears ( U . arctos ) is a subject of continuing controversy . To address this we generated genome-wide sequence data for seven polar bears , two brown bears ( including one from the enigmatic ABC Islands population ) , and a black bear ( U . americanus ) . These data reveal remarkable genetic homogeneity within polar bears and clear evidence of past hybridization with brown bears . Hybridization , however , appears to be limited to habitat islands , where isolated populations of polar bears are gradually converted into brown bears via male-mediated dispersal and sex-biased gene flow . Our simplified and comprehensive model for the origin and evolution of polar bears resolves conflicting interpretations of mitochondrial and nuclear genetic data , and highlights the potential effect of natural climate change on long-term evolutionary processes . | [
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] | 2013 | Genomic Evidence for Island Population Conversion Resolves Conflicting Theories of Polar Bear Evolution |
Hepatitis B virus ( HBV ) core protein assembles viral pre-genomic ( pg ) RNA and DNA polymerase into nucleocapsids for reverse transcriptional DNA replication to take place . Several chemotypes of small molecules , including heteroaryldihydropyrimidines ( HAPs ) and sulfamoylbenzamides ( SBAs ) , have been discovered to allosterically modulate core protein structure and consequentially alter the kinetics and pathway of core protein assembly , resulting in formation of irregularly-shaped core protein aggregates or “empty” capsids devoid of pre-genomic RNA and viral DNA polymerase . Interestingly , in addition to inhibiting nucleocapsid assembly and subsequent viral genome replication , we have now demonstrated that HAPs and SBAs differentially modulate the biosynthesis of covalently closed circular ( ccc ) DNA from de novo infection and intracellular amplification pathways by inducing disassembly of nucleocapsids derived from virions as well as double-stranded DNA-containing progeny nucleocapsids in the cytoplasm . Specifically , the mistimed cuing of nucleocapsid uncoating prevents cccDNA formation during de novo infection of hepatocytes , while transiently accelerating cccDNA synthesis from cytoplasmic progeny nucleocapsids . Our studies indicate that elongation of positive-stranded DNA induces structural changes of nucleocapsids , which confers ability of mature nucleocapsids to bind CpAMs and triggers its disassembly . Understanding the molecular mechanism underlying the dual effects of the core protein allosteric modulators on nucleocapsid assembly and disassembly will facilitate the discovery of novel core protein-targeting antiviral agents that can more efficiently suppress cccDNA synthesis and cure chronic hepatitis B .
Hepatitis B virus ( HBV ) is a small DNA virus that chronically infects 240 million people worldwide and causes approximately 686 , 000 deaths annually due to various severe liver diseases , including cirrhosis , hepatocellular carcinoma ( HCC ) and liver failure [1] . Currently approved direct-acting antiviral agents against HBV are six nucleos ( t ) ide analogues that inhibit viral DNA polymerase with varying potency and barriers to drug resistance [2] . Although those viral DNA polymerase inhibitors significantly reduce viral load and prevent liver disease progression , they rarely cure HBV infection due to their inability to eradicate cccDNA [3] . HBV core protein is a small polypeptide of 183 amino acid residues . It exists in infected hepatocytes as several distinct quaternary structures and plays multiple roles in the viral replication cycle [4] . The best characterized function of core protein is the assembly of pre-genomic ( pg ) RNA and viral DNA polymerase complex into nucleocapsids where HBV DNA synthesis takes place [5] . Moreover , temporally and spatially regulated disassembly ( or uncoating ) of nucleocapsids is essential for delivery of viral relaxed circular ( rc ) genomic DNA into the nuclei of infected hepatocytes [6 , 7] , where it is converted to covalently closed circular ( ccc ) DNA [8 , 9] . Furthermore , it has also been suggested that core proteins may associate with cccDNA minichromosomes , in an as-yet undefined structural manner , to regulate its transcription [10] . Interestingly , it was also reported that core protein can be hijacked by host immune responses to recruit cytokine-induced DNA cytosine deaminase APOBEC3A to cccDNA minichromosomes , which results in cytosine deamination and decay of cccDNA [11 , 12] . Due to their unique structures and essential roles in viral replication , disruption of , or interference with , nucleocapsid assembly and/or disassembly with small molecular core protein allosteric modulators ( CpAMs ) represents a new frontier in development of novel antiviral agents against HBV [13 , 14] . Over the last two decades , at least five chemotypes of CpAMs have been reported [13] . Those compounds bind to a hydrophobic pocket , designated as the HAP pocket , at the dimer-dimer interface near the C-termini of core protein subunits [15 , 16] . Binding of these molecules in the HAP pocket induces large scale allosteric conformational changes in core protein subunits and alters the capsid assembly kinetics and pathways [4 , 17] . While heteroaryldihydropyrimidines ( HAPs ) , such as Bay 41–4109 and GLS4 , misdirect capsid assembly to form non-capsid polymers of core proteins [17 , 18] , all other chemotypes of CpAMs , including sulfamoylbenzamides ( SBAs ) and phenylpropenamides ( PPAs ) , represented by ENAN-34017 and AT-61 , respectively ( S1 Fig ) , induce the formation of morphologically “normal” empty capsids with distinct quaternary and/or tertiary structural changes and thus , preclude viral DNA replication [19 , 20] . Thus far , several HAPs and SBAs have been shown to inhibit HBV replication in animal models and are currently under preclinical or clinical development [14 , 21] . Inspired by the observation that a small molecule compound targeting the capsid protein of dengue virus has dual effects on both the assembly and disassembly ( or uncoating ) of the viral capsids [22] , we hypothesized that HBV CpAMs may not only disrupt capsid assembly , but also alter the structure and function of assembled nucleocapsids and consequentially affect viral DNA replication and/or cccDNA synthesis . Indeed , we have now obtained evidence showing that HAPs and SBAs , but not PPAs , induce disassembly of nucleocapsids from virions as well as double-stranded DNA-containing cytoplasmic progeny nucleocapsids and consequentially interfere with cccDNA biosynthesis from de novo infection and intracellular amplification pathways .
Discovery of human sodium taurocholate cotransporting polypeptide ( hNTCP ) as the bona fide receptor for HBV infection of hepatocytes allows for establishment of convenient HepG2-derived HBV infection cell culture systems [23 , 24] . We have thus established a novel NTCP-expressing human cell line , designated as C3AhNTCP , and demonstrated its susceptibility to HBV infection . The parental cell line , C3A , is a subclone of HepG2 cells that exhibits strong contact inhibition of growth and metabolic features that are more similar to normal hepatocytes [25] . As shown in S2 Fig , cccDNA became detectable as early as 1 day and reached maximum levels at 2 day post infection by qPCR and conventional Southern blot assays . HBV pgRNA and core-associated viral DNA replication intermediates as well as core protein also accumulated sequentially in infected cultures . HBsAg was readily detectable by ELISA as a product of HBV infection in the culture media . In order to investigate the effects of CpAMs on HBV infection , particularly cccDNA synthesis from a de novo infection , C3AhNTCP cells were mock-treated or treated with representative HAP ( Bay 41–4109 , GLS4 ) or SBA ( ENAN-34017 ) and control compounds entecavir ( ETV ) or Myrcludex B ( MyrB ) , starting at 24 h before HBV infection until harvesting at day 3 and day 6 post infection . As expected ( Fig 1 ) , MyrB , an acylated peptide derived from the HBV large envelope protein blocks virus entry [26] , inhibited cccDNA formation and consequential accumulation of pgRNA and core DNA . Also as anticipated , ETV , an HBV DNA polymerase inhibitor , did not affect the synthesis of cccDNA and accumulation of pgRNA , but inhibited the synthesis of core DNA [27] . Interestingly , GLS4 , Bay 41–4109 and ENAN-34107 significantly reduced the amounts of cccDNA . Viral pgRNA and core DNA were also proportionally reduced . A more detailed time course study spanning the first four days post infection revealed that the three CpAMs significantly inhibited cccDNA formation , whereas ETV and IFN-α did not ( S3 Fig ) ( Fig 1D , lanes 5 and 9 ) . However , while ETV did not reduce viral RNA , IFN-α reduced the levels of viral pgRNA and 2 . 4/2 . 1 kb mRNA , presumably due to suppression of cccDNA transcription [28 , 29] . To further characterize the inhibitory effect of CpAMs on cccDNA biosynthesis , time-of-addition and dose response experiments were performed . In agreement with its mode of action , MyrB treatment starting at 24 h before or at the time of infection efficiently blocked cccDNA formation , whereas delayed treatment starting at 24 h post infection completely failed to inhibit cccDNA formation ( Fig 2A ) . Consistent with the kinetics of cccDNA formation in this cell culture system ( S3 Fig ) , while CpAM treatment starting at 24 h before or at the time of infection reduced cccDNA formation at similar efficiency , their inhibitory effects were significantly reduced when the treatment started at 24 h post infection . Moreover , all the three CpAMs inhibited cccDNA formation in a concentration dependent manner ( Fig 2B ) . Those results are in agreement with a report published during the preparation of this manuscript that Bay 41–4109 and SBA derivative JNJ-632 inhibited HBV cccDNA synthesis during HBV infection of human primary hepatocytes [30] . To investigate the possibility that the observed inhibition of CpAMs on cccDNA formation is due to inhibition of NTCP-mediated HBV entry , we examined their effects on hepatitis D virus ( HDV ) infection of C3AhNTCP cells . The results demonstrated that while MyrB efficiently reduced genomic and antigenomic HDV RNA by more than 3 log , ETV and IFN-α as well as Bay-41-4109 and ENAN-34017 did not apparently alter the amounts of HDV RNA in the infected cultures ( S4 Fig ) . The results thus imply that inhibition of cccDNA synthesis by the CpAMs is due to their interaction with HBV-specific components , most possibly nucleocapsids , but not the host cellular factor ( s ) in the entry pathway shared by HBV and HDV . Besides being synthesized from incoming virion DNA in the de novo infection , cccDNA in infected hepatocytes can also be amplified by delivery of rcDNA from cytoplasmic progeny nucleocapsids into the nucleus and conversion to cccDNA [31–33] . This intracellular cccDNA amplification pathway has been demonstrated to function in cultured cells and in vivo in duck hepatitis B virus ( DHBV ) -infected ducks , and is regulated by the large envelope protein and host cellular factors [33 , 34] . Because CpAMs inhibit pgRNA encapsidation and thus preclude viral DNA replication and intracellular amplification of cccDNA , their effects on intracellular progeny nucleocapsids and cccDNA amplification cannot be investigated in cells directly treated with those compounds [35] . To circumvent this problem , as depicted in Fig 3A , we first arrested HBV DNA replication by culturing HepAD38 cells in medium without tetracycline , but containing the reversible viral DNA polymerase inhibitor Foscarnet ( trisodium phosphonoformate , or PFA for short ) for four days , which arrested HBV DNA replication predominantly at the stages of incomplete and complete minus-strand DNA ( Fig 3B ) [36] . The cells were then cultured in the presence of tetracycline to stop HBV pgRNA transcription from integrated transgene in cellular chromosome , and also in the absence of PFA to allow viral DNA replication and cccDNA synthesis to resume . At the time of PFA withdrawal , mock treatment or treatment with ETV , Bay-41-4109 , ENAN-34017 was initiated and cells were harvested at the indicated time points for analyses of HBV core DNA and cccDNA . Synthesis and identity of cccDNA in this cell culture system were confirmed by its resistance to heat denaturing and conversion into 3 . 2kb unit-length DNA after heat denaturing and EcoRI digestion ( S5 Fig ) . As shown in Fig 3B , upon removal of PFA from culture medium , the incomplete and complete minus strand , partial double-strand and complete double strand HBV DNA species ( including rcDNA ) sequentially increased from 3 to 12 h ( Fig 3B ) . Deproteinized rcDNA ( DP-rcDNA ) and cccDNA became readily detectable at 9 and 12 h , respectively ( Fig 3C ) . As expected , ETV treatment inhibited the elongation of arrested HBV DNA species and prevented the production of rcDNA as well as DP-rcDNA and cccDNA . Interestingly , although Bay-41-4109 or ENAN-34017 treatment did not inhibit elongation of minus-strand and partial double-strand DNA in the cytoplasmic nucleocapsids , the rcDNA was not accumulated in those cells ( Fig 3B ) . However , analysis of Hirt DNA indicated that the amount of DP-rcDNA was not apparently reduced by CpAM treatment and to our surprise , the cccDNA was readily detected as early as 9 h after the removal of PFA in CpAM-treated cells . Experiments with additional CpAMs and extended treatment duration further supported the notion that the selected HAP and SBA compounds reduced the accumulation of cytoplasmic rcDNA-containing nucleocapsids ( S6 Fig ) , but significantly accelerated cccDNA synthesis from intracellular progeny nucleocapsids , as demonstrated by two different cccDNA assay procedures ( S6 Fig and Fig 4 ) . The apparent contradicting effects of CpAMs on cytoplasmic rcDNA-containing nucleocapsid accumulation and kinetics of cccDNA synthesis in HepAD38 cells prompted us to investigate whether those compounds inhibited the completion of rcDNA synthesis and/or destabilized the nucleocapsids containing mature forms of double-stranded DNA . This latter possibility may explain the observed acceleration of cccDNA formation from intracellular progeny nucleocapsids [7 , 37] . To this end , HBV capsids were purified from the cytoplasmic fraction of PFA-treated cells and an endogenous DNA polymerase assay were performed in vitro in the absence or presence of CpAMs . To probe the integrity of nucleocapsids , the accessibility of viral DNA to DNase I digestion were tested at the completion of endogenous DNA polymerase reaction , but before extraction of viral DNA . Southern blot analysis of viral DNA species indicated that rcDNA can be efficiently synthesized in the in vitro endogenous DNA polymerase reaction when dNTPs were provided ( Fig 5A ) . Furthermore , the presence of Bay 41–4109 , ENAN-34017 or AT-61 did not inhibit rcDNA synthesis . However , the rcDNA synthesized in the presence of Bay 41–4109 and ENAN-34017 , but not AT-61 , was susceptible to DNase I digestion ( Fig 5A and 5B ) . Hence , our results indicate that CpAMs do not inhibit HBV DNA synthesis , but favor a hypothesis that the selected CpAMs specifically alter the structure of , and destabilize mature rcDNA-containing nucleocapsids and facilitate rcDNA nuclear delivery and synthesis of cccDNA . Because the mature rcDNA-containing nucleocapsids only constitute a small fraction of total cytoplasmic capsids [38] , it is not surprise that the CpAM treatment did not alter the amounts and migration mobility of capsids , as revealed by a native agarose gel electrophoresis-based particle gel assay ( Fig 5A and 5B , lower panels ) [35 , 39] . The differential effects of CpAMs on cccDNA synthesis from the de novo infection and intracellular amplification pathways argues that the compounds may have a different effect on the nucleocapsids in virions and in the cytoplasm . To investigate this possibility , we purified HBV virion particles from the blood of a chronic HBV carrier and examined the effects of CpAMs on rcDNA synthesis and integrity of nucleocapsids in an in vitro endogenous DNA polymerase reaction as described above . Similar to the results obtained with cytoplasmic nucleocapsids , the presence of Bay 41–4109 , ENAN-34017 or GLS4 did not inhibit rcDNA synthesis from partially double-stranded virion DNA , but conferred susceptibility of virion rcDNA to DNase I digestion in a concentration–dependent manner ( Fig 6A ) . To further investigate whether CpAMs can directly induce structural change of the partially double-stranded DNA-containing nucelocapsids , virion particles prepared from the patient serum were treated with the CpAMs in an endogenous DNA polymerase reaction without dNTP and followed by DNase I treatment prior to DNA extraction . The results showed that each of the three tested CpAMs rendered all virion DNA species susceptible to DNase I digestion in a concentration-dependent manner ( Fig 6B ) . Hence , the results indicate that irrespective to the maturation stage of viral DNA , the nucleocapsids derived from virion particles are sensitive to CpAM-induced structural changes that expose viral DNA for DNase I digestion . Encouraged by the observation that the CpAM-induced virion DNA susceptibility to DNase I did not depend on active DNA polymerase reaction or ongoing DNA chain elongation ( Fig 6B ) , we further examined the effects of CpAMs on capsids purified from the cytoplasm of HepAD38 cells in an endogenous DNA polymerase reaction buffer without dNTPs . As shown in Fig 7A , while rcDNA became susceptible to DNase I digestion at lower concentrations of GLS4 or ENAN-34017 , the less mature , partially double-stranded DNA species became susceptible to DNase I digestion under gradually increased concentrations . This result strongly suggests that elongation of positive strand DNA in hepatocytes may incrementally induce structural changes of nucleocapsids and confer gradually increased sensitivity to the CpAM induction of viral DNA exposure . Moreover , a comprehensive dose-response experiment revealed that the minimum concentrations of ENAN-34107 , Bay 41–4109 and GLS4 that induce a complete exposure of rcDNA are approximately 0 . 3 , 0 . 04 and <0 . 02 μM , respectively ( S7 Fig ) , which are comparable to their potency to inhibit nucleocapsid assembly and viral DNA replication in HepG2 cells [35 , 39 , 40] . A kinetics study further revealed that while up to 6 h incubation was required for ENAN-34017 to induce significant exposure of rcDNA , 1 to 2 h exposure was sufficient for GLS4 and Bay 41–4109 to induce an extensive exposure of rcDNA ( Fig 7B ) . To determine the kinetics of CpAMs induction of rcDNA exposure in cells , HepAD38 cells cultured in tet-free medium for 6 days were treated with GLS4 for the indicated periods of time . The cytoplasmic lysates were mock-treated or treated with DNase I before extraction of DNA . As shown in S8 Fig , treatment of GLS4 for 6 h induced extensive rcDNA exposure for DNase I digestion . Although results presented above indicate that CpAM treatment induces the exposure of rcDNA in nucleocapsids to DNase I digestion , the extent of disruption on the structure of mature nucleocapsids by the different CpAMs remains to be determined . We therefore examined whether the mature viral DNA species , rcDNA and double-stranded linear ( dsl ) DNA , were still associated with capsids after CpAM treatment . The assumption is that if CpAM treatment severely disrupts the mature nuclocapsids and results in releasing of viral DNA , we anticipate that rcDNA and dslDNA species will not co-sediment with any form of capsids . However , if CpAM treatment only mildly disrupts the mature nucleocapsids and causes the exposure of viral DNA that is still associated with capsid structure , we anticipate to see the rcDNA and/or dslDNA species will co-sediment with capsids . To this end , HBV capsids prepared from HepAD38 cells were mock treated or incubated with ENAN-34017 , Bay 41–4109 or GLS4 in endogenous DNA polymerase reactions without dNTPs . The reactions were then fractionated by sucrose density gradient ultracentrifugation . The amounts of total capsids and capsid-associated DNA in each of the fractions were analyzed by a 1 . 5% native agarose gel electrophoresis-based particle gel assay [39] . As shown in the upper panels of Fig 8 A to 8D , compared to mock-treated control , treatment with any of the three CpAMs did not alter the sedimentation profile of capsids and capsid associated HBV DNA . These results are consistent with the observation that CpAMs only affect the mature nuclocapsids that constitute only a small portion of total capsids ( Fig 7 and S7 Fig ) . However , analysis of viral DNA by Southern blot hybridization in each of the fractions revealed that rcDNA and dslDNA were lost or reduced from capsids sedimenting to 21% to 25% sucrose after Bay 41–4109 or GLS4 treatment , but the majority of rcDNA and dslDNA still co-sediment with capsids after ENAN-34017 treatment ( Fig 8 A to 8D , lower panels ) . Due to the small amounts of rcDNA and dslDNA and low sensitivity of Southern blot hybridization assay , we were not able to identify the location or distribution of the disassociated DNA species in the gradients . Nevertheless , those results indicate that while Bay 41–4109 or GLS4 treatment most likely induced structural changes that were significant enough to cause loss of rcDNA and dslDNA from majority of the mature nucleocapsids , the less active compound ENAN-34017 might only induce structural changes that render the DNA content susceptible to DNase digestion . These two distinct degrees of conformational alteration may correspond to a subtle increase in “capsid breathing” for ENAN-34017 , versus extensive rearrangement of the capsid subunit organization for BAY-41-4109 and GLS4 [41] .
The genomes of all viruses are wrapped with capsid protein ( s ) to form nucleocapsids . Unlike viral enzymes that often have host cellular homologues , host cells do not encode proteins that are structurally and functionally similar to viral capsid proteins . Therefore , viral capsid proteins are ideal and highly selective antiviral targets [42] . In addition to serving as a vehicle for transmission of viral genomes between host cells , HBV nucleocapsids have other unique functions in the viral life cycle [4 , 9 , 27] . As illustrated in Fig 9 , first , HBV DNA replication occurs exclusively within the cytoplasmic nucleocapsids , by reverse transcription of viral pgRNA first into negative-strand DNA and then double-stranded rcDNA . Second , unlike all other viruses where the progeny nucleocapsids have only one destination , i . e . , to be secreted as virions , the HBV progeny nucleocapsids can also deliver their rcDNA into the nuclei to synthesize cccDNA . Due to superinfection exclusion [43 , 44] , it is reasonable to consider that the activity of the intracellular amplification pathway is the key determinant of cccDNA pool size in infected hepatocytes [45] . Due to the large amounts of progeny nucleocapsids in the cytoplasm , this intracellular cccDNA amplification pathway must be , and actually is , tightly controlled by viral and host factors [7 , 34 , 37 , 46] . Finally , the exclusive replication in nucleocapsids and the spatially-controlled disassembly and delivery of rcDNA into nuclei at nuclear pore complexes protect the viral DNA from recognition by cytoplasmic DNA sensors , and thus favor the persistent infection by HBV [8 , 9 , 47] . Hence , it has been speculated that targeting HBV core protein may disrupt multiple steps of HBV replication and activate innate immune response in virally infected cells . However , as mentioned , while several distinct chemotypes of HBV CpAMs have been shown to disrupt viral nucleocapsid assembly and consequentially inhibit viral genome replication , their effects on other aspects of nucleocapsid function have not been investigated . Herein , we provide evidence suggesting that selected HAPs and SBAs are able to interact with nucleocapsids from virions and mature forms of rcDNA-containing nucleocapsids in the cytoplasm and subsequently interfere with their function of delivering viral rcDNA to the nuclei for cccDNA synthesis . Although the structural basis for the CpAMs to target the highly selected sub-populations of nucleocapsids remains to be determined , our results are consistent with previous findings that mature HBV nucleocapsids are intrinsically unstable or fragile [48] , probably due to the stiffness of rc and dslDNA , which imposes bending energy and electrostatic repulsion to the capsid shell [49] . Moreover , viral DNA synthesis in the nucleocapsids assembled from mutant DHBV core proteins with a serial N-terminal inertions destabilized mutant nucleocapsids , rendering mature viral DNA selectively sensitive to nuclease digestion [50] . Therefore , it is possible that the intrinsic instability of mature nucleocapsids , due to the completion of double-stranded DNA , confers the selective sensitivity for CpAMs to induce disassembly . Considering the result that CpAM treatment induces the accessibility of all forms of virion DNA , either rcDNA or partially double-stranded DNA , to DNase I digestion , a possible explanation is that like many other viruses , structural shifts or maturation of nucleocapsids may occur during or after virion assembly and secretion , and confer susceptibility to CpAMs [51] . Moreover , a recent report showed that the carboxyl-terminal domain of core proteins is hypophosphorylated in DNA-containing virions , but remains hyperphosphorylated in intracellular DNA-containing nucleocapsids [52] . Although the C-terminal arginine-rich domain of HBV core protein is not directly involved in the binding of CpAMs [39] , the dephosphorylation may alter the interaction between core protein and viral DNA [53] , and thus affect the nucleocapsid structure in a manner distinct from that of the hyperphosphorylated state [54] . In addition , the sensitivity of partially double-stranded DNA-containing cytoplasmic nucleocapsids to the increased concentrations of CpAMs strongly suggests that elongation of positive-stranded DNA toward rcDNA induces incremental , or gradual , structural changes favoring specific interaction with CpAMs . Structural biology studies with purified double stranded DNA-containing capsids may reveal those important structure differences . However , it is technically challenging to purify sufficient amounts rcDNA-containing HBV capsids for Cryo-EM analyses . Although our study revealed correlations between altered cccDNA synthesis and induction of nucleocapsid destablization by CpAMs , the molecular mechanisms on how the CpAM-induced nucleocapsid structural changes disrupt cccDNA formation in de novo infection , but accelerate cccDNA synthesis from progeny intracellular nucleocapsids remain to be determined . However , reasonable speculations can be made based on current knowledge . As illustrated in Fig 9 , on one hand , in de novo infection , CpAMs may interact with nucleocapsids in virions during endocytic entry or immediately after their release into the cytoplasm to induce viral DNA exposure or release from nucleocapsids . The premature disassembly of nucleocapsids results in viral DNA release and decay by cytoplasmic DNases before its arrival to the nuclear pore complex for nuclear import and subsequent cccDNA synthesis . On the other hand , due to the shorter distance traveled as compared to the de novo infection , the intracellular progeny rcDNA-containing nucleocapsids may reach nuclear pore complexes before a certain stage of their disassembly and CpAM-induced uncoating actually accelerates the release of rcDNA into the nuclei and thus cccDNA formation . Of course , a fraction of rcDNA decay in the cytoplasm may also occur . In fact , this interpretation is in agreement with recent findings that enhanced destabilization of mature rcDNA containing nucleocapsids , due to unidentified host cellular factors in mouse hepatocytes or a single amino acid substitution ( I126A ) in core protein , significantly reduced the accumulation of rcDNA , but increased the DP-rcDNA and cccDNA synthesis [7 , 37] . It had not escaped our attention that the released or exposed rc/dslDNA in the cytoplasm may activate innate DNA sensors [55–58] . However , cytokine response was not detected in CpAM-treated cells . Whether this is due to the deficiency of cyclic GMP-AMP synthase ( cGAS ) - stimulator of interferon genes ( STING ) pathway in hepatocytes and hepatoma cells [59–61] or efficient digestion of the released viral DNA by cytoplasmic nucleases [62] is currently under investigation . While inhibition of cccDNA synthesis from de novo infection is obviously a beneficial therapeutic effect , the acceleration of intracellular cccDNA amplification is detrimental . However , the potent inhibition of pgRNA encapsidation by CpAMs will quickly block viral DNA replication and production of mature progeny nucleocapsids and consequential cccDNA synthesis . Therefore , the only chance for CpAMs to accelerate cccDNA synthesis during antiviral therapy is at the initial period of treatment to promote cccDNA synthesis from pre-existing mature nucleocapsids in HBV infected cells . Fortunately , treatment of HepAD38 cells supporting steady-state HBV DNA replication with ETV and CpAMs to mimic the initial stage of antiviral treatment in vivo did not observe a significant increase of cccDNA accumulation within first 24 h of treatment . Instead , similar to ETV , CpAMs prevented amplification of cccDNA pool during a prolonged treatment , as compared with mock-treated control ( S9 Fig ) . In fact , those results are consistent with the observation that CpAM treatment of primary human hepatocytes after establishment of HBV infection did not alter the amount of cccDNA [30] . Taking together , the results imply that CpAMs only significantly increase the amount of cccDNA by acceleration of ongoing cccDNA synthesis , such as under the condition of fast cccDNA synthesis after release from PFA arrested HBV DNA replication , but cannot accelerate the very low ( or negligible ) rate of cccDNA synthesis to significantly increase the amount of cccDNA in cells with established HBV infection . Mechanistically , as stated above , it is possible that only when CpAM-induced disassembly of mature nucleocapsids occurs at or near the nuclear pore complex may facilitate the import of rcDNA into the nuclus for cccDNA synthesis , but the mature nucleocapsids at such status may not exist in a significant amount in hepatocytes with established infection . Nevertheless , careful monitoring of cccDNA synthesis during the early phase of CpAM treatment in vivo in animals and in clinical trials and pretreatment or combination with viral DNA polymerase inhibitors might be considered .
The HepAD38 cell line ( obtained from Dr . Christoph Seeger at Fox Chase Cancer Center , Philadelphia ) supporting HBV pgRNA transcription and subsequent viral DNA replication in a tetracycline ( tet ) -inducible manner was maintained as previously described [63] . C3A cell line [a derivative of HepG2 ( ATCC HB-8065 ) ] ( ATCC CRL-10741 ) was maintained in DMEM/F-12 ( 1:1 ) medium supplemented with 10% FBS ( GEMINI Bio-Products ) , 100 U/ml penicillin , 100 μg/ml streptomycin . Entecavir ( ETV ) is a gift from Dr . William S . Mason at Fox Chase Cancer Center , Philadelphia [64] . Foscarnet was purchased from Sigma . Capsid assembly modulators ENAN-34017 and Bay41-4109 , GLS4 and AT-61 were described previously [35 , 65] . Myrcludex B is a gift of Dr . Stephan Urban at Heidelberg University , Germany [26] . Alpha-interferon ( IFN-α ) was purchased from PBL Assay Science . Rabbit anti-HBc antibody was obtained from Dako ( B0586 ) . Human sodium taurocholate cotransporting polypeptide ( NTCP ) gene coding sequence was amplified from a cDNA clone purchased from Origene ( SC118232 ) . A carboxyl-terminal C9 tag was added by PCR amplification with the primers harboring C9 tag sequence and NotI & Bam HI restriction enzyme sites . The purified PCR fragments were digested with restriction enzymes Not I and Bam HI and subsequently cloned into a pQCXIP vector ( Clontech ) . VSV G protein pseudotyped retroviruses were packaged in GP2-293 cells as previously described [66] . C3AhNTCP cell line stably expressing human NTCP was established by infection of C3A cell line with the pseudotyped retroviruses and selected with medium containing 2 μg/ml of puromycin . Puromycin-resistant cells were expanded into cell line and designated as C3AhNTCP . Proper expression of NTCP was confirmed by immunofluorescence and Western blot assays . C3AhNTCP cells were seeded into collagen-coated 24-well plates at a density of 4×105 cells per well and cultured in complete DMEM medium containing 3% dimethyl sulfoxide ( DMSO ) . One day later , the cells were infected with HBV prepared from HepAD38 cell culture media at a MOI of 500 genome equivalents per cell in DMEM containing 4% PEG-8000 . The inoculums were removed at 24 h post infection and the cultures were maintained in complete DMEM medium containing 3% DMSO until harvesting . HBV core DNA and RNA extraction from infected C3AhNTCP or HepAD38 cells , Southern blot hybridization , and real-time PCR analyses were performed as described previously [35 , 65] . HBV cccDNA from HBV-infected C3AhNTCP cells and HepAD38 cells were extracted by a modified Hirt DNA extraction procedure [33] . A fraction of Hirt DNA preparation was digested with 1 unit of plasmid-safe adenosine triphosphate ( ATP ) -dependent deoxyribonuclease ( PSAD ) ( Epicentre Technologies ) in a 25 μL reaction for 1 h at 37°C to remove rcDNA . The DNase was inactivated by incubation of the reactions for 30 min at 70°C . cccDNA in the PSAD-treated samples were quantified by a real time PCR assay with primer sequences GGGGCGCACCTCTCTTTA ( forward ) and CCACCCAGGTAGCTAGAGTCATTAG ( reverse ) . The real-time PCR was performed using the SYBR Premix Ex Taq on a LightCycler 480 II ( Roche ) as the following reaction procedure: 95°C for 10 min then 45 cycles of 95°C for 30 s , 60°C for 5 s , and 72°C for 30 s . The amount of HBV cccDNA in a DNA preparation was determined by real-time PCR using a plasmid containing HBV genotype D genome as the standard . For Southern blot hybridization , the Hirt DNA samples were denatured at 88°C for 5 minutes and chilled in ice . This procedure completely denatures deproteinized rc-DNA ( DP-rcDNA ) into single stranded DNA , whereas cccDNA will remain as double stranded circular DNA [67] . The denatured Hirt DNA samples without or with further digestion with restriction enzyme Eco RI to linearize cccDNA into double-stranded linear DNA were resolved in 1 . 5% agarose gel and transferred onto Hybond-XL membrane . The membrane was probed with α-32P-UTP labeled minus strand specific full-length HBV riboprobe . | Persistent HBV infection relies on stable maintenance of a nuclear episomal viral genome called covalently closed circular ( ccc ) DNA , the sole transcriptional template supporting viral replication . The currently available antiviral therapeutics fail to cure chronic HBV infection due to their failure to eradicate or inactivate cccDNA . In addition to packaging viral pregenomic ( pg ) RNA and DNA polymerase complex into nucleocapsids for reverse transcriptional DNA replication to take place , HBV core protein also participates in and regulates virion particle assembly , capsid uncoating and cccDNA formation . We report herein an intriguing observation that selected core protein allosteric modulators not only inhibit nucleocapsid assembly , but can also act on assembled , nucleus-bound nucleocapsids to promote their uncoating and consequentially interfere with cccDNA biosynthesis . This finding establishes molecular basis for development of novel core protein targeting antiviral agents with improved efficacy of suppressing cccDNA synthesis and curing chronic HBV infection . | [
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] | 2017 | HBV core protein allosteric modulators differentially alter cccDNA biosynthesis from de novo infection and intracellular amplification pathways |
Computational protein design is a reverse procedure of protein folding and structure prediction , where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction . Following this spirit , we developed a novel method to design new protein sequences based on evolutionarily related protein families . For a given target structure , a set of proteins having similar fold are identified from the PDB library by structural alignments . A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space , where physicochemical packing is accommodated by single-sequence based solvation , torsion angle , and secondary structure predictions . The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes , which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods . Without using homologous proteins , the designed sequences can be folded with an average root-mean-square-deviation of 2 . 1 Å to the target . As a case study , the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis , which is the second leading cause of death from infectious disease . On a smaller scale , five sequences were randomly selected from the design pool and subjected to experimental validation . The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure , as demonstrated by circular dichroism and NMR spectroscopy . Together , these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality .
Computational protein design aims to identify new amino acid sequences that have desirable 3-dimensional ( 3D ) structure and biological function . This can be considered as a reversed procedure of protein folding and protein structure prediction , in that protein folding and protein structure prediction aim to deduce the 3D structure from given amino acid sequences . In protein 3D structure prediction , it has been well-established [1]–[2] that the most reliable and accurate models are those constructed by homology modeling which copies and refines structural frameworks from evolutionarily related proteins for the template-based modeling targets . The sequence profiles , which scale the evolutionary conservation/mutation characteristics of protein families in a form of a L×20 matrix [3] , play a central role in improving the alignment accuracy of structural template identifications [4]–[5] . On the other hand , ab initio folding approaches , which try to fold proteins using physics-based force fields , work well only occasionally for small proteins ( <100 residues ) with low resolution ( RMSD>3–5 Å ) [6]–[8] . The difficulty of the physics-based ab initio approaches was generally considered to be due to the inaccuracy of force field design and the limits of the conformational search [9]–[10] . Recently , a super-long time ( >100 µs ) molecular dynamics simulation by Raval et al [11] demonstrated that the conformational search is a factor of less impact to the failure to protein folding and structure refinement compared to the force field accuracy . Zhang et al [12] and Mirjalili et al [13] further showed that the spatial restraints from structural templates can help improve the energy funnel of the physics-based force field and guide the molecular dynamics simulation for structure refinements . However , these refinements are limited to fine-tuning the local structure details and are far from topology-level improvements . Somewhat in paradox , the physics-based force field , which has been exploited in most of current approaches [14]–[21] , seems to work well on protein designs . A number of newly designed proteins with improved structural stability and/or biological functionality have been reported [14] , [22]–[25] . One of the reasons for the success is probably due to the iterative searching simulations , which reinforce the match of the designed sequence with the target structure that can result in a simplified energy landscape of the design sequence . As a result , the folding accuracy of structural models on the designed sequences can be significantly increased compared to that encountered in structure prediction of natural proteins [18] , [26] . To further improve the biological specificity of designed sequences , Floudas and co-workers recently introduced constraints from sequence homology search , including charge , amino acid content and residue frequency , to guide the physics-based sequence designs [25] , [27]–[29] . Nevertheless , many of the physics-based designs are structurally and thermodynamically less well-defined than natural proteins [14] , [30] . Similar to the protein folding problem , one major difficulty stems from the inaccuracy of the force field to balance the subtle atomic interactions and to distinguish the unique structures from alternatives , especially for the medium-to-large size proteins . In addition , the exponential increase in sequence phase space with protein size L ( ∼20L ) is prohibitive for direct design enumerations . To address these issues , we propose an evolution-based protein design method , whereby sequence space search is constrained by the sequence and structural profiles collected from protein analog families , with local side-chain packing accommodated by neural-network based solvation and secondary structure predictions . The principle of the approach follows the critical lessons that we learnt from threading-based protein structure prediction methods , i . e . to use the reliable “finger print” of nature in the form of structural profile information to guide the simulation to the fold of the target scaffold structure . To examine the generality of the approach , we compared a combined evolutionary and physics based method ( EBM ) against a stand-alone physics-based design method [19] , termed PBM , on a large set of proteins using computational protein structure prediction methods to test the foldability and physicochemical compatibilities of the designed sequences . As a case study of large-scale applications , the EBM method was extended to redesign all proteins from the pathogenic bacteria Mycobacterium tuberculosis ( MTb ) , which is the second leading cause of death from infectious diseases [31] . Finally , a handful of designed domains were expressed , purified and biophysically characterized by circular dichroism ( CD ) and NMR spectroscopy experiments for various folding feature validations .
To evaluate the likelihood of the designed sequences to fold into stable and desired structures ( or the foldability ) , we exploited the I-TASSER pipeline [33]–[34] to generate structural models for each of the designed sequences and then examine the structural similarity to the target scaffold , where all homologous templates to the scaffold sequence were excluded from the threading structure library . Here , one reason for the choice of the computational folding approach for validation is that experimental validations are generally too expensive for large-scale protein design experiments . Second , the current ab initio folding methods have limited ability to fold protein structures beyond 100 residues . In contrast , the I-TASSER pipeline has a high success rate ( ∼3/4 ) to construct correct folds for medium-to-large sized proteins by structurally reassembling the fragments excised from threading template structures without using homologous templates , as demonstrated by the recent community-wide CASP experiments [35]–[38] . In a most recent study of the I-TASSER based design validation [19] , it was shown that none of the randomized sequences , even with sequence identity to the target higher than the well-designed sequences and having the same secondary structure propensities as the targets ( i . e . obtained by integrating segments cut from other PDB structures that had the same secondary structure ) , could be folded by I-TASSER to a model below 6 Å to the target structures , with the average RMSD to target being 13 . 4 Å . For the well-designed sequences with optimized tertiary atomic interactions , however , 77% of cases can be folded by I-TASSER to the models below 2 Å . These data demonstrated that the I-TASSER algorithm is indeed selective to native-like sequences , satisfying the minimum requirement for validating the foldability of protein design by computational structure prediction . The data also confirmed that mere coupling of native sequence identity and secondary-structure propensity does not constitute a native-like foldable sequence . For a more realistic test-bed , we collected a set of 45 sequences from previous protein design experiments [18] , [39]–[51] , which include 16 successful designs with the solved structure deposited in the PDB ( folded set ) and 29 unsuccessful sequences ( unfolded set ) defined as “not soluble” , “not folded-CD” , “not folded NMR” , or “natively unfolded” . The unfolded set also includes two of our recent failed designs by EBM on the mouse double minute 2 homolog protein ( MDM2 ) which were experimentally validated as “not folded-CD” , but conceived using a different version of the computational method presented here ( Shultis et al , unpublished results ) . The folded and unfolded sets have a similar average length ( 98 . 1 vs . 97 . 8 ) , with details of the proteins in each set listed in Table S1 of Supplementary Information . Since these proteins have passed various computational feature tests in their designs , these sequences are much closer to real proteins than random sequences . In Figures 2A and 2B , we first ran I-TASSER on the 16 successfully designed proteins and calculated the confidence score ( C-score ) of each model based on the combination of the threading Z-scores and the convergence of the I-TASSER assembly simulations [52] . For each I-TASSER model , we then estimated TM-scores and RMSD values from the C-score using known correlation equations obtained from large-scale benchmark tests [52] . The data in Figures 2A and 2B show that the estimated TM-score and RMSD of the I-TASSER predictions for the designed proteins are highly correlated with the actual TM-score and RMSD , with a correlation coefficient of 0 . 91 and 0 . 80 , respectively . The data therefore confirms that the C-score and the estimated TM-score and RMSD values reflect the actual quality of the predicted models , with the actual TM-score and RMSD mostly within the error bars of the estimated values . In Figure 2E , we applied I-TASSER to both sets of folded and non-folded proteins , where all homologous templates with a sequence identity >25% to the target or detectable by PSI-BLAST were excluded . From Figure 2E , it can be seen that there is an obviously higher percentage of high C-score sequences in the folded design set than that in the non-folded set . The average C-scores are −0 . 003 and −1 . 4 for the folded and non-folded sequences respectively ( see the vertical lines marked in the Figure ) . In Figures 2C and 2D , we present the histogram distribution of the estimated TM-score and RMSD calculated on the C-score values for the two sets of sequences . Again , there is a large gap between folded and non-folded sequences , where the average TM-scores ( RMSDs ) are 0 . 718 ( 3 . 9 Å ) and 0 . 551 ( 6 . 8 Å ) , respectively . In particular , there are much more proteins in the high-quality modeling regions , e . g . with TM-score>0 . 8 or RMSD<2 . 5 Å , for the folded sequences than for the non-folded sequences . This data again shows that there is a greater probability of the I-TASSER simulations generating high confidence models close to the target structures for successfully designed sequences than for unsuccessfully designed sequences . In Table 1 ( second and third columns ) , we present a summary of the I-TASSER structural models for the sequences created by both PBM and EBM in comparison with the target structure , where all homologous templates detectable by PSI-BLAST search were excluded from the I-TASSER template library . The average RMSD and TM-score between the I-TASSER models and the scaffold structures are 4 . 14 Å and 0 . 74 , respectively , for the PBM sequences , while the RMSD and TM-score for the EBM designed sequences are 2 . 12 Å and 0 . 87 , respectively , which demonstrated an improved foldability by EBM . Here , the average TM-scores are higher than the estimated TM-scores obtained for the sequences taken from the previous design experiments . The major reason is due to the different template filters used in the I-TASSER modeling , since an additional stringent sequence identity cutoff ( >25% ) was used in the last section . We have confirmed that similar high TM-score values can be obtained when omitting the second homology filter in sequence identity cutoff during the template search . Moreover , as shown in Figure 2A , the estimated TM-score is on average slightly lower than the actual TM-score . A detailed analysis on the EBM designed sequences indicates that 80% of the predicted structures have an RMSD of <2 . 0 Å to the target scaffold , and 42 . 5% are highly accurate with a RMSD<1 . 0 Å . For the PBM category , only 54% of the predicted structures have an RMSD<2 . 0 Å , and 31% have an RMSD<1 . 0 Å . Having in mind that both the structural profiles and the FoldX potential [53] , which were used to design the EBM sequences , are independent from the I-TASSER folding force field , such a high structural similarity between the I-TASSER models and the target structures indicates that the design algorithm should have captured the features essential to the global fold of the target scaffolds . In Tables S2 and S4 , we list the detailed results of the I-TASSER models for each of the testing protein targets by EBM and PBM , respectively . Compared to the EBM designs , the distribution of TM-scores of the PBM designed sequences is more divergent , i . e . the TM-scores are either very high ( >0 . 85 ) or very low ( <0 . 35 ) , demonstrating that the purely physics-based design is less reliable than the combined physics and evolutionary based EBM approach in designing protein folds . For all 14 cases where the PBM sequences have a low TM-score ( <0 . 3 ) , the combined physics and evolutionary based EBM method drastically improved the TM-scores to >0 . 75 except in 2ZXY_A ( with TM-score from 0 . 20 to 0 . 69 ) . This data highlights the efficiency and robustness of the evolutionary profiles in the design of protein folds , which is consistent with observations from protein structure predictions where profile-based threading approaches have been shown to be much more accurate and reliable than physics-based force fields in recognizing protein folds [1] , [8] . In Column 4 and 5 of Table S2 , we also show the TM-scores of the I-TASSER models to the structural analogs in the profiles and to the scaffold , respectively . On average , the TM-score of the EBM design to the scaffold is 22 . 5% higher than the TM-score to the structural analogs in the profile . The higher similarity of the I-TASSER models to the scaffold than the structural analogs is probably due to the fact that the scaffold is normally located at the center of the structural analog family , since it was used as the probe for the profile construction . Thus , the consensus effect from the profiles tends to drive the design simulations toward the center structure rather than individual analogs , although all the analog sequences contribute to the consensus effect . Noteworthily , the average sequence identities between EBM designs and the target scaffold is 28% , which is higher by seven percentage points than the average sequence identity between the PBM designs and the scaffold ( 21% ) . This data may raise a question on whether the improved folding accuracy from I-TASSER is just due to the increase in the sequence identity . In our previous study [19] , we have demonstrated that the mere coupling of high sequence similarity and secondary structure from random sequences cannot constitute a reasonable rate of I-TASSER folding . Here , we conduct a similar experiment on this set of 87 proteins which randomly generates artificial sequences for each target but with the identity of the artificial sequences to the target being the same to the designed sequences by EBM and PBM , respectively . When we submit the two sets of artificial sequences to the I-TASSER pipelines , both generate non-foldable models of the similarly high RMSD ( ∼9 . 7 Å ) to the scaffold , which is 4 . 6 times higher than that of the EBM design sequences . We have further examined the artificial sequences with a set of more stringent constraints , i . e . with the conserved residues copied from the designed sequences and with the non-conserved residues randomly generated but having a similar residue type ( non-polar , polar-uncharged , and charged ) as the target sequence ( see below for the definition of conserved residues ) . The secondary structures of the artificial sequences from PSSpred predictions [54] are confirmed to be similar to the target with a Q3 score >70% , i . e . at least 70% of residues having the same secondary structure type ( helix , strand or coil ) to the target . By including such constraints , the I-TASSER models of the artificial sequences show much closer similarity to the target , with the average RMSD equal to 5 . 65±2 . 1 Å for the sequences with the same sequence identity as the EBM proteins and to 5 . 72±2 . 2 Å for the sequences having the same sequence identity as the PBM proteins . Nevertheless , the RMSD values of both sets are still significantly higher than the RMSD values of the designed EBM sequences . Despite the difference in sequence identity , the difference in RMSD of the I-TASSER models between the two sets of artificial sequences is negligible compared to the standard deviation . This data again shows that higher sequence similarity in the absence of protein design does not guarantee the significantly more accurate foldability by prediction simulations , or that the drastic improvement in the folding accuracy of EBM sequences ( 2 . 12 Å vs . 4 . 14 Å ) should not be attributed to the increase in sequence identity with the EBM method . To examine the secondary structure ( SS ) distribution of the designed sequences , we developed a new SS prediction method , PSSpred , which combines 7 neural network predictors trained on different PSI-BLAST profiles [54] . In a large-scale test on 3 , 128 proteins , PSSpred achieves a Q3 accuracy of 84 . 5% , which is 3% higher than the widely-used PSIpred program [55] . The fourth column of Table 1 shows the SS assignment results of the designed sequences by PSSpred , in comparison to the DSSP assignment on the target structures [56] . To count for the inherent inaccuracy of PSSpred predictions , we calculate the normalized relative error: NRE = ( EDS−ETS ) /ETS , where EDS is the PSSpred prediction error to DSSP on the designed sequence and ETS is that on the target sequence . The NRE of designed sequence by the EBM is 0 . 33 , which is seven times lower than that by the PBM method ( column 4 , Table 1 ) . In Figure 3 , we showed an example of the designs from the soluble human CD59 protein [PDB ID: 2J8B] . The crystal structure of CD59 possesses five beta-strands and one helix packed in a sandwich fold following the DSSP analysis . All the secondary structure elements are present in PSSpred predictions on the target sequence and the EBM based designed sequences ( Figure 3D ) . However , in the sequence designed by the physics-based force field , three strands are completely missed and instead one more long-helix has appeared in the PSSpred prediction on the PBM sequence . Overall , the Q3 accuracy of the PSSpred predictions is 96% for both the EBM sequence and the target sequence , but the Q3 accuracy of the PBM sequence is only 53% , relative to the DSSP assignment of the crystal structure . As a result , I-TASSER folds the EBM sequence to a structural model of RMSD = 1 . 16 Å to the target ( Figure 3B ) , where the I-TASSER model on the PBM sequence is 9 . 2 Å away from the target ( Figure 3C ) . The reduction in the secondary structure error for the EBM method is mainly due to the smoothening effects introduced by the structural profiles and the single-sequence based SS energy terms , which significantly increase the short-range residue cooperation that are usually missed in the physics-based force fields . These effects thus improve the cooperation of secondary structure propensity and the overall foldability of the designed sequences . To examine the torsion angle and solvation distributions of the residues in the designed sequences , we submitted the designed sequences to sophisticated neural-network predictors [57]–[58] . As shown in Columns 5–7 of Table 1 , the normalized relative errors on Φ , Ψ and solvent accessibility ( SA ) of the EBM designed sequences , relative to the DSSP assignments on the target structures , are 3 . 1 , 4 . 6 and 20 . 5 times lower than the corresponding errors for the PBM sequences . Using the same example of the soluble human CD59 in Figure 3 , the SA assignments on all the residues are highly consistent with the assignments by DSSP on the target structure , with a Pearson correlation coefficient = 0 . 74 . If we turn off the structural profile restraints , the Pearson correlation coefficient of the designed sequences rapidly reduces to 0 . 42 . Accordingly , for this example the NRE on torsion angle ( Φ/Ψ ) of the designed sequence increases from 0 . 04/0 . 15 to 0 . 49/0 . 73 . Most of the Φ/Ψ errors are found to occur in the loop regions but many also occur in the regular secondary structural regions , which influences the folding stability of the designed sequences as demonstrated by the high RMSD of the I-TASSER simulations . In general , a reasonably designed sequence should recapitulate most of the target sequence amino acid identities . However , a high recapitulation rate is not always necessary to guarantee the correct fold and desire function , since a similar fold can be adopted by a variety of protein sequences and families ( e . g . the Tim beta/alpha-barrel fold is taken by 33 superfamilies of variant sequences in the SCOP database ) . In our test set , when using the physics-based FoldX potential , the sequence identity of the designed sequence to native is 21% ( 35% in the core regions ) ( Columns 8–9 of Table 1 ) . When the structural profiles are considered , the sequence recapitulation increases only slightly by 6–7% , i . e . 28% in the whole sequence and 41% in the core region . Considering the identity over whole protein sequence , our EBM designs are comparable with Kuhlman et al ( 27% sequence identity ) [59] but lower than Saunders et al ( 37% ) [60] . In the core regions , however , the native repetition for these methods consistently increased to 51% and 57% respectively , which are significantly higher than our designs . Despite the low sequence recapitulation , the high similarity of the I-TASSER models of the designed sequences to the scaffold structures as reported in Table 1 is striking . To have a better understanding of the implications , we examined the distribution of the recapitulated residues , especially on the evolutionally conserved residues which are often critical to gauge the global fold [61] . For this purpose , we define conserved positions based on the PSI-BLAST sequence family search , i . e . a residue is named as “conserved” if the entropy of the residue ( ) in the multiple sequence alignment of PSI-BLAST search is low ( <−0 . 3 ) . Based on the experimental data in the PDB library , 56% of these conserved residues are located in , or spatially close ( <6 Å ) to , the functional sites and/or the ligand-binding pockets , which further confirmed the biologically importance of the residues . We found that 32% of residues in the conserved positions in the EBM sequences are identical to that in the target and 44% of residues in the conserved regions are highly homologous ( with a BLOSUM62 mutation score>0 . 5 ) to the corresponding residues in the target . In contrast , these percentages are significantly lower ( 23% and 29% , respectively ) for the PBM sequences . These data show that the structural profiles generated in the EBM pipeline help recognize the highly conserved residues in the evolutionary protein families , which are essential for retaining the protein global fold and biological functionalities . As demonstrated in the I-TASSER folding results , these additional conserved residues facilitate the identification of the better quality of structural fragments and frameworks , which are essential to the correct modeling of the global fold of the proteins ( Table 1 ) . Despite the relatively low sequence identity , we found that the amino acid composition and solvation propensity are similar to the target protein . Figure 4 presents the average difference in the fraction of amino acid composition between the designed and target sequences . Here , a positive value indicates a preference for a particular amino acid in the designed sequences over the target sequence , and vice versa for a negative value . Amino acids are plotted from left to right in order of decreasing hydrophobicity . To have more insight into the distribution of amino acid on the 3D structure , residues are further divided into the core and surface regions based on solvent accessibility , i . e . an amino acid is considered to be at the core region if the relative accessible surface area is <0 . 16; otherwise it is on the surface . The EBM derived sequences show a relatively even distribution of amino acids irrespective of their hydropathy scale ( Figure 4A ) . The overall absolute composition difference from the target proteins is 1 . 1% . In comparison , the composition difference with the PBM sequences is ∼3 times larger with an average deviation 3 . 4% . An obvious trend in the PBM sequences is the preference of hydrophobic amino acids over hydrophilic , which were also observed in previous physics-based designs [19] , [24]; this is mainly due to the biasness of physics-based potential ( e . g . FoldX function [53] ) towards hydrophobic residues for the stability of protein . In particular , the PBM mode leads to consistent over-enrichment of Methionine and Proline . This feature may disrupt regular secondary structure elements due to the exceptional conformational rigidity of the amino acids [19] . The structural folds in the PDB library are highly uneven and therefore not all target structures have a sufficient number of analogs . An important issue to the EBM design is to examine how the performance of designed sequences depends on the number of available structural analogs . In our EBM design pipeline , we set a default cutoff of TM-score>0 . 7 to construct the structural profile . Out of the 87 test proteins , 41 have more than 10 structural analogs with TM-score>0 . 7 . The average number of analogs is 51 for these proteins . In the remaining 46 cases , we gradually reduced the TM-score cutoff so that each target protein has at least 10 analogs to construct the structural profiles . As a result , 24 targets have the TM-score cutoff = 0 . 6 and 22 have TM-score cutoff = 0 . 5 . In Figure 5 , we present the I-TASSER folding results on the three groups of designed sequences , which indeed shows a difference in RMSD to the target structure . In general , when a higher number of closely analogous proteins are available , a better quality of structural profile can be constructed to closely characterize the conserved/mutation positions along the designed sequences . In our case , the average RMSD of the I-TASSER models for the first group of 46 proteins is 1 . 46 Å , which is lower than the two other groups based on the lower TM-score cutoffs ( 2 . 57 Å and 2 . 84 Å ) . On the contrary , the folding accuracy on the PBM sequences shows a reversed tendency , i . e . the RMSD of the third group with a TM-score cutoff >0 . 5 is lower than that of the first group with a TM-score cutoff >0 . 7; this is probably because of the slightly shorter chain length of the third group which is relatively easier to fold by I-TASSER . In Figures S4 and S5 , we also show the performance of torsion angles , secondary structure , solvation and sequence recapitulation on the different TM-score cutoffs . A similar dependence is observed on the torsion angles and secondary structures . But the TM-score cutoffs have no obvious influences on the solvation and sequence identities to the target scaffold . These data may raise a concern with the design method for novel proteins which are supposed to have no close structural analogs in the PDB library . In reality , recent studies have demonstrated that the current PDB library is approaching to completeness and almost all the proteins , including random homopolypeptides , can have protein analogs with similar folds ( TM-score>0 . 5 ) in the PDB [62]–[64] . To quantitatively examine this issue , we re-ran our design programs but excluded all analogous proteins with a TM-score>0 . 5 to the target . As a result , the average RMSD of the I-TASSER models indeed becomes relatively higher ( increasing from 2 . 12 Å to 2 . 66 Å for the 87 test proteins ) and the NRE for secondary structure , Φ/Ψ angles becomes larger ( 2 . 11 , 0 . 6 , 0 . 99 , respectively ) . However , these are still much lower than the purely physics-based design methods , demonstrating that the structural profiles , even collected from distantly analogous proteins , are helpful for guiding the design procedures to construct better protein folds . Although the EBM design , combining both evolution and physics-based energy terms , demonstrated clear advantage over the PBM design that uses only the physics-based potentials , it is of interest to examine how the method works if the force field only includes the evolution-based terms ( termed EvBM ) . In the third row of Table 1 , we summarize the results when dropping off the FoldX terms from the EBM design , where the detailed data for each of the targets are listed in Table S3 . Overall , the EvBM results are largely comparable with the EBM method , but clearly outperform that by PBM , in terms of both the structural similarity of the I-TASSER models to the scaffolds and the quality of the local structural feature predictions . In summary , the TM-score of the I-TASSER models on the EvBM design is 11% higher than those created by PBM , and the normalized relative errors of SS , Φ , Ψ and SA by EvBM are 5- , 1 . 6- , 3 . 4- and 10-folds lower than that by PBM , respectively . The average sequence identity between design and scaffold along the entire chain by EvBM is comparable with that by EBM ( 27% vs . 28% ) , while that in the core region is the same as that by PBM ( 35% ) . These data demonstrate again that the evolution-based energy terms , including the profiles and the knowledge-based structure feature predictions , are the major driving force for the designs conducted by the EBM pipeline . Since the EBM design procedure is fully-automated , it has the potential for large-scale protein design applications . Here , as an illustration we apply the pipeline to redesign all solved proteins in M . tuberculosis ( MTb ) genome which contains various pathogens known to cause serious diseases in mammals , including tuberculosis and leprosy . MTb proteins are encoded by 4 , 062 genes where 243 distinct proteins with length up to 296 residues have had their protein structure solved in the PDB library [65] . Table S5 summarizes the redesign results on all the 243 MTb proteins . Overall , the performance data is consistent with the results on the test proteins shown in Table 1 . As shown in Table S5 , the average NRE is 0 . 29 , 0 . 14/0 . 18 , and 0 . 09 for SS , Φ/Ψ , and SA , respectively . The average RMSD of the I-TASSER models is , however , relatively higher ( = 3 . 28 Å ) ; this is mainly due to the difficulty of I-TASSER in folding large proteins since all homologous templates have been excluded from the template library . If we exclude the proteins of length >200 residues , the average RMSD of the I-TASSER models is reduced to 2 . 57 Å; but as expected , other qualities of local structural features ( SS , Φ/Ψ , and SA ) do not change much with the different length cutoffs . In order to assess the diversity of the structural analogs used for profiling the MTb proteins , the number of the analogous structures and the average sequence identity of the analogs to the scaffolds are listed , respectively , in Columns 4 and 5 of Table S5 . If we divide the results into different classes based on the number of structures needed for profile construction , then the trends follow the test set result as shown in Figure 5 and Figures S4 , S5 ( data not shown ) . To partly examine the biological functionalities of the designed MTb proteins , we exploit a well-established structure-based ligand-binding prediction algorithm , COFACTOR [66]–[67] , to search through the comprehensive ligand-protein interaction database , BioLiP [68] , based on both local and global comparisons of I-TASSER models with template proteins . The analysis indicates that 62% of the EBM designed proteins have binding partners with a high confidence score , of which 51 . 3% are enzyme . When using the target scaffold structure as probe , COFACTOR detects slightly less ( 59% ) binding partners , of which 50% are enzyme . Meanwhile , the EBM designed sequences have on average more binding sites ( 6 . 2 per protein ) than the target proteins ( 5 . 5 per protein ) , although the number of binding residues per site are the same ( 7 . 2 ) . In 88 out of the 117 cases ( 75% ) where both designed and target sequences have the binding partner prediction with high confidence by COFACTOR on the same binding site , the binding affinity as assessed by the COFACTOR free-energy calculations is higher in the EBM proteins than in the target . In Figures 6A–C , we show an illustrative example from the MTb thioredoxin C protein [PDB ID: 2I1U] where COFACTOR identifies a binding pocket with high confidence on the EBM protein , but no binding pocket is identified on the target . The designed sequence is 38% identical to the target protein where I-TASSER folds the sequence with an RMSD 2 . 52 Å of the first model to the target structure ( Figure 6A ) . Interestingly , although no natural binding pocket exists in the target , mutations of T35S , G38P , and S79G on the designed sequence change the local binding pocket conformation and therefore facilitate the formation of four hydrogen bonds with the sulfate ion ( dashed line in Figure 6B ) that was identified by COFACTOR as the binding ligand . The binding affinity of this ion ligand is also favored by an independent binding scoring function , X-score [69] , with an affinity score 3 . 45 pKd . As shown in Figure 6C , the ion-binding interaction vanishes in the target protein due to the dominant steric clashes of the side-chain atoms with the putative ligand . In Figures 6D–F , we presented another example from the PZAase of Pyrococcus Horikoshii ( PH999 ) which is known to bind with zinc [PDB ID: 1IM5] . The EBM design on PH999 shows a sequence identity 39% to the target and the I-TASSER model has an almost identical structure to the target ( RMSD = 0 . 28 Å ) ( Figure 6D ) . Although we did not include the metal ion binding and active site information in the design procedure , the designed protein shows remarkable conservation within these regions . For instance , the triad consisting of C133 , K94 and D10 ( color green in Figure 6E ) , which occurs at the bottom of the cavity , and the residues ( D52 , H54 , and H71 ) responsible for positioning zinc ion ( Zn2+ ) , are well preserved in the designed protein but the configuration of H71 is flipped in the model ( red in Figure 6E ) . The cis-peptide bond observed in the target between V128 and A129 at the cavity of PH999 is also retained in the design . Among the 18 residues whose side-chains are involved at the active site , five have been mutated in the EBM design ( V23I , A95G , E101L , A102R , and Y132I ) . All the mutations are spatially clustered together with other active site residues , except for Y132I where one aromatic hydrophilic residue is exchanged for a hydrophobic residue ( yellow in Figure 6F ) . To examine the impact of the mutations and the aromatic exchange on overall ligand binding , we ran COFACTOR based on the I-TASSER model of the designed protein and the target structures , which identified one isochorismic acid binding site ( Figure 6F; space filled atoms ) including Residue-132 for both proteins with a binding affinity 5 . 1 pKd as calculated by X-Score . In addition , the COFACTOR predictions reveal one more sulfate ion binding site with a comparable binding affinity to the target protein ( blue in Figure 6F ) . Apparently , the binding of isochorismic acid is highly competitive with that of sulfate ion in the target , both of which locate at nearly the same site . In the designed protein , the latter was completely eliminated , mainly due to the aromatic exchange at Y132I . Despite the plausible analyses using state of the art computational docking scoring calculations , none of the binding data on the M . Tuberculosis proteins were experimentally validated , which is essential for the eventual confirmation of the biological insights . To facilitate further experimental studies , all designed sequences , the I-TASSER models , and the computational ligand-binding scoring analyses on M . Tuberculosis proteins are made available at: http://zhanglab . ccmb . med . umich . edu/MTb . To experimentally validate the EBM designed sequences , we randomly selected five proteins: four from our benchmark set [heterogeneous nuclear ribonucleoprotein K domain ( hnRNPK , PDBID: 1ZZK ) , thioredoxin domain ( 1R26 ) , cytokine-independent survival kinase phox homology domain ( CISK-PX , 1XTE ) , and light oxygen voltage domain ( Lov2 , 2V0U ) ] , and one from the MTb genome [Translation Initiation Factor 1 ( TIF1 , 3I4O ) ] . These proteins contain different fold types ( 4 αβ- and 1 β-proteins ) with length ranging from 68 to 146 residues . The RMSD of the I-TASSER models are in a typical range from 1 . 33 to 2 . 99 Å , with an average RMSD of 2 . 16 Å , close to the average RMSD of the overall benchmark test ( 2 . 12 Å ) . A list of the proteins is shown in Table 2 . For the designed sequences , constructs were first cloned into MSCG over-expression vectors with an N-terminal Mocr domain [70] , expressed in a Rosetta 2 cell line ( Millipore ) , purified to greater than 95% homogeneity , and then biophysicially characterized by circular dichroism and NMR spectroscopy . As seen in Table 2 , all the designed domains successfully expressed and were soluble after the N-terminal Mocr tag was removed following purification . The domains were first biophysically characterized by circular dichroism to ascertain the presence of secondary structure . Again , all the designs had a negative ellipticity , as shown in the spectra from Figure 7 ( Left Panel ) , indicating that these sequences possess distinct secondary structural elements . The hnRNPK and CISK-PX designs fit well to the typical α-helix/β-strand secondary structure folds with negative mean residue ellipticity troughs at 208 and 222 nm wavelength and clear exciton splitting . The Lov2 spectra have a major minimum at 208 nm plus a slop dip at 222 nm which also indicates a mixed α-helix/β-strand structure . The thioredoxin spectra have an unusual broad minimum at 222 nm , similar to the native E . coli thioredoxin spectra , suggests again a mixed helix/strand structure according to the analysis in [71] . In contrast , the TIF1 domain has almost no 222 nm signal and is dominated by β-strand spectra at 205 nm . In the last two columns of Table 2 , we listed a quantitative comparison of fractions of α-helical/β-strand residues between the designed and the scaffold proteins , where the data on the designed proteins were calculated from an average of the estimations by three CD analysis programs ( CONTINLL [72] , CDSSTR [73] , and SELCON [74] ) on the CD spectra in Figure 7 and the secondary structures of the scaffolds were calculated by STRIDE [75] . The data showed that the secondary structure fractions in the designed sequences are largely consistent with those in the corresponding scaffold structures . Following the CD experiments , the designed domains were analyzed by 1H 1D NMR spectroscopy . Specifically , we used NMR to probe the existence of a well-folded , stable , protein core , which is detectable by a shift of the side-chain resonances upfield ( more negative ) and by the dispersion and resolution of the amide protons . As shown in the Right Panel of Figure 7 , the hnRNPK and Lov2 designs lacked upfield methyl chemical shifts ( −1 . 0-0 . 5 ppm ) and had sparse features in the protein amide range ( 5 . 5–10 . 0 ppm ) ( Figures 7F and 7I ) , which suggest that they do not possess a stable fold . By contrast , the designs for the thioredoxin , CISK-PX and TIF1 domains showed strongly shielded methyl shifts between 0 . 5 and −1 . 0 ppm and had well-resolved peaks in the amide region , features that are indicative of proteins possessing stable folds . Free energies of folding for the thioredoxin and CISK-PX designs were further determined by CD using urea as a chemical denaturant ( we did not conduct the unfolding experiment on the TIF1 domain because it was observed to lack significant negative ellipticity at 222 nm ) . As shown in Figure 8 , the designed thioredoxin domain started to unfold at ∼7 . 5 M urea and complete unfolding of the protein was not achieved with 9 . 5 M urea . In contrast , CISK-PX was completely unfolded by 8 . 5 M urea . Free energies of folding for the thioredoxin and CISK-PX domains were calculated by linear regression from the data points available and determined to be −16 . 1 and −29 . 6 kJ/mol , respectively [76] . Despite unfolding at a higher concentration of urea , the thioredoxin domain had a slower transition to an unfolded state and is thus less stable than the CISK-PX domain .
Deducing structure models from evolutionarily related proteins has been established to be the most reliable method for protein 3D structure prediction . Following a similar spirit , we introduce the idea of structure profile to protein design , a reverse procedure of protein folding and protein structure prediction . The key step of the approach is to construct an evolutionary profile from a family of proteins that have similar fold to the target structure . Such a profile matrix helps to identify the conserved/variable positions along the sequence , which are important in protein evolution and critical for maintaining the global structural fold and functionalities . Technically , since the foldable sequence space of a specific protein target is extremely narrow ( few sequences can fold to the structure ) , targeting the design to an envelope of proteins of similar folds can increase the breadth of free-energy landscape and meanwhile enhance the robustness of the designed sequences upon structural variations . One technical issue is that the profile-based design may simply converge to the consensus of the multiple sequence alignments , which can have discrete physiochemical feature distributions along the sequences . To alleviate the problem , we developed a set of single-sequence based predictors to regulate the secondary structure , torsion angles and solvent accessibilities . These predictors are fast and based only on a single sequence but the accuracy is comparable with the more sophisticatedly trained predictors using multiple sequence alignment searches ( see Text S1 and Figures S1 , S2 , S3 for details ) . To accommodate the steric and physiochemical interactions of residues , a physics-based atomic potential ( FoldX ) is introduced on the top of the profile-based energy terms . The method is tested on the design experiment of 87 non-homologous single-domain proteins covering different fold classes . Compared to the sequences designed only on the physics-based energy terms ( PBM ) , significant improvement has been observed on the general features of the designed sequences , where the normalized relative errors are reduced by 7 times for secondary structure , 3 ( 5 ) times for Φ ( Ψ ) angles , and 21 times for solvent accessibilities . These improvements are partly attributed to the smoothening effect of the structural profile weighting and the restraints from the knowledge-based feature predictions . When submitting the sequences to the I-TASSER structure assembly pipeline , an average RMSD of 2 . 12 Å is achieved to the target structures although all homologous templates detectable by PSI-BLAST were excluded from our predictions ( Table 1 ) . Since the force field and phase space searching used by protein design and I-TASSER folding are independent from each other , such a high consistency between the I-TASSER models of the designed sequence and the target scaffold indicates that the design procedure using the structural profiling should have captured the features that are essential to generate the overall fold of the proteins . The identity of the designed sequences to the target is relatively low ( 28% ) ; but the identity of residues in the evolutionarily conserved regions is much higher ( i . e . 44%; in comparison , only 23% residues are conserved in these regions in the PBM designed sequences ) . This data shows the effect of structural profiles in recapitulation of evolutionarily conserved positions . Meanwhile , the amino acid composition is closely similar to that of the target sequences . Compared to sequences generated by PBM , the absolute composition difference from the native sequence is reduced by more than three times ( from 3 . 4% to 1 . 1% ) , and the bias of designed sequence to Proline is completely eliminated in EBM . The inclinations of hydrophobic residues over the hydrophilic and charged residues in PBM are also reduced greatly . These improvements facilitate the designed sequences in retaining the balance of the amino acid distributions along the sequence . Because the design procedure is fully-automated , it has the potential for large-scale protein design applications . As an illustration , we applied the EBM method to redesign all 243 solved proteins from M . tuberculosis . The designed sequences can be folded by I-TASSER to the structures of average RMSD 3 . 28 Å without using homologous templates ( or 2 . 57 Å for the proteins below 200 residues ) . In 75% of the cases where there is a confident binding partner on the same binding site , the binding affinity is higher in the EBM proteins than in the target , as shown by the binding free-energy calculated by COFACTOR [66] and X-score [69] . Two typical examples were shown in Figure 6: for thioredoxin , a new binding pocket was formed by the mutation of three key residues in the active site , which improved the binding pocket shape and hydrogen-bonding network with the ligand; for PZAase , although the overall sequence identity is only 39% , the triad , cis-peptide and metal ion binding residues at the active site are well conserved on the designed sequence . Nevertheless , one of the two competing binding sites ( the one with sulfate ion ) was eliminated by the mutation of Y132I in which one aromatic hydrophilic residue is replaced by a hydrophobic residue . Although these calculations were based only on computational docking analysis without stringent experimental screening , the converging data from different analysis methods show the possibility of varying substrate scope and binding affinity via the redesign of the active site residues to alter the catalytic activity of enzymes . A handful of sequences were randomly selected from the EBM designed sequences for experimental validation . These sequences have a length ranging from 68 to 146 residues and cover different fold types . All the designed sequences were found to be soluble and possess distinct secondary structures as witnessed by the negative ellipticity in the circular dichroism experiment . Three out of the five sequences ( thioredoxin , CISK-PX , and TIF1 ) were revealed to possessed stable tertiary structures by 1H 1D NMR spectra . Further , urea denaturation experiments combined with linear regression showed that the domains of thioredoxin and CISK-PX are stable with the free energies of folding below −16 kJ/mol . These experiments , although incomplete for all designed targets , demonstrated the EBM represents is a robust protein design tool capable of making novel sequences that adopt stable tertiary folds , with a quite reasonable success rate ( ∼3/5 ) . It should be mentioned that many methods in the literature have been developed to design proteins with either improved functions or completely novel folds through the mutation of natural sequences or de novo design calculations . One motivation for the development of EBM is to provide a reliable platform that can design any protein with improved foldability using the restraints from evolutionary profiles of similar fold families . With this platform , the functional characteristics , including enhanced and/or alternative ligand bindings for instance , can be further introduced . In a recent achievement ( Brender et al , in preparation ) , we have demonstrated that the introduction of specific interface potentials to the current EBM platform be used to create altered binding affinity of natural or drug ligands on the designed proteins , as shown by computational scoring calculations as well as preliminary experimental data . Overall , our study demonstrates the potential of using evolutionary based information in conjunction with the physics-based force field for de novo protein design . This opens up a new avenue in computational protein design to improve the biological and structural properties of the designed protein sequences . It also provides an exciting possibility to extend the existing template libraries for protein 3D structure predictions , which is under exploration in our lab .
The first step of EBM is to construct a structure profile which will be used to guide the sequence design simulation and selection . For a given target protein structure ( or scaffold ) , the profile is constructed from a family of structural analogs that are collected from a non-redundant set of the PDB library by the structural alignment program , TM-align [77] , using the scaffold as the probe . For each structure alignment , the TM-align returns a TM-score to assesses the structural similarity of the PDB protein to the scaffold protein [78] . In general , the TM-score ranges from 0 to 1 with a higher value indicating a higher structural similarity , and a TM-score value>0 . 5 roughly corresponds to the similarity seen for proteins within the same SCOP/CATH family according to the database analyses [79] . In our design procedure , all PDB proteins with a TM-score>0 . 7 are considered to be a structure analog and added to the structural profile pool . If less than ten structural analogs are detected from the PDB with a TM-score>0 . 7 , we gradually reduce the TM-score cutoff until the number of analogs is above ten to ensure a sufficient number of proteins for the followed-up profile construction . To specify the conservation/variation residues in the analogy protein family , we construct a profile matrix following the idea of Gribskov et al [3] , which was designed to extract the position-specific scoring table from the multiple sequence alignment ( MSA ) . Here , the MSA is collected from the pair-wise TM-align structural alignments between the PDB protein and the scaffold but with the gaps/insertions eliminated according to the residues appearing along the scaffold sequence . The structural profile is specified by an L×20 matrix , where L is the length of the scaffold sequence ( and the MSA ) and 20 is the number of different amino acid types . The elements of the matrix for amino acid a at position p is given by . Here B ( a , x ) is the BLOSUM62 substitution matrix with x varying for 20 amino acids , and w ( p , x ) is the frequency of the amino acid x appearing at the pth position in the TM-align MSA . To account for the potential bias to specific protein families due to the uneven distribution of the PDB structures in the sequence space , we reweighted each residue in the MSA by a Henikoff-Henikoff scale H ( p , x ) , i . e . . Here , we note that the evolutionary profiles have often been defined from sequence-based homologous search , e . g . through hidden-Markov model [80] or PSI-BLAST [81] searches . The reason for us to choose structure analogs is due to the consideration that the profiles from structural analogs should be more sensitive to the desired folds of the scaffold , since numerous data analyses have shown that structure is more robust than sequence against the evolutionary variations and sequences of high residue identity may adopt completely different folds and functions [82] . Indeed , we have tried to use the sequence homologies instead of structural analogs or use the sequence homologies on top of the structural analogs for the profile construction , but found that the inclusion of sequence homologies increases the sequence diversity of the simulations , as well as increase the normalized relative errors and the RMSD of the I-TASSER predictions on the designed sequences . Starting from a randomly generated sequence , Metropolis Monte Carlo simulations are conducted to search through the amino acid sequence space for the sequences that best match with the target structural profile . At each step of movement , a set of randomly selected residues will be mutated randomly . The energy function of the MC search consists of two parts . The first part counts for the alignment match of the sequence decoy with the target structural profile: ( 1 ) where the first term is the structural profile defined above; the second , third and fourth terms in Eq . 1 are the difference of the decoy and target sequences in secondary structure , solvent accessibility and torsion angles , respectively . Because the predictions of these structural features are needed for each step of the MC movements , a quick neural-network predictor is developed based on single sequence for the decoy sequence which is much faster ( takes ≪1 s ) than the normal PSI-BLAST based predictors but with comparable prediction accuracy ( see Text S1 and Figures S1 , S2 , S3 for details ) . The SS , SA and Φ/Ψ features for target structure is assigned by the DSSP program [56] . The optimal alignment path between the decoy and target structure is obtained by the Needleman-Wunsch dynamic programming with the maximum score assigned as Eevolution in Eq . 1 . The second part of the energy function contains a physics-based force field from FoldX V3 . 0b5 [53] , designed to further enhance the stability and local structure packing of designed sequence . It consists of 9 empirical terms [53] , [83]: ( 2 ) where Evdw is the sum of the van der Waals contribution of all atoms; EsolvH and EsolvP count for the solvation energy for apolar and polar groups , respectively; Ewb is the water bridge hydrogen bonding between water and protein; Ehb is the intra-molecule hydrogen-bonding; Eel counts for the electrostatic contribution of interactions between charged groups; Emc and Esc are entropy costs for fixing main-chain and side-chain atoms in a particular conformation , respectively; and Eclash counts for the penalty from atomic steric overlaps . The parameters f1–9 were trained by maximizing the correlation between the calculated and experimental free-energy changes on a set of experimental residue mutants . The detail of FoldX potential design and parameterization can be found in Refs [53] , [83] . We used the default parameters for the FoldX calculation , except for the van der Waal weight f1 which was increased to 0 . 33 to eliminate the extra steric clashes observed in our simulations . Since FoldX potential is full-atomic , we use SCWRL V4 . 0 [84] to construct the side-chain conformations after each MC movement . To balance the two parts energy terms which are derived from different resources , we renormalized the energy terms based on their deviations: ( 3 ) where and δE are average and standard deviation of the energy scores calculated from previous steps of simulations . The weight parameters in Eqs 1 and 2 ( w1–5 ) were determined on a set of 625 non-redundant training proteins that are non-homologous to the test set and case study proteins ( see http://zhanglab . ccmb . med . umich . edu/EvoDesign/list625 . txt ) . For w1–3 in Eq . 1 , the weights are decided by the relative accuracy of the individual feature predictions , i . e . w1 = C*ASS , w2 = C*ASA , w3 = C*ATA , where ASS , ASA and ATA are the number of correctly predicted residues on secondary structure ( SS ) , solvent accessibility ( SA ) and torsion angles ( TA ) , respectively , divided by the total number of residues on the training proteins . C is the parameter to balance the average magnitude of feature predictions with that of the profile term . The final weights for Eq . ( 1 ) are: w1 = 1 . 58 , w2 = 2 . 45 , w3 = 1 . For Eq . ( 2 ) , the weights were adjusted so that the average contribution from the evolution terms and the physics based terms are comparable based on the designing simulation of the 625 training proteins . The final decided weights are w4 = −0 . 5 , w5 = 1 . 22 . Following each of the random mutation trials , the movement is accepted or rejected by the Metropolis criterion , i . e . with the acceptance rate ∼ , where β is the Boltzmann temperature factor and Enew and Eold are the energy calculated for the sequences after and before the mutation , respectively , based on Eq . ( 3 ) . We have conducted two control studies to the EBM design . In the first , the protein design by physics-based force field ( PBM ) was conducted following a procedure similar to the EBM simulation but the MC energy score contains only the FoldX function . i . e . , we set w4 = 0 and w5 = 1 in Eq . ( 3 ) . In the second , we consider only the evolution based energy potential , termed EvBM , i . e . we set w4 = −1 . 0 , w5 = 0 . 0 in Eq . ( 3 ) . For each target , ten independent Monte Carlo runs , each starting from a different random sequence , are performed . The final designed sequence is selected by clustering all the sequence decoys generated in Monte Carlo simulations . The clustering procedure is implemented by an algorithm similar to SPICKER with the distance matrix between sequence decoys defined by BLOSUM62 substitution scores , following the procedure by Bazzoli et al [19] . Initially , the distance threshold is set as zero but increases gradually until the size of the largest cluster reach to 40% of the total number of sequences . Upon termination , the sequence corresponding to the highest number of neighbors is considered a designed sequence . In the Metropolis Monte Carlo simulations , the number of decoys at each sequence cluster nc is proportional to the partition function ( Zc ) of the conformational search , i . e . , where the logarithm of the cluster size is thus related to the free-energy of the simulation by . Thus , the design sequences with the largest cluster size in EBM should correspond to the state of the lowest free-energy in our simulations . Our sequence design simulations contain the calculation of two parts of energy terms , Eqs . ( 1 ) and ( 2 ) . Since the structure feature prediction is single-sequence dependent , the calculation of the evolutionary terms is fast and takes only fraction of seconds per sequence per Monte Carlo step . The calculation of the second term from FoldX is however much more expensive ( up to minutes per sequence ) which is mainly due to the side-chain conformation calculation by the SCWRL program . In our test on the 87 proteins , the average simulation time of our method without using FoldX is 3 . 8 hours , while including FoldX increases the time for the program to 16 . 5 hours . Another important factor impacting the time cost and the quality of designed sequences is the dynamics of the Monte Carlo simulations . The current EBM programs implemented 10 independent Metropolis MC runs , each running 30 , 000 mutation movements . Due to the inherent limit of the Metropolis algorithm whereby the acceptance rate of movements is proportional to the inversed exponential of the height of energy barriers ( see above ) , the individual MC simulations can be easily trapped at local minimum . In our test , the pair-wise sequence identity between the lowest energy sequences of ten different runs is low ( 28% on average ) , which demonstrated the divergence of the Metropolis simulations and some simulations might have trapped at local minimum . Accordingly , the average RMSD of the I-TASSER models on the ten lowest energy sequences from the ten MC runs is 3 . 7 Å , 1 . 5 Å higher than that obtained for sequences selected from clustering ( see Table 1 ) , which demonstrates the necessity of multiple MC runs and the usefulness of sequence clustering . We also tested the simulations starting from one of the sequences used in the profile or from the consensus of the MSA . The average results are similar to that of the simulations starting from random sequences , including the average RMSD of the I-TASSER models of the designed sequences and the pair-wise sequence identity between the lowest energy sequences of different runs . The average identity between final sequence and the starting seeds is also low ( <30% ) , which indicates that the simulations did not stick to the seeds when starting from the sequences in the profile . The similar average results were also obtained if we start the 10 independent simulations from the same sequence but with different random numbers . Nevertheless , we choose to have the EBM simulations started from different random sequences in our designs , which should help avoid the possible bias as introduced by specific starting sequences . Finally , we have tested running more than 10 MC simulations , but the assessment results are not improved compared to the 10 runs , in terms of average sequence identity , normalized relative error and the RMSD of the final I-TASSER models to scaffold . The data implies that 10 simulation runs are probably sufficient for obtaining converged results . Nevertheless , 10 runs might still be too expensive , especially for large-scale design applications . We are testing the use of more advanced MC techniques , including replica-exchange sampling [85] and simulated annealing [86] , with the aim to improving the speed and kinetics of the EBM simulations . The results will be reported elsewhere . Five proteins were randomly selected from the EBM based design for experimental validation . The DNA and protein sequences of the proteins are listed in Text S1 . The DNA sequences for the designed domains were cloned into a mOCR domain over-expression vector via ligation independent cloning [70] . The expression construct contains a N-terminal solubility tag consisting of 6×His tag , a Mocr solubility domain , and a rTEV protease site . The following N-terminal artificial cloning residues , “SNA” , remain after rTEV protease cleavage during purification . Design constructs were transformed into a Rosetta 2 E . coli expression cell strain ( EMDmillipore ) . Cells were grown in LB media with ampicillin at 0 . 1 g/L at 310 K until mid-log phase . At a cell density of 0 . 6–1 . 0 OD ( 600 nm wavelength ) protein expression was induced by the addition of 0 . 2 mm IPTG for 5 hours at 305 K . All temperatures were at 277 K during purification and biophysical characterization unless declared otherwise . Cells were harvested by centrifugation and resuspended in 50 mM Tris pH 7 . 5 , 150 mM NaCl , 5 mM imidazole , and then lysed by sonication ( Fisher model 705 series ) . Samples were subsequently centrifuged [30 , 000 g×30 min Beckman J26-XP ( JA25 . 50 rotor ) ] to pellet cell debris . The supernatant was incubated with Ni-NTA resin ( Qiagen ) and washed with 50 bed volumes of resuspension buffer . The protein was subsequently eluted with resuspension buffer plus 200 mM imidazole . After being dialyzed overnight in resuspension buffer and rTEV protease , the cleaved N-terminal tag containing the mOCR domain was removed via substractive Ni-NTA and anion exchange Acro-sep Q ( Pall ) purification . The eluate was subsequently concentrated using 3–10 K MWCO concentrators ( Pall ) . A final purification polishing step by size-exclusion gel filtration using a ( GE ) AKTA chromatographic work station and an S-100 column was conducted . Circular dichroism spectroscopy was conducted to determine if the designed domains had secondary structure . An Aviv 202 CD spectropolarimeter was used for all experiments . Wavelength scans from 190–250 nm were conducted with 2 sec averaging and 1 . 5 nm slit width . Experimental conditions were 20 mM NaPO4 pH 7 . 5 , 50 mM NaCl at 288 K . Protein concentration was 2–4 µM . Measurements were in millidegrees ellipticity , which was then converted to mean residue ellipticity ( MRE ) for analysis . Data was collected in triplicate , and averaged . To analyze protein stability , unfolding experiments were conducted in 25 mM NaPO4 pH 7 . 5 , 150 mM NaF at 298 K with increasing concentrations of urea as a denaturant ( up to 9 . 5 M ) . Ellipticity values at 222 nm were recorded for each sample . NMR spectroscopy was conducted to determine if the designed domains possessed stable tertiary folds . 1H 1D NMR spectra were recorded using a Bruker 600 MHZ spectrometer with cryoprobe at 20 mM NaPO4 pH 7 . 5 , 150 mM NaCl , and 298 K with protein concentrations ranging from 70–100 µM . | The goal of computational protein design is to create new protein sequences of desirable structure and biological function . Most protein design methods are developed to search for sequences with the lowest free-energy based on physics-based force fields following Anfinsen's thermodynamic hypothesis . A major obstacle of such approaches is the inaccuracy of the force-field design , which cannot accurately describe atomic interactions or correctly recognize protein folds . We propose a novel method which uses evolutionary information , in the form of sequence profiles from structure families , to guide the sequence design . Since sequence profiles are generally more accurate than physics-based potentials in protein fold recognition , a unique advantage lies on that it targets the design procedure to a family of protein sequence profiles to enhance the robustness of designed sequences . The method was tested on 87 proteins and the designed sequences can be folded by I-TASSER to models with an average RMSD 2 . 1 Å . As a case study of large-scale application , the method is extended to redesign all structurally resolved proteins in the human pathogenic bacteria , Mycobacterium tuberculosis . Five sequences varying in fold and sizes were characterized by circular dichroism and NMR spectroscopy experiments and three were shown to have ordered tertiary structure . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis |
Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples . These analyses yield specific predictions—the population frequency of individual clones , their genetic composition , and their evolutionary relationships—which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia , each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples . Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material . In addition , it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity . Accordingly , we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid . Furthermore , we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective , scalable , and adaptable to the analysis of both hematopoietic and solid tumors , or any heterogeneous population of cells .
Intratumoral heterogeneity is an emerging hallmark of cancer that can be interrogated genome-wide with next-generation sequencing . Critically , sub-populations of tumor cells are organized into hierarchies through clonal evolution . A powerful strategy for studying this population structure is multi-sampling—independently assaying genetic variation at distinct points in time or space and comparing mutation profiles . In particular , whole genome sequencing ( WGS ) of de novo acute myeloid leukemia ( AML ) has demonstrated genetic evolution between diagnosis and relapse [1] , [2] , and similar results have been obtained from WGS of paired primary-metastasis samples in breast cancer [3] . Furthermore , whole exome sequencing ( WES ) of multiple regions within primary tumors has revealed extensive regional heterogeneity in pancreatic [4] , hepatocellular [5] , and renal [6] carcinomas . Thus , clonal heterogeneity within tumors compounds the biological complexity of human cancers , and a detailed understanding of this is important for clinical genomics . The ultimate resolution of multi-sampling is single-cell analysis , which is rapidly becoming tractable . For example , Anderson et al . have used fluorescence in situ hybridization ( FISH ) to genotype up to five so-called “driver” lesions in individual pediatric acute lymphoblastic leukemia ( ALL ) cells , which demonstrated a range of clonal architectures ( from linear to complex ) in different subjects [7] . Jan et al . , Potter et al . , and Klco et al . have reported similar findings using either single-cell allele-specific PCR or amplicon sequencing to assay five to ten clonal markers in de novo AML or pediatric ALL [8]–[10] . In broader ( genome-wide ) analyses , Navin et al . and Voet et al . have leveraged WGS to call copy number variants ( CNVs ) in single cells , which they used to reconstruct the phylogenetic history of breast cancer cell lines and primary tumors [11] , [12] . In addition to multi-sampling strategies , we and others have reported clonal inference from deep sequencing of individual tumor samples [1] , [13]–[15] . Briefly , this approach uses the fraction of sequencing reads calling a specific somatic mutation ( i . e . , the variant allele fraction , or VAF ) to estimate the frequency of that variant in the original sample . Often , large numbers of single nucleotide variants ( SNVs ) cluster at a common VAF , suggesting the presence of a clonal population at a defined frequency . Analyzing tumors in this way yields specific predictions about the clonal relationships among variants detected in unfractionated samples: 1 ) the genetic composition of individual clones ( groups of SNVs that arose together ) , 2 ) the frequency of each clone ( proportional to the mean VAF of the corresponding cluster ) , and 3 ) a model for how the clonal architecture evolved ( clones at lower frequencies descending from those at higher frequencies ) . We set out to test these predictions by sequencing single cells from three subjects with an initial diagnosis of myelodysplastic syndrome ( MDS ) , each of whom progressed to secondary AML ( sAML ) . We had previously characterized these subjects by WGS of both MDS and sAML bone marrow as well as matched skin samples , resulting in a call set of several thousand validated somatic mutations in addition to specific models for the clonal architecture of each tumor [14] . In the current study , we used targeted sequencing to genotype >1 , 900 of these positions in a dozen single cells from each subject . We used SNP array data to quantify the accuracy of single-cell variant calling , and—as reported by others—we observed frequent genotyping errors due to stochastic biases in whole genome amplification ( allelic dropout , or ADO ) [11] , [12] , [16] . Nevertheless , while ADO inflated our false negative rate , we maintained a relatively low false positive rate . It was therefore possible to evaluate the major clonal relationships among targeted variants using single-cell sequencing . Ultimately , the single-cell data strongly supported the major clonal populations predicted from the analysis of bulk tissue , in addition to resolving the clonality of SNVs that were originally ambiguous and suggesting previously unappreciated complexity among rare subclones . Accordingly , our findings validate many of the critical assumptions underlying the inference of tumor clonality from unfractionated samples , in addition to demonstrating a high-throughput approach to single-cell genotyping that provides insight into the clonal architecture of heterogeneous samples .
We prepared a total of 56 sequencing libraries from whole genome amplified ( WGA ) single-cell and two-cell sAML samples in addition to non-WGA unfractionated MDS , sAML , and normal ( skin ) samples ( Table S1 ) . We used hybridization capture to enrich these libraries for 1 , 953 somatic SNVs discovered and validated previously in unfractionated samples [14] ( Table S2 ) . Sequencing yielded 4 . 1 Gb of de-duplicated data that aligned to targeted loci , resulting in an average depth of coverage of 148× per sample ( Table 1 , Table S3 ) . The subject identity corresponding to each sequencing library was confirmed using variant calls at both germline SNPs and targeted somatic SNVs ( Table S4 , Table S5 ) . In order to assess the quality of our capture reagent , we compared the VAF distributions of variants in unfractionated MDS and sAML samples to those previously reported [14] ( Figure S1 ) , finding a strong correlation between these independently-generated datasets ( R2 = 0 . 66–0 . 96 ) . Consistent with previous reports , we observed a number of differences in sequencing performance between WGA libraries and those prepared from unfractionated material [11] , [12] , [16] . In particular , single- and two-cell libraries had a lower proportion of the capture target covered at any threshold ( Figure 1A ) . This was attributable in part to 20% fewer reads obtained from libraries prepared from WGA material ( Table 1 ) . Furthermore , these libraries had a lower on-target rate ( likely driven by locus dropout ) and a higher rate of PCR duplicates ( i . e . , reduced library complexity ) ( Table 1 ) . In addition , single- and two-cell samples had a significantly less uniform distribution of reads across the capture target ( Figure 1B ) , again reflecting WGA biases . In aggregate , these technical issues limited callable positions ( sites with ≥25× coverage ) to approximately 55% of targeted SNVs in single- and two-cell samples ( 41%–63% for single-cell and 46–53% for two-cell libraries ) . To quantify the accuracy of variant calling in single cells , we examined germline ( i . e . , inherited ) SNPs genotyped previously using Affymetrix 6 . 0 arrays . We evaluated three separate variant callers: SAMtools [17] , VarScan2 [18] , and the Genome Analysis Toolkit ( GATK ) Unified Genotyper [19] , [20] . With SAMtools and VarScan2 , we called variants from individual samples , whereas with GATK , we called variants jointly across all single-cell libraries . At homozygous SNPs , all three callers performed similarly ( Figure 2A , 2B ) . However , at heterozygous SNPs ( which best approximate targeted SNVs ) , calling samples jointly yielded a modest benefit in sensitivity , while reducing specificity ( Figure 2C ) . Based on these results , we chose to call variants jointly using GATK at sites with ≥25× coverage , and we estimated our sensitivity and specificity for singe-cell variant calling to be 0 . 88 and 0 . 98 , respectively . As a caveat , benchmarking joint variant calling at germline SNPs ( which are present in every cell ) potentially overestimates sensitivity to detect subclonal SNVs ( which may be present in only a subset of cells ) . Nevertheless , joint variant calling likely offers a genuine increase in sensitivity , without incurring much cost in specificity , especially when calls are restricted to sites with high coverage . As shown in Table 2 , the majority of genotyping errors ( assessed at germline SNPs ) were false negatives , i . e . failures to detect true non-reference alleles , which resulted in reduced true positive rates ( TPRs ) . These occurred exclusively at heterozygous positions in libraries prepared from WGA material , implicating ADO as the underlying mechanism ( approximately equal to the false negative rate , or FNR ) . This assumption is further supported by the observation that the frequency of homozygous reference calls was similar to that of homozygous variant calls at known heterozygous SNPs ( Figure S2 ) . ADO is a well-documented limitation of commercial single-cell WGA kits [11] , [12] , [16] . Nevertheless , although our analysis of germline SNPs demonstrated that single-cell reference allele calls were enriched for false negatives ( at heterozygous positions ) , it also showed that non-reference allele calls were generally accurate ( overall false positive rate , or FPR , approximately equal to 0 . 02 ) . This asymmetry between FNR and FPR was critical for differentiating genuine clonal relationships among targeted SNVs from genotyping errors . Finally , we tested whether ADO could be linked to systematic ( i . e . , locus-specific ) effects , or if it was predominantly stochastic . To do this , we compared the rate at which inherited heterozygous SNPs common to all three subjects were called reference in single-cell libraries ( Figure S3 ) . In general , the dropout rate of a specific locus across single-cell libraries from one subject was not predictive of its dropout rate across single-cell libraries in another ( R2 = 0 . 25–0 . 30 ) , suggesting that ADO was not attributable to strong positional biases . As an additional quality control measure , we asked if the VAF distribution in single cells could be used to infer sample cellularity . In single cells , the true ( unobserved ) VAF of heterozygous variants is 0 . 5 ( at diploid loci ) . As shown in Figure S4 , S5 , S6 , the VAF distributions in single-cell samples exhibited high variance ( ranging from 0 to 1 ) compared to unsorted samples , reflecting stochastic biases in WGA . However , the mean VAF for each cluster , as well as for germline heterozygous SNPs , was fixed at approximately 0 . 5 . In contrast , in intentionally “cross-contaminated” two-cell samples , the mean VAF of individual clusters ( but never germline heterozygotes ) dropped to 0 . 25 , the precise dilution expected from the admixture of two cells sharing some , but not all , heterozygous SNVs ( Figure S4 , Figure S6 ) . To analyze this further , we modeled these distributions computationally and used maximum likelihood analysis integrating a site-specific error model to assess the probability that each dataset was generated from all possible combinations of two cells . This predicted that >90% of single-cell libraries were derived from true single-cell samples ( Table S7 ) . Previously , we generated WGS data from MDS , sAML and normal samples for each subject in the current study , and we analyzed the VAF distribution of validated somatic mutations to infer the clonal architecture of each tumor [14] . In the current study , we applied SciClone—a variational Bayesian algorithm—to the original WGS data to refine these models [13] , [21] . As shown in Figure 3A–C , groups of SNVs cluster at distinct frequencies , and we hypothesized that each cluster represented a clonal population of tumor cells . I . e . , clustered SNVs were predicted to colocalize within individual cells . Furthermore , we predicted that the population frequency of putative clones was proportional to the mean VAF of the corresponding cluster . Finally , we hypothesized that clones present at successively lower frequencies evolved linearly from clones at higher frequencies , i . e . , that these populations were nested . Accordingly , subjects were predicted to be monoclonal ( UPN182896 ) or biclonal ( UPN461282 , UPN288033 ) at the time of MDS diagnosis , and harbor two or more clones upon progression to sAML ( Figure 3D ) . In addition , our analysis of both unfractionated blood and bone marrow samples indicated that tumor clonality was similar in both compartments ( consistent with recent findings in both de novo AML and MDS [10] , [22] ) , though UPN288033 had an overall reduction in tumor cells in peripheral blood ( Figure S4 , S5 , S6 ) . To evaluate models of tumor clonality predicted from unfractionated samples , we overlaid tracks of single-cell variant calls on the cluster definitions derived previously ( Figure 4 , Figure S7 ) . In general , single-cell mutation profiles strongly supported the existence and composition of the predicted clonal populations . We observed multiple cells from each subject harboring the majority of targeted SNVs , and at least one cell in each subject in which complete clusters of putatively subclonal variants were called reference . Single-cell sequencing thus demonstrated the existence of distinct cells arising at successive points in tumor evolution , in addition to validating our hypothesis that SNVs present at similar VAFs travel together in individual cells . As shown in Figure 4 , we observed a significant rate of reference calls ( 15% , on average ) in each cell at sites predicted to be within a mutation cluster . Formally , this could reflect cryptic subclonal heterogeneity , but these positions could not be aggregated into clusters of more than a few variants . Furthermore , mutually exclusive sets of variants that were reference in cells representing the founding clone were recovered in cells corresponding to more mature clones , which would imply an unlikely rate of convergent evolution . Alternatively , these reference calls likely represent stochastic false negatives in each cell . Indeed , the rate of these reference calls was consistent with our estimated FNR ( due to ADO ) of 0 . 12 . Accordingly , the majority of these reference calls likely reflect ADO ( are false negatives ) , not cryptic population substructure . While the single-cell genotypes we obtained generally validated our predicted model , they suggested a number of modifications . First , there was ambiguity in our original analysis as to which clone gave rise to cluster 5 variants in UPN461282; this appeared to be a rare subclone that could have emerged from any of its predecessors . The single-cell data unambiguously show that cluster 5 SNVs descended linearly from cluster 4 ( i . e . , cluster 5 variants always colocalized with cluster 4 variants ) . Second , approximately 9% of targeted SNVs could not be clustered in our original study , i . e . , the clone to which they belonged was ambiguous . For UPN461282 and UPN288033 ( for which we had multiple cells representing each clone ) , we were able to confidently assign 50% of these outliers to specific clones ( Figure 4A , C ) . For UPN182896 ( for which we only had one cell representing the founding clone ) , we were only able to recover 35% of outliers ( Figure 4B ) . In addition to resolving the clonality of ambiguous clusters and outliers , the single-cell data identified a small set of variants that were mutually exclusive across multiple cells in each subject—suggesting that a subset of targeted SNVs may in fact represent subclones within the cluster to which they were originally assigned ( Figure 4 ) . For UPN461282 , this occurred among low-frequency cluster 5 variants . Only 20 of the 60 variants we targeted in this cluster were detectable—suggesting that these variants were enriched for false positives or belonged to additional rare subclones not sequenced in the current study—but these 20 appear to be split between two distinct clones . We observed similar evidence of mutually exclusive variant sets ( i . e . , evolutionary branch points ) among the outliers that could be re-clustered in UPN182896 and UPN288033 . Again , these potential subclones were small , consisting of only 4–5 SNVs , thus supporting the interpretation that the dominant evolutionary relationship among targeted variants was linear , though a minority of variants may have arisen secondarily to major clonal expansion events . Finally , we performed phylogenetic analysis to assess tumor clonality based solely on the genetic distance between individual cells ( independent of predicted cluster definitions ) . We used maximum likelihood to reconstruct the phylogenetic tree of each tumor using single-cell genotypes at targeted SNVs ( Figure 5 ) , which again supported our original model . The major clones ascertained from single-cell mutation profiles were separated by stable branches in each tree . These trees illustrate a generally linear topology , in addition to the branching event within cluster 5 in UPN461282 , but they also provide evidence for additional branching events within UPN182896 and UPN288033 . We integrated single-cell mutation profiles and trees to assign groups of individual cells to clones; we then compared the frequency of each clone among single cells to our prediction from sequencing unfractionated material , based on the mean VAF of each cluster , and we found a modest but significant correlation ( R2 = 0 . 60 ) ( Figure S8 ) .
Deep sequencing of unfractionated tumors is a powerful tool for interrogating inter- and intra-tumoral genetic variation [23] . Multiple studies have demonstrated that clonal heterogeneity is a key aspect of cancer biology [13] , [15] . These results have validated long-standing models of cancer as an evolutionary process [24] , which has clinical implications for the design of effective therapies ( selecting targeted agents and predicting response ) . Indeed , recent work has demonstrated functional heterogeneity among AML subclones [10] as well as prognostic value in detecting subclonal variation in MDS and chronic lymphoid leukemia [25] , [26] . Thus , even though the clonal architecture of individual tumors is often strongly implied from sequencing unfractionated samples , a direct assessment of these models and their underlying assumptions is critical . Here , single-cell analysis of MDS-derived secondary AML samples generally validated predictions from prior analysis of unfractionated samples . The vast majority of SNVs predicted to co-occur in a clonal population were shown to be present in at least one cell , clusters of variants corresponding to subclones were called reference en bloc ( supporting the predicted evolutionary progression ) , and the frequency of each clone was correlated ( albeit , modestly ) with the mean VAF of clusters in unfractionated samples . Nevertheless , the single-cell data suggested specific modifications to the original models . A limited set of variants ( n = 3 ) appear to have been misclustered in the original analysis , 35–50% of outliers could be assigned to clones for the first time , and the ambiguous clonal assignment of clone 5 in UPN461282 was resolved . In addition , approximately 9% of targeted positions ( covered in at least one cell ) were never called as variants , suggesting that some targeted SNVs were false positives in the original study , or belonged to subclones that were not sampled in this study by chance . Although most of the variants we targeted were found to colocalize in at least one cell ( supporting generally linear evolution ) , we did observe clusters of variants in each subject that were mutually exclusive ( suggesting subclonal branch points ) . These clusters were typically small ( with five or so variants differentiating a putative subclone ) , but were supported by multiple cells . The strongest evidence for this occurred in a low-frequency subclone in subject UPN461282 ( cluster 5 variants ) . As a class , it is plausible that low-frequency variants may be enriched for complexity , i . e . , may tend to be divided among multiple clones , and/or derive from different ancestral populations . Thus , we find that genotyping unfractionated and single-cell libraries are complementary approaches to resolving subclonal complexity . Analysis of unfractionated samples at multiple time points identifies major branches that may not be appreciated at a single time point ( e . g . , clone 1>clone 2>clone 3 in UPN461282 ) , whereas single-cell genotyping improves the interpretation of low-frequency variants ( removing false positive calls and revealing cryptic clonal substructure ) . Consistent with our results , recent work by Klco et al . has shown that single-cell genotyping supports the tumor clonality predicted from unfractionated de novo AML samples [10] . Klco et al . used WGA and amplicon sequencing to assay a smaller number of clonal markers ( n = 1–3 SNVs per clone , 10 total ) across a larger number of single cells ( n = 95 ) . This illustrated the utility of a large sample size for accurately estimating clone frequencies from single cells—Klco et al . achieved more precise single-cell estimates of variant frequencies that more closely matched estimates from bulk tumors . Alternatively , our analysis of several hundred clonal markers suggested that the secondary AML tumors we analyzed harbored complexity that was not appreciated by bulk analysis , and assaying a small number of variants per clone would not have shown this . Together , the Klco et al . study and our own suggest that the clonal architecture of complex tumors is best appreciated through the analysis of a large number of variants across a large number of cells . Previous reports of single-cell sequencing have already described the primary technical challenges we encountered in this study: 1 ) locus dropout and non-uniform coverage led to a substantial amount of missing data ( positions inadequately covered ) , and 2 ) ADO compromised the accuracy of variant calling at heterozygous sites [10]–[12] , [16] , [27] , [28] . Nevertheless , previous studies have generally attempted variant discovery from single-cell sequencing , whereas we sought to genotype a defined set of validated variants , i . e . , to understand the clonal relationships among SNVs that were supported by prior knowledge . Alternatively , others have reported analyses of tumor clonality using more accurate single-cell genotyping methods ( FISH , allele-specific PCR ) [7]–[9] , but these lack the throughput required to assay hundreds of variants simultaneously . Therefore , as improvements to WGA technologies are developed ( increasing coverage and reducing allelic bias ) [16] , in addition to more sensitive methods for rare variant detection [29] , [30] , a capture-based strategy offers an attractive balance of throughput and cost-effectiveness for studying tumor clonality . Accordingly , the approach we have outlined here—integrating both variant discovery in bulk samples , and clonality analysis in single-cells—could be used to confidently localize mutations within clonal hierarchies prior to the initiation of targeted therapies . This has the potential to inform treatment regimens that target complex populations of cells , not just isolated subclones , which may lead to improved patient outcomes .
All subjects were diagnosed with de novo myelodysplastic syndrome ( MDS ) and progressed to secondary acute myeloid leukemia ( sAML ) within 32 months . UPN461282: 65 year-old male ( refractory anemia with excess blasts and complex karyotype ) ; UPN182896: 75 year-old male ( refractory anemia with trisomy 8 ) ; UPN288033: 31 year-old female ( refractory anemia with excess blasts and normal karyotype ) . Detailed clinical histories have been reported previously [14] . All subjects provided written informed consent authorizing whole genome sequencing on a protocol approved by the Washington University Office of Human Research Protection . Affymetrix 6 . 0 SNP genotyping and WGS of unfractionated normal , MDS , and secondary AML samples were performed as described previously [14] . Somatic mutations were validated by solid phase targeted capture and deep sequencing . Single vials of cryopreserved bone marrow cells from each subject at sAML diagnosis were thawed , washed in PBS , counted , and adjusted to 7 . 5 million cells/mL . Single bone marrow cells were deposited into 96 well plates by flow cytometric cell sorting . Additional microtiter plates with two-cells per well were generated to produce intentionally “cross-contaminated” samples . Bivariate plot isolation of single , viable cells was made by forward low angle light scatter and 90 degree light scatter against apex debris and noise , as well as scatter pulse width to isolate single cells from aggregates . This sort decision was applied to a MoFlo cell sorter ( Beckman Coulter Inc . , Brea , CA ) equipped with a Cyclone X-Y deposition instrument , configured to deposit densities of 0–4 cells per well . The coincident cell abort mask was set to be the most stringent , allowing sorted droplets to contain only one target cell with no particles within adjacent droplets . Cells were sorted directly into extraction buffer; genomic DNA extraction and amplification were carried out using a PicoPlex WGA kit according to the manufacturer's protocol ( Rubicon Genomics , Ann Arbor , MI ) . WGA DNA yield was determined by Qubit fluorometric quantitation ( Life Technologies , Carlsbad , CA ) , and WGA DNA quality was assessed by qPCR . Sequencing libraries were prepared from single-cell WGA DNA ( n = 12 per subject ) , two-cell WGA DNA ( two cells intentionally deposited in one well , n = 2 per subject ) , as well as unamplified genomic DNA from unsorted samples—bone marrow and peripheral blood cells ( at MDS and sAML diagnosis ) and matched normal tissue ( skin biopsy ) ( Table S1 ) . Barcoded paired-end Illumina libraries were prepared according to the manufacturer's recommendations ( Illumina Inc . , San Diego , CA ) , with the following exceptions: 1 ) 250–1000 ng of WGA DNA ( sorted samples ) and 1000–3000 ng of unamplified DNA ( unsorted samples ) were fragmented using the Covaris E220DNA Sonicator ( Covaris Inc . , Woburn , MA ) to a size range between 100–400 bp; 2 ) Illumina adapter-ligated library fragments were amplified in four 50 µL PCR reactions for eighteen cycles; 3 ) Solid Phase Reversible Immobilization ( SPRI ) bead cleanup was used for enzymatic purification throughout the library process , as well as final library size selection targeting 300–500 bp fragments . All 56 sequencing libraries were pooled ( normalized to 85 ng per library ) and hybridized in solution to a custom library of capture oligonucleotides targeting 492 , 297 bases , according to the manufacturer's protocol ( Roche NimbleGen , Madison , WI ) . Capture baits targeted a total of 1 , 953 validated somatic single nucleotide variants ( SNVs ) : 872 SNVs from UPN461282 , 777 SNVs from UPN182896 , and 304 SNVs from UPN288033 , as reported previously [14] ( Table S2 ) . qPCR was used to calibrate flow cell loading concentration and cluster density . Libraries were run on a single lane of an Illumina HiSeq2000 , according the manufacturer's recommendations ( Illumina Inc . , San Diego , CA ) . Illumina reads were de-multiplexed and aligned to the NCBI 37/hg19 reference sequence ( GRCh37-lite ) using BowTie2 in local mode to allow soft-clipping of WGA adapter sequences [31] . Binary alignment/map ( BAM ) files were merged and duplicates marked using Picard v1 . 46 ( http://picard . sourceforge . net ) . Coverage metrics were calculated with GATK v1 . 2 DepthOfCoverage , with reads filtered for a minimum alignment score of 10 ( -mmq10 ) and a minimum base quality of 13 ( -mbq13 ) [19] , [20] . Read pileups were generated for individual samples with the SAMtools v0 . 1 . 18 mpileup command using default settings with the following exceptions: 1 ) base alignment quality ( BAQ ) computation disabled ( -B ) ; 2 ) minimum alignment score of 10 ( -q 10 ) ; and 3 ) minimum base quality score of 13 ( -Q 13 ) ; 4 ) maximum read depth of 99999 ( -d 99999 ) [17] . Variants were called from individual sample pileup files with either SAMtools or VarScan v2 . 3 . 5 using default parameters [17] , [18] , or using the GATK Unified Genotyper applied jointly across all single-cell libraries [19] , [20] . The identity of each sample was confirmed by variant calls at known germline homozygous SNPs ( Table S4 ) , as well as individual-specific somatic SNVs ( Table S5 ) . Phylogenetic analysis was performed in R ( v3 . 0 . 1 ) using the packages ape [32] and phangorn [33] . Briefly , genetic distances were estimated among all single cells for each subject under a generalized Kimura model [34] , and initial trees were derived using a modified neighbor joining algorithm . Likelihood optimization was then used to obtain the maximum likelihood ( ML ) tree for each subject using a generalized time reversible ( GTR ) substitution model . Finally , we performed a non-parametric bootstrap on each ML tree to estimate the support for individual branches ( n = 1000 iterations ) . For each single- and two-cell sample , the number of variant reads at heterozygous loci was modeled as a binomial process with a probability , p , derived from: 1 ) the variant allele fraction , f , in the original population ( putatively 1 or 2 cells ) , and 2 ) the cumulative error rate , e , attributable to WGA , library preparation , and sequencing . I . e . , for each locus , P ( X = k ) ∼Bin ( n , p ) , where k is the number of variant reads , n is the total read depth , and p is given by p = f ( 1−e ) + ( 1−f ) e . For each mutation cluster , the cumulative likelihood of the observed variant allele counts was calculated using specific VAFs for every possible combination of two clones . A likelihood ratio test using a one-sided chi-square distribution with 1 degree of freedom was then applied to calculate the overall probability that the observed variant allele fraction distribution was generated from a clonally pure ( single-cell ) or clonally heterogeneous ( two-cell ) sample . For each subject , the cumulative error rate was estimated for each cluster by calculating the mean VAF at these sites among single-cell samples from the other two subjects ( samples expected to be reference at these positions ) . I . e . , since all samples were processed in parallel and run on the same sequencing lane , subjects served as mutual controls for modeling the site-specific error rates intrinsic to WGA , library prep , and sequencing . | Human cancers are genetically diverse populations of cells that evolve over the course of their natural history or in response to the selective pressure of therapy . In theory , it is possible to infer how this variation is structured into related populations of cells based on the frequency of individual mutations in bulk samples , but the accuracy of these models has not been evaluated across a large number of variants in individual cells . Here , we report a strategy for analyzing hundreds of variants within a single cell , and we apply this method to assess models of tumor clonality derived from bulk samples in three cases of leukemia . The data largely support the predicted population structure , though they suggest specific refinements . This type of approach not only illustrates the biological complexity of human cancer , but it also has the potential to inform patient management . That is , precise knowledge of which variants are present in which populations of cells may allow physicians to more effectively target combinations of mutations and predict how patients will respond to therapy . | [
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] | 2014 | Clonal Architecture of Secondary Acute Myeloid Leukemia Defined by Single-Cell Sequencing |
Sleep disordered breathing ( SDB ) -related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities . Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality . We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90% . The discovery sample consisted of 8 , 326 individuals . Variants with p < 1 × 10−6 were analyzed in a replication group of 14 , 410 individuals . We identified 3 significantly associated regions , including 2 regions in multi-ethnic analyses ( 2q12 , 10q22 ) . SNPs in the 2q12 region associated with minimum SpO2 ( rs78136548 p = 2 . 70 × 10−10 ) . SNPs at 10q22 were associated with all three traits including average SpO2 ( rs72805692 p = 4 . 58 × 10−8 ) . SNPs in both regions were associated in over 20 , 000 individuals and are supported by prior associations or functional evidence . Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses , including a region overlapping Reelin , a known marker of respiratory complex neurons . These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep , a phenotype of high clinical interest . Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways , such as the biologically-plausible NLRP3 inflammasome , may contribute to nocturnal hypoxemia .
Arterial oxyhemoglobin saturation is a fundamental physiological trait that is tightly regulated at cellular and systemic levels to optimize tissue oxygen delivery . Reduced values , or hypoxemia , occurs secondary to acute and chronic respiratory or cardiovascular diseases , and rarely due to hemoglobin protein mutations . Chronically , low oxygen saturation predicts cognitive deficits in patients with chronic obstructive pulmonary disease ( COPD ) and in sleep apnea ( SA ) [1 , 2] . Oxyhemoglobin saturation ( SpO2 ) , the proportion of oxygen-saturated to total hemoglobin in the blood , is most commonly measured using non-invasive equipment ( oximeters ) . Oximetry is used to screen and monitor a wide range of health conditions . Normal SpO2 values range from 95% to 100% during wakefulness and normally fall by 2 to 4% during sleep . Oxygen saturation is reduced in individuals living at high altitude and in patients with cardiopulmonary diseases . However , even within specific disease groups , there is variation in SpO2 that is not explained by factors such as age , obesity , lung function or tobacco exposure [3] . Twin studies indicate that as much as 26% of the variation in waking SpO2 can be explained by genetic factors [4] . Population studies also indicate that genetic effects contribute to variation in waking SpO2 among Tibetan highlanders and in COPD [3 , 5] . Sleep disordered breathing ( SDB ) is a common disorder characterized by recurrent falls of SpO2 during sleep due to repetitive episodes of apneas ( no airflow ) or partial airflow ( hypopneas ) , most often due to recurrent collapse of the upper airway . Our prior family-based studies have indicated that average SpO2 during sleep is significantly heritable [6] . Sleep-related hypoxemia is a key component of the pathophysiology of the disorder and variations in SpO2 during sleep in patients with SDB are predictive of incident atrial fibrillation [7] , certain types of cancer [8–10] , and death [7] . Minimum nocturnal SpO2 predicted future carotid plaque burden in the Wisconsin sleep cohort , even after adjusting for traditional risk factors [11] . In cohorts of patients with both heart failure and SDB , overnight hypoxemia is a stronger risk factor for incident cardiovascular events and death than is the apnea hypopnea index ( AHI , a count of the number of breathing pauses per sleep hour ) [12–14] . Mean oxygen saturation and acute hypoxemia during sleep have more significant associations with liver steatosis than the AHI [15] . Sleep-related hypoxemia also may significantly influence prognosis of patients with COPD , asthma , and interstitial lung disease [16–19] . Adverse effects of sleep-related hypoxemia include those directly related to tissue ischemia as well as to the effects related to activation of hypoxia-inducible factor-1 ( HIF1A ) mediated and NF-kB pathways , that then activate the sympathetic nervous system , stimulate release of angiogenic and inflammatory factors , cause oxidative stress , reduce insulin sensitivity , and cause endothelial dysfunction . Therefore , understanding variation in nocturnal SpO2 is important for improving our understanding of variation in risk of a wide range of chronic health outcomes . In this study , we conducted the first multi-ethnic genome-wide association study ( GWAS ) of 3 nocturnal oxygen hemoglobin saturation ( SpO2 ) traits: average and minimum SpO2 , and the percent of sleep time under 90% SpO2 ( Per90 ) . ( Lower values of Per90 are better while higher values are better for the other two measures . ) These measures provide complementary information on hypoxemic burden across the sleep episode and can be derived from oximetry , which is potentially scalable for large-scale studies . We analyzed data from 10 cohort studies and four ethnic groups and focused on identifying obesity-independent loci by adjusting for body mass index ( BMI ) . We also considered sex differences in associations given the growing interest in sexual dimorphism in genetic analyses [20] . Furthermore , SDB prevalence varies by sex [21 , 22] ) , as do SDB risk factors such as the ventilatory response to arousal and regional fat distributions [23 , 24] , and sex differences have also been reported for the relationship between chronic hypoxemia and cardiovascular events [12] . These analyses extend our prior report of results for SDB in Hispanic/Latino-Americans [25] .
Descriptive characteristics of the discovery and replication study samples are provided in Tables 1 and 2 . Collectively , we studied 22 , 736 individuals . The discovery sample consisted of 8 , 326 individuals across 6 studies and 4 populations ( 1 , 209 African-Americans [AA]; 228 Asian-Americans [AsA]; 5 , 649 European-Americans [EA]; 1 , 240 Hispanic/Latino-Americans [HA] ) . Replication cohorts included 14 , 410 individuals ( 681 AAs , 2 , 378 EAs and European-Australians , and 11 , 351 HA ) from 4 cohorts . Across cohorts , mean age ranged from 37 . 8 ( CFS African-Americans ) to 77 . 7 years ( CHS European-Americans ) . Female participation ranged from 0% ( MrOS ) to 72% ( Starr ) . The mean BMI ranged from 24 . 1 kg/m2 ( MESA Asian-Americans ) to 32 . 3 ( JHS ) . Waking SpO2 values , which were typically measured prior to the sleep episode on the same equipment , ranged from 94 . 96% ( in the older MrOS cohort ) to 97 . 78% ( among relatively young CFS African-Americans ) . Average SpO2 during sleep ranged from 93 . 74% ( CFS European-Americans ) to 96 . 45% ( HCHS/SOL ) . The median Apnea Hypopnea Index ranged from 1 . 97 ( HCHS/SOL , a relatively young cohort ) to 24 . 60 ( WASHS , a sleep clinic-derived cohort ) . Average forced vital capacity ( FVC; percent predicted value ) exceeded 90% in cohorts in which these data were available . The prevalence of chronic lung diseases ( asthma , COPD ) and diabetes varied across cohorts , likely reflecting differences in age , ascertainment and possible disease definitions . Pairwise correlations among phenotypes and selective demographic variables are shown in S1 Table . As expected , the three overnight oxyhemoglobin saturation traits are strongly correlated ( average SpO2 –minimal SpO2 ρ = 0 . 61; average SpO2 –Per90 ρ = -0 . 73; minimal SpO2 –Per90 ρ = -0 . 86 ) . Waking oxyhemoglobin saturation correlates with average nocturnal SpO2 ( ρ = 0 . 59 ) , minimal nocturnal SpO2 ( ρ = 0 . 35 ) and Per90 ( ρ = -0 . 40 ) . The AHI was also correlated with minimal SpO2 ( ρ = -0 . 71 ) , Per90 ( ρ = 0 . 70 ) , and average SpO2 ( ρ = -0 . 55 ) . Lung function ( percent predicted FEV1 and FVC [26] ) correlated modestly with each of the overnight oxygen saturation measures ( ρ = -0 . 20 –+0 . 23 ) . Manhattan and QQ plots for the overall sample and population-specific primary discovery analyses are provided in S1–S3 Figs . The maximum lambda value was 1 . 02 , in the multi-ethnic average SpO2 analysis , suggesting that our analysis results were largely free of technical artifacts and corrected appropriately for population structure within each ethnic group . We analyzed SNPs in loci with discovery p-values < 1 × 10−6 in our replication cohorts and identified 6 significant ( p < 5 . 0 × 10−8 ) and 1 suggestive ( p < 1 . 0 × 10−6 ) associations in joint discovery and replication analyses spanning 5 regions; 2q12 ( IL18R1; Fig 1 ) , 10q22 ( HK1; Fig 2 ) , 3p24 ( intergenic region; S8 Fig ) , 4q35 ( RP11-242J7 . 1 , S9 Fig ) ; S2 Table ) , with several associations specific to given population backgrounds . Effect estimates and directions of allelic effect were consistent in the discovery and replication stages for all SNPs ( METAL heterogeneity p > 0 . 1 ) . In the multi-ethnic combined discovery and replication meta-analysis ( n>20 , 000 ) , genome-wide significant associations were identified with: a ) minimum SpO2 in the IL18R1 region ( rs78136548 discovery , p = 2 . 66 × 10−7 , combined p = 2 . 70 × 10−10 ) ; and b ) average SpO2 in the HK1 region ( rs72805692 discovery p = 7 . 20 × 10−8 , combined p = 4 . 58 × 10−8 ) ( Figs 1 and 2 , Table 3 ) . Lead population- and sex-specific SNPs from each locus meeting our replication criteria definitions are also presented ( S2 Table ) . Consistent negative effect directionality was observed for the IL18R1 region SNP rs78136548 T across all 13 available association tests in African , European , and Hispanic/Latino ancestral populations ( S3 Table ) . The association was largely driven by males ( females beta ( se ) -0 . 065 ( 0 . 023 ) , p = 0 . 005 , males beta ( se ) -0 . 131 ( 0 . 022 ) , p = 2 . 69 × 10−9; S4 Table ) . Average SpO2 was significantly associated with the HK1 region in a European-American analysis ( rs16926246 n = 5 , 649; p = 2 . 46 × 10−8; 1000G EUR rs72805692 r2 = 0 . 625 ) . The HK1 region was also notable for a second European-American significant association using the complementary phenotype Per90 ( percentage of sleep with oxyhemoglobin saturation below 90%; rs148471505 p = 3 . 08 × 10−8; 1000G EUR rs72805692 r2 = 0 . 679; S2 Table ) . Minimum SpO2 was also suggestively associated with the HK1 region in European-American males ( rs17476364 p = 6 . 79 × 10−8; 1000G EUR rs72805692 r2 = 0 . 937; S3 Table ) . Given that sleep disordered breathing and respiratory control vary by sleep state [27 , 28] , we also explored whether associations for oxygen saturation differed when using measurements specific to non rapid eye movement ( NREM ) versus rapid eye movement ( REM ) sleep in cohorts with sleep state information ( S5 Table ) . Several SNPs showed associations with lower p-values and/or higher point estimates for stage-specific results . The minimum SpO2 within NREM rs72805692 association result showed the lowest p-value for any HK1 locus SNP across all analyses ( p = 1 . 60 × 10−9 ) and further indicated that the HK1 region SNPs were significantly associated with all three traits . The secondary sex-stratified discovery analyses ( Miami plots , S4–S6 Figs ) identified 6 additional independent loci associated in males with consistent effects in replication and suggestive p-values < 1 . 0 × 10−6 in joint analyses ( S3 Table; S11–S17 Figs ) . A combined secondary meta-analysis of the discovery and replication cohorts for SNPs with initial discovery phase p-values ≥ 1 . 0 × 10−6 identified four additional significantly associated loci ( 22q11 , 6q25 , 17p13 and 7q22 including new candidate genes CHRNE and RELN; S6 Table and S18–S22 Figs ) . Joint analysis results of the lead loci are provided for each SNP in S3 Table , while a comparison of individual SNP results using combined-sex and sex-stratified models can be found in S4 Table . Although overnight oxygen saturation values most strongly correlate with measurements of SDB , they also may be influenced by pulmonary function , waking oxygen saturation , and hemoglobin levels . We therefore tested associations of the lead loci for sleep SpO2 traits with waking SpO2 , the AHI ( the clinical metric for SDB ) , forced vital capacity ( FVC , percent predicted , a measure of pulmonary function ) , and hemoglobin concentration ( S5 Table ) . Sample sizes for the comparison traits varied based on the availability of these exploratory phenotypes , with hemoglobin and FVC collected at different exams from the sleep recordings in a subset of cohorts . Consistent with the strong correlation between sleep period SpO2 and AHI phenotypes ( S1 Table ) , several lead oxygen saturation SNPs also displayed modest to strong associations with the AHI ( 12 of 17 available p-values < 0 . 05; minimum AHI p = 5 . 3 × 10−5 ) . Weaker associations were observed with the other traits: waking SpO2 ( p generally > 0 . 01 and < 0 . 05; minimum p = 0 . 005 ) ; FVC ( p generally > 0 . 05; minimum p = 0 . 025 ) ; and hemoglobin concentration ( p generally > 0 . 05; minimum p = 0 . 003 ) . We next evaluated whether associations between sleep SpO2 values and lead SNPs persisted after adjusting for AHI , FVC percent predicted , waking SpO2 , asthma history , COPD history , current smoking status , and hemoglobin concentration ( S8 Table ) . Analyses restricted to individuals with these available covariates showed that neither FVC , asthma , COPD , current smoker status or hemoglobin concentration changed the estimated SNP effects for sleep SpO2 by more than 10% for any SNP , suggesting that lung function and lung disease did not mediate the associations between sleep oxygen saturation and each SNP . In contrast , adjustment for AHI reduced the SNP association effect estimates by more than 10% in most of the models tested . Adjustment for waking SpO2 , which correlated with nocturnal oxygen saturation , reduced the effect estimates by 0 . 2 to 35% ( S8 Table ) , although the statistical significance of direct associations of these SNPs with waking SpO2 was modest ( p = 0 . 003–0 . 93; S5 Table ) . We searched for SNPs in our top loci that overlap regulatory regions as determined by the ENCODE and Roadmap Epigenomics Consortia and collated by HaploReg . S9 Table lists the 144 of 227 unique SNPs with p-values < 1 × 10−6 that overlap regulatory regions ( promoter or enhancer marks; DNase I hypersensitivity sites; or protein binding regions ) in at least 1 cell line . Our lead HK1 region SNP in multi-ethnic meta-analysis , rs72805692 ( average SpO2 multi-ethnic p = 4 . 58 × 10−8 ) overlapped enhancer marks in 107 cell lines across 21 organs . Other notable genome-level significant SNPs in the HK1 locus include rs16926246 and rs148471505 ( overlapping enhancer marks in 91 and 71 cell lines , respectively ) . We further queried for Blueprint Consortium promoters and enhancers ( largely blood cell lines ) and Vermunt et al . brain region enhancers ( S10 Table ) . 104 of the 227 unique replication and combined meta-analysis SNPs with p-values < 1 × 10−6 overlapped at least one regulatory region . rs72805692 additionally overlapped 30 Blueprint and 98 Vermunt enhancer regions , and rs16926246 overlapped 106 combined enhancer regions . We also queried overlap with published expression quantitative trait loci ( eQTL ) associations . 182 of the 227 unique SNPs with p-values < 1 × 10−6 were eQTL SNPs for at least one of 42 genes ( S11 Table ) . 13 SNPs that were genome-level significant SNPs in the IL18R1 region were also eQTL SNPs for both interleukin 18 receptor subunits in whole blood ( IL18R1 eQTL p < 4 . 9 × 10−11; IL18RAP eQTL p < 1 . 6 × 10−46 ) , indicating a possible role for interleukin 18 signaling in the as yet unknown causal tissue ( s ) . No significant colocalization was observed when testing this region using Blueprint Consortium eQTL signals . The lead significant HK1 region SNP rs16926246 was also associated with HK1 expression in whole blood ( EA average SpO2 p = 2 . 46 × 10−8; HK1 eQTL p = 9 . 64 × 10−13 ) . We performed a multi-variate GWAS of the three SpO2 traits in the European-ancestry samples using MTAG [29] . Lead results ( p < 1 × 10−6 ) are shown in S12 Table . No novel genome-level significant loci were detected . We used our European-American GWAS meta-analysis results to impute gene-level expression differences in a subset of 6 GTEx-assayed tissues and Depression and Genes and Networks ( DGN ) whole blood using MetaXcan . Tissue-specific results are presented in S13–S19 Tables . Three genes were associated at either a Bonferroni-adjusted significance level ( p < 4 . 01 × 10−7 ) or at a suggestive level within an order of magnitude , all in the minimum SpO2 analysis: CHRNE ( minimum p = 7 . 61 × 10−8 in subcutaneous adipose tissue ) , C17orf107 ( overlapping and antisense to CHRNE; minimum p = 2 . 68 × 10−7 in visceral omentum adipose tissue ) , and IL18R1 ( minimum p = 6 . 28 × 10−7 in subcutaneous adipose tissue ) . We carried the whole blood MetaXcan results forward for pathway analyses ( DGN sample size = 922 ) . GIGSEA analyses of KEGG pathways and Molecular Signatures Database curated microRNAs and transcription factors are presented in S20–S22 Tables respectively . The most enriched KEGG pathway was steroid hormone biosynthesis ( Average SpO2 empirical p-value = “0” following 10 , 000 permutations ) . This pathway was observed twice with empirical p-values < 0 . 05 , as were the KEGG asthma and ribosome pathways . The most significantly observed miRNA binding site was for MIR-380-3P ( average SpO2 empirical p-value = 0 . 006 ) . MIR-140 and MIR-190 displayed empirical p-values < 0 . 05 in two analyses . PPARG transcription factor binding sites were enriched in all three analyses , while PPAR signaling was the most enriched Per90 KEGG pathway . NHLH1 ( formerly HEN1 ) transcription factor binding sites were enriched in all three analyses , and six transcription factor binding sites were enriched in two analyses .
We identified significant associations between HK1 SNPs and average oxygen saturation ( SpO2 ) during sleep and percentage of sleep with SpO2 < 90% ( Table 3 ) . State-specific results also indicate a genome-level association with minimum SpO2 during NREM sleep ( S5 Table ) . Hexokinase is the first enzyme and the rate-limiting step in the glycolysis pathway [30 , 31] and its activity is regulated by hypoxia inducible factor 1a ( HIF1A ) [5 , 32 , 33] . Obstructive sleep apnea following CPAP withdrawal increases glucose during sleep [34] . Rs16926246 ( significantly associated with average SpO2 ) and rs10159477 ( among our suggestive average SpO2 SNPs , S3 Table ) are associated with HK1 expression in whole blood ( [35] , S11 Table ) and also have been associated with hemoglobin concentration [36] . Rs16926246 was the study-wide lead SNP and previously found to be highly significantly associated with hemoglobin A1c ( HbA1c ) levels , a marker of glucose homeostasis , through an erythrocytic pathway [37] . Rs72805692 , our lead multi-ethnic average SpO2 SNP , has also been associated with HbA1c levels [38] . Both SNPs overlap enhancer marks in ≥ 197 ENCODE , Roadmap Epigenomics , Blueprint , and Vermunt et al . cell lines and/or brain regions ( including erythroblasts; S9 and S10 Tables ) . The Rapoport–Luebering glycolytic shunt affects erythrocytic oxygen capacity through allosteric binding of 2 , 3-bisphosphoglycerate ( 2 , 3-BPG , also known as 2 , 3-diphosphoglycerate or 2 , 3-DPG ) to hemoglobin . The concentration of glycolytic pathway intermediates can impact 2 , 3-BPG concentration , partially mediated by hexokinase [39–41] . Rs72805692 was marginally associated with hemoglobin concentration in our sample for individuals with available measurements ( p = 0 . 0034 ) . The A allele was associated with reduced hemoglobin concentration , average sleeping and waking SpO2 and increased sleep time with oxygen saturation under 90% . However , the association with average sleeping SpO2 was not appreciably changed when adjusting for hemoglobin concentration ( S5 Table ) . Alternatively , HK1 , in concert with cytokines including IL18 , may influence overnight oxygen saturation through effects on pulmonary inflammation and ventilation-perfusion mismatch . Hexokinase-1 mediated glycolysis regulates the NLR Family Pyrin Domain Containing 3 ( NLRP3 ) inflammasome [42] , a multiprotein complex implicated in obesity-related inflammation [43] as well as several pulmonary diseases [44–50] . The NLRP3 inflammasome activates caspase-1 , resulting in cleavage of pro-IL1B and pro-IL18 into their mature forms , amplifying inflammation [50 , 51] . The NLRP3 inflammasome is proposed to play a critical role in lung injury occurring in response to exposures to inflammatory mediators , oxidative stress and mechanical ventilation , including cyclic pulmonary stretching , which induces NLRP3 inflammasome activation in alveolar macrophages [52] . Patients with SDB , particularly obstructive sleep apnea , experience oxidative stress and pulmonary inflammation [53] , as well as swings in intrathoracic pressure , potentially causing pulmonary strain . Our data suggest the possibility that variations in HK1 ( and possibly IL18 ) pathways may contribute to individual differences in pulmonary gas exchange occurring during sleep , possibly through pulmonary inflammation and/or subclinical pulmonary injury . Circulating markers of alveolar epithelial injury , including KL-6 , surfactant protein-A , and matrix metalloproteinase-7 , correlate with degree of overnight hypoxemia and AHI in patients with SDB [54 , 55] . Chronic intermittent hypoxia induces physiological deficits in rats with allergen-induced airway inflammation , due to collagen deposition and other effects [56] . Although the mechanisms underlying these associations are unclear , lung imaging studies show an increase in subclinical interstitial lung abnormalities in individuals with sleep apnea [55] . Our data suggest the possibility that variations in HK1 pathways may contribute to differences in pulmonary gas exchange that occurs during sleep , possibly through effects on ventilation-perfusion mismatch due to subclinical pulmonary inflammation . Recent population-based studies found that sleep apnea associates with both elevated pulmonary inflammatory markers and imaging evidence of interstitial lung abnormalities [55] . Finally , the NLRP3 inflammasome has been shown to influence brain tissue , and changes in sleep delta power have been observed in knock-out mice [57] . Another and correlated mechanism could be through HIF1A . In addition to oxygen sensing effects in the carotid body [58] , HIF1A regulates HK1 in human alveolar cells [59] , is regulated by PFKM ( a downstream glycolysis enzyme ) in macrophages [60] , and is involved with metabolic reprogramming of macrophages [61] . Activation of glycolytic enzymes in pulmonary epithelial cells exposed to cyclic mechanical stretching is abrogated with HIF1A repression [62] . Ventilatory differences in responses to intermittent hypoxemia secondary to SDB could influence several measures of overnight SpO2 , as observed in our analyses . The second set of significant SNPs implicated in overnight SpO2 levels were in the IL18R1 region , with external evidence indicating eQTL associations with both IL18 receptor subunit genes ( IL18R , IL18RAP ) in over a dozen genome-level significant SNPs ( S8 Table ) . Minor alleles were associated with an increase in minimum oxygen saturation , an increase in IL18RAP expression , and a decrease in IL18R1 expression in whole blood [35] . IL18R1 expression was also suggestively associated with minimum oxygen saturation in a gene-level analysis using MetaXcan . These genes are essential for IL18 signaling [63 , 64] , suggesting that the IL18 pathway may partially mediate the association at this locus . IL18 is a pro-inflammatory cytokine produced by macrophages and is involved in multiple inflammatory disorders [65] . This region has been associated with Blautia genus microbiota abundance in the gut ( lead locus SNP rs79387448 Min SpO2 p = 8 . 61 x 10–8 [S3 Table] ) [66] . Il18 over-expression in mice leads to chronic pulmonary inflammation , including the increased levels of CD4+ , CD8+ CD19+ , eosinophils , macrophages , NK1 . 1+ , and neutrophils; along with alveolar destruction , fibrosis , and other effects [67 , 68] . In humans , IL18 plasma concentration levels are elevated in acute respiratory distress syndrome [69] . As described above , IL18 as well as IL1B are the inflammatory proteins activated by caspase 1 in HK1-regulated NLRP3 inflammasome activation [42] . MTOR , a member of the complex that induces this HK1-mediated activation , is the 6th most associated gene in our analyses of Per90 using MetaXcan whole blood analysis ( p = 4 . 5 × 10−4 , S18 Table ) . Mechanical stretching-induced NLRP3 inflammasome activation induces activated IL18 release from alveolar macrophages [52] . Casp1- ( required for Il18 activation ) and Nlrp3-knockout mice are protected from hypoxemia accompanying mechanical ventilation [70] . Models of cyclic stretching induce the release of Il18 in mouse alveolar macrophages , mediated by Nlrp3 [52] . Serum IL18 concentrations are also significantly higher in patients with SDB compared to obese controls and correlated with serum concentrations of C reactive protein and interleukin 6 [71] . Il18r1 is among the genes with the most robust circadian rhythmic profiles in healthy mouse lung [72]; it is possible that timing-specific gene expression may influence the nocturnal hypoxemia phenotype we studied . An association between asthma and a SNP in the IL18R1 region is reported [73] . Our lead SNPs had reduced linkage disequilibrium with this SNP ( rs3771166 minimum p in any model = 5 . 6 x 10−5 for minimum SpO2 in EA males ) . Analyses adjusted for asthma did not significantly attenuate our associations ( rs78136548 minimum SpO2 p adjusted for asthma = 1 . 21 x 10−7 , unadjusted p = 1 . 01 x 10−7 in equivalent samples ) . Therefore , different variants in the IL18R1 region may influence pulmonary and sleep related hypoxemia traits . The circadian timing of sleep may impact IL18 pathway-specific effects on pulmonary-related traits . The associations with HK1 further also implicate the possibility that variants in both genes may contribute to SpO2 levels . IL18 has also been shown to regulate HIF1A [74] . The protein coding gene most proximal to the Per90 association with the 4q35 region in African-Americans ( S2 Table , S9 Fig ) was CASP3 , a second caspase gene involved with alveolar wall destruction [75] . Despite the modest sample size , the p-value almost met genome-wide significance ( p = 9 . 39 x 10−7 ) , suggesting the utility of future studies of the role of this gene in influencing nocturnal saturation . We also detected multiple genome-level significant associations following a combined discovery plus replication cohort meta-analysis ( S7 Table ) . Although these associations require independent evidence for replication , two of these associations are of particular interest . In European-Americans , minimum oxygen saturation was associated with 2 genome-level significant and 65 suggestive SNPs that are associated with CHRNE ( acetylcholine receptor , nicotinic epsilon [muscle] ) expression in 19 GTEx tissues and monocytes ( p < 5 x 10−8; S11 Table ) . CHRNE and the proximal gene C17orf107 had the lowest p-values in the expression-based MetaXcan gene tests . Phospholipidase D2 ( PLD2 ) , another gene associated with the locus through expression ( eQTL ) SNPs , is required for hypoxia-induced expression of HIF1A . Hypoxia-induced gene expression in mouse lung endothelial cells is reduced in Pld2 knockout mice [76] . A multi-ethnic Per90 association physically overlaps RELN ( reelin ) . While no expression or epigenetic evidence was available , this association is of interest given the suggested respiratory role of reelin within the Pre-Bötzinger complex , a major center for respiratory control [77] . No novel genome-level significant loci were detected in our multi-variate MTAG analyses ( S12 Table ) . As expected from the univariate results , HK1 was significantly associated and the lead SNP rs72805692 had reduced p-values for average and minimum SpO2 ( p = 4 . 0 × 10−9 and 1 . 1 × 10−9 respectively ) . Among the genes in novel suggestive regions was WLS ( formerly GPR177; rs17481104 minimum SpO2 p = 5 . 8 × 10−7 ) , which is involved in pulmonary vascular development and has been suggestively associated with airflow obstruction in COPD [78 , 79] . Enrichment of the KEGG asthma pathway for both minimum SpO2 and Per90 ( S20 Table ) lends support to the ‘overlap syndrome’ of these two pulmonary diseases [80] . PPAR-gamma transcription factor binding site enrichment in all three analyses ( S22 Table ) suggests the potential importance of future mechanistic studies of this inflammation-related transcription factor . PPAR signaling was the most enriched KEGG pathway in the Per90 analysis ( S20 Table ) . PPAR signaling and PPARG expression in visceral adipose tissue have previously been associated with obstructive sleep apnea [81] . Sex-stratified analyses identified stronger associations among males compared to females for the IL18R1 signal ( rs78136548 p females = 0 . 005 , males = 2 . 69 × 10−9; S4 Table ) and for several SNPs within the HK1 locus ( e . g . rs17476364 EA min SpO2 p females = 0 . 19 , males = 6 . 79 × 10−8 ) . In addition , sex-stratified analyses identified two other loci of interest ( S6 Table ) . Among EA males only , a suggestive association with Per90 in the IL1RAPL1 region of the X chromosome was identified . The region has recently been suggestively associated with asthma in Hispanic/Latino children , with one replication cohort indicating potential male-specific effects [82] . An association in the PPP4R1 region ( protein phosphatase 4 regulatory subunit 1 ) was nearly genome-level significant in EA males ( p = 5 . 4 × 10−8 ) . Ten suggestive SNPs in this locus were also PPP4R1 eQTL SNPs in whole blood ( p < 1 × 10−40; S11 Table ) . PPP4R1 regulates HDAC3 ( histone deacetylase 3 ) , an epigenetic modulator of circadian lipid metabolism [83 , 84] . Respiratory control and neuromuscular activation vary between NREM and REM sleep . Analyses restricting to these states may reduce heterogeneity due to differences in state that influence airway patency or respiratory chemosensitivity . The PPP4R1 locus p-value lowered to genome-level significance when analyzed using NREM sleep data ( rs78805840 p = 1 . 81 × 10−8; S5 Table ) . The lowest overall p-value in the HK1 locus was a minimum SpO2 within NREM association with rs27805692 ( all population combined-sex p = 1 . 60 × 10−9 ) . The three traits that we analyzed ( average and minimum SpO2 during sleep , percent of sleep with SpO2 < 90% ) each are commonly measured and reported in evaluation of patients with sleep apnea . Although correlated , they each measure somewhat different aspects of oxygen saturation . Notably , associations for the Hexokinase 1 ( HK1 ) region showed associations with several measures of oxygen saturation . Consistency of these findings across phenotypes suggests the importance of the HK1 pathway in influencing several aspects of oxygenation during sleep , including severity of response to an airway occlusion ( i . e . , as measured by minimal saturation ) , overall severity ( Per90 ) , and overall level ( average ) . Although overnight hypoxemia can occur with underlying pulmonary disease , our analyses also showed that each SpO2 association typically associated with the AHI , a primary index of sleep apnea , and associations were not appreciably influenced after considering effects of lung disease , tobacco use , lung function , and hemoglobin level ( S8 Table ) . As expected , baseline oxygen saturation also correlated with average SpO2 , consistent with an influence of waking SpO2 on overall nocturnal levels . Notably , none of our sleep-related trait associations overlapped published associations for resting oxygen saturation in COPD . Across our cohorts , average level of lung function was within the normal range , and prevalence of lung diseases was low . These findings , as well as our analyses that adjusted for several factors and independently assessed genetic signals for the other pulmonary traits , indicate that the variations in SpO2 traits in our cohorts predominantly reflected differences in SDB-related levels of hypoxemia . Relevance of our results to SDB is supported by finding that 12 of the 17 available lead loci SNPs across all analyses had at least a nominal association with the AHI ( S5 Table ) , including the associations for HK1 rs72805692 and IL18R1 region rs78136568 SNPs ( p = 8 . 1 × 10−5 and 7 . 2 × 10−5 respectively ) . SDB is a common disorder affecting 17% of middle-aged men and 9% of middle-aged women and characterized by repetitive episodes of upper airway obstruction resulting in intermittent hypoxemia , sleep disruption , and profound physiological disturbances [85] . Past genetic analyses of sleep apnea have mainly focused on the AHI , which does not fully describe the broad range of physiologic stressors that occur in SA , including patterns of SpO2 desaturations [86] . Overnight SpO2 analysis provides clinically relevant information [2 , 7–9 , 12–14] and can be measured relatively simply , and thus can be scaled for future genetic studies and precision medicine . Our study has several strengths . The sample size of over 22 , 000 is among the largest available GWAS analyses of any trait associated with objectively recorded sleep disordered breathing . The associations were observed in cohorts with varying demographics and ascertainment strategies ( Tables 1 and 2 ) , and as such are likely generalizable to diverse populations . We used a stringent imputation quality threshold ( 0 . 88 ) to reduce random error , using a 1000 Genomes Project or denser template in all studies . Several of our associations are supported by published gene expression , bioinformatics evidence , and/or physiological studies . Several weaknesses also need to be acknowledged . While we have not performed functional assays as part of the present analysis , the most biologically compelling candidates are supported by several lines of evidence from the literature and will require future experimental validation . Data on potential mediators ( e . g . , lung function , hemoglobin ) were collected in different visits or were available only in a subset of our cohorts . Some promising findings did not meet genome-wide significance criteria or could not be replicated across cohorts . While this first multi-ethnic meta-analysis of the three traits included over 22 , 000 individuals , weak or population-specific associations were likely to be missed due to power limitations . In conclusion , we have performed the first genome-wide association analysis of clinically relevant sleep disordered breathing traits , specifically measures of nocturnal oxygen saturation , and identified several novel associations that are of potential biological relevance . Of particular interest were variants in the HK1 and IL18R1 regions . Understanding the genetic underpinnings of these sleep-related traits may guide future studies investigating the contribution of sleep disordered breathing to the hypoxemic burden of pulmonary disorders , and identify common mechanisms such as activation of the NLRP3-inflammasome pathway . Full meta-analysis results are freely available from http://www . sleepdisordergenetics . org/informational/data .
The Atherosclerosis Risk in Communities Study ( ARIC; n = 1 , 432 ) and Framingham Heart Study ( FHS; n = 640 ) cohorts participating in the Sleep Heart Health Study ( SHHS ) were analyzed with available polysomnography ( PSG ) and genotype data [87–89] . This community-based study included a baseline examination ( 1995–1998 ) that included in-home polysomnography , and questionnaires [89] . Polysomnography from the baseline examination was collected using the Compumedics PS-2 system ( Abbotsford , AU ) [90] . Oxyhemoglobin saturation was measured with finger pulse oximetry over the sleep episode and cleaned of signal artifact . The 3 parent cohorts are described below , with CHS used as a replication cohort in the current study ( genetic data from this cohort was obtained after the other two studies ) . In ARIC , genotyping was performed using the Affymetrix 6 . 0 array . In FHS , genotyping was performed using the Affymetrix 500k and Illumina Omni 5M arrays ( obtained from dbGaP; pht000395 . v7 . p8 ) . The Cleveland Family Study ( CFS ) is examining the genetic and familial basis of sleep apnea with 2 , 534 African- and European-American individuals from 356 families . Four visits occurred from 1990–2006 , with a final visit at a clinical research center ( 2000–2006 ) . Index probands with confirmed sleep apnea were recruited from sleep centers in northern Ohio . Additional family members and neighborhood control families were also studied [91] . Measurements including sleep apnea monitoring , anthropometry , other related phenotypes , and questionnaires . Before 2000 , an Edentrace Type 3 home sleep apnea device was used ( Eden Prairie , MN ) . The final examination used 14-channel polysomnography ( Compumedics E series , Abottsford , AU ) . Genotyping was based on the Affymetrix 6 . 0 and Illumina OmniExpress , Exome , and IBC chip arrays . Data were based on 1 , 411 individuals with both genotypes and sleep data from either the home sleep study ( n = 784 ) or the lab-based study ( n = 627 ) . The Multi-Ethnic Study of Atherosclerosis ( MESA ) is examining the risk factors of clinical cardiovascular disease [92] . The baseline examination in 2000 included 6 , 814 participants ages 45 to 84 from 6 communities: Baltimore MD , Chicago IL , Los Angeles CA , New York NY , Minneapolis/St . Paul MN , and Winston-Salem NC . Four ethnicities are being studied: African- , Asian- , European- , and Hispanic/Latino-Americans . An ancillary sleep study of 2 , 060 individuals who did not use nightly CPAP , overnight oxygen , or an oral device for sleep apnea occurred between 2010–2013 . Sleep measurements included in-home PSG , actigraphy , and a questionnaire adapted from the SHHS questionnaire [93] . Unattended polysomnography used a 15-channel monitor ( Compumedics Somte System , Abbotsford , AU ) . Final study inclusion for individuals with an Affymetrix 6 . 0 assay was 1 , 883 . The Osteoporotic Fractures in Men Study ( MrOS ) is a prospective cohort study examining the risk factors for fractures , osteoporosis , and prostate cancer [94 , 95] in males age 65 or older from six U . S . communities . An ancillary sleep study of 3 , 135 individuals was conducted between 2003 and 2005 , including in-home PSG ( Compumedics Safiro system; Abbotsford AU ) , anthropometry , and questionnaires . Genotyping was performed with the Illumina Human Omni 1 Quad v1-0 H array . A total of 2 , 178 European ancestry individuals had PSG and genotype data . The Starr County Health Studies ( Starr ) have been examining the risk factors of diabetes in a predominantly Mexican-American border county in Texas since 1981 [96 , 97] . The sleep apnea assessment occurred between 2010 and 2014 and included a questionnaire and home sleep apnea testing using the WatchPAT-200 device ( Itamar-Medical Ltd . , Caesarea , Israel ) , with recording of finger pulse oximetry , actigraphy , body position , peripheral arterial tonometry , and snoring . It has previously been validated using polysomnography [98] . The current analysis included 782 individuals with valid oximetry and Affymetrix 6 . 0 data . Data from the Sleep Heart Health Study Cardiovascular Health Study ( CHS ) [99] was available after ARIC and FHS and used in replication analysis . Sleep phenotyping was performed as described earlier . 185 African-American and 731 European-Americans with available polysomnography and Illumina CNV370 , and/or Omni1M plus IBC genotypes obtained through dbGaP ( pht003699 . v1 . p1 ) were analyzed . The Hispanic Community Health Study/Study of Latinos ( HCHS/SOL ) is studying risk and protective factors of multiple health conditions in Hispanics/Latinos [100 , 101] . 16 , 415 community members from randomly selected households aged 18–74 from 4 cities ( Chicago , IL; Miami , FL; Bronx , NY; San Diego , CA ) were examined in a baseline exam between 2008–2011 . The sample design consisted of a stratified two-stage area probability sample of household addresses . Six cohort backgrounds were represented: Central American ( n = 1 , 730 ) , Cuban ( n = 2 , 348 ) , Dominican ( n = 1 , 460 ) , Mexican ( n = 6 , 471 ) , Puerto-Rican ( n = 2 , 728 ) , and South American ( n = 1 , 068 ) . The exam included anthropometry , questionnaires , and home sleep apnea testing using the ARES Unicorder 5 . 2 ( B-Alert , Carlsbad , CA ) , which records measurements of airflow using a nasal pressure cannula and pressure transducer; oxyhemoglobin saturation and pulse rate using a forehead-based reflectance oximeter; head movements and position using an accelerometer; and snoring levels using a microphone . The device has undergone previous validation for in-home use [102] . Records were manually scored and cleaned of artifacts at a central sleep reading center [101] . The current study includes 11 , 351 non-Asian ancestry individuals with oxyhemoglobin saturation values during sleep and Illumina Omni 2 . 5 genotyping . The Jackson Heart Study ( JHS ) is a population-based prospective investigation of cardiovascular disease [103 , 104] . The ancillary sleep study occurred from 2012–2016 , and included home sleep apnea testing with the Embla Embletta Gold , a 6-channel device that includes an oximeter ( Broomfield , CO ) . The device has been validated previously [105] . Additional collected measures include sleep questionnaires and anthropometry . 496 African-American individuals with phenotyping and Affymetrix 6 . 0 genotyping were included in this study , reflecting a dataset freeze at the time of analysis . The Western Australian Sleep Health Study ( WASHS ) is examining the epidemiology and genetics of sleep apnea and related comorbidities [106] . This clinic-based study examines patients presenting to the sole public sleep clinic in Western Australia , located in Perth . 91% of patients were referred for SDB . Data collection for individuals in the current analysis occurred from 2006–2010 . In-lab , attended polysomnography was performed using the Compumedics Series E device ( Abbotsford , AU ) . After excluding principal component ( PC ) outliers ( see below ) , valid oximetry data and genotype data ( Illumina Omni 2 . 5 ) were available for 1 , 647 European ancestry patients . The quantitative phenotypic outcome was oxyhemoglobin saturation during sleep ( SpO2 ) , measured as an average , minimum , or as a percentage of the night with SpO2 < 90% ( Per90 ) measured using finger pulse oximetry ( all using NONIN oximetry boards ) or transcutaneous oximetry ( HCHS/SOL only ) measured continuously as part of polysomnography or home sleep apnea testing . Other than the WASHS clinical cohort , all sleep data were scored by a central reading center with high levels of established reliability [107] by scorers blinded to all other data . Intermittent waking and SpO2 artifact were manually edited from all records . Covariates were obtained by questionnaires , direct measurement ( BMI ) , and oximetry ( waking oxygen saturation was measured prior to the sleep recording ) . Secondary measures such as hemoglobin concentration and spirometry were collected from the same visit whenever possible , however this was not possible for all cohorts ( most notably hemoglobin was collected years prior to the sleep exam in some cohorts ) . Potential device differences were minimized by both performing analyses at a cohort level and using a rank-normal phenotype transformation to reduce the impact of phenotypic outliers . Our analysis focused on identifying potential loci operating in obesity-independent pathways . Hispanic/Latino-specific results have been reported previously for average SpO2 [25] . Genotypes from all cohorts were imputed to at least a 1000 Genomes Phase 1 density . ARIC , JHS , and HCHS/SOL were imputed using a 1000 Genomes Phase 1 version 3 template . WASHS was imputed using a Haplotype Reference Consortium version 1 . 0 template [108] . All other cohorts were imputed using a 1000 Genomes Phase 3 version 5 template [109 , 110] . Single nucleotide polymorphisms ( SNPs ) and insertions/deletions with minor allele frequency < 0 . 01 , minor allele counts < 20 within a cohort , or an IMPUTE2/PBWT info score < 0 . 88 were removed from the analysis . Sample sizes and variant counts for each cohort for the three primary phenotype analyses are provided in S23 Table . We explored ancestry-specific associations given past SDB trait differences ( e . g . [93 , 101] ) and linkage disequilibrium differences [109] . Data were analyzed at a cohort- and population-specific level ( e . g . 4 separate analyses for the MESA cohort ) . Population structure was controlled for using linear mixed models followed by genomic control . Population structure principal components were calculated for the minimally-admixed , self-reported Asian-American and European-American/Australian population groups within individual studies using TRACE [111] . WASHS initial self-reported European ancestry was based on classification of the patient's parents [106] . Individuals were defined as population outliers and removed from analysis if any coordinate from PC 1–4 was greater than 5 standard deviations from the population mean . Individuals self-reporting into groups with modest sample size within a cohort ( e . g . MrOS Asian-Americans ) were excluded from study . Our analysis focused on identifying potential loci operating in obesity-independent pathways . We adjusted for age , age2 , sex , age × sex , BMI , and BMI2 to address known demographic factors and potential non-linear effects of age and BMI . Phenotypes , adjusted for age and sex , were rank-normalized . Residuals were then calculated by further adjusting for BMI . Primary analyses were performed using GEMMA , which incorporates linear mixed models that control for the relatedness structure [112] . HCHS/SOL analyses were performed using the GENESIS Bioconductor package [113] ( DOI:10 . 18129/B9 . bioc . GENESIS ) . A fixed effects , inverse variance weighted meta-analysis was performed using METAL with genomic control applied in each analysis [114] . Variants with p-values < 1 × 10−6 in the discovery cohort meta-analysis were carried forward to replication and combined discovery/replication analysis . To reduce the influence of small studies possibly leading to spurious findings , we only present meta-analysis results where 1 , 000 or more individuals contributed . Individual SNPs in the multi-ethnic analyses were only analyzed if they remained unfiltered in two or more populations . The three traits differed in their final variant counts due to phenotype missingness and ascertainment ( no average SpO2 was available for WASHS in this analysis ) . In aggregate for the discovery cohorts , there were 11 , 297 , 250–11 , 298 , 080 AA; 8 , 956 , 016–8 , 958 , 150 EA; and 9 , 481 , 040–9 , 481 , 751 multi-ethnic variants . The replication cohorts included 12 , 243 , 361–12 , 346 , 361 AA; 7 , 448 , 148–8 , 707 , 439 EA; and 10 , 173 , 881–10 , 480 , 925 multi-ethnic variants . Visualizations were constructed using LocusExplorer and EasyStrata [115 , 116] . Sleep and sleep disordered breathing may be regulated by multiple tissues [86 , 117] . Epigenetic database queries were performed using HaploReg version 4 using an imputed model and exact SNPs . HaploReg data included ENCODE and Roadmap Epigenomics consortia data [118–120] . Additional queries examined non-cancerous Blueprint Consortium data ( largely related to blood cell lines ) and Vermunt et al . brain region enhancer data[121–123] . Gene expression data used in expression quantitative trait loci ( eQTL ) lookups were obtained from multiple studies , including a seven-cohort consortium investigating whole blood ( Westra et al . ) [35 , 124–130] . The Westra data were pruned to include only eQTL SNPs with FDR < 0 . 05 . Moloc was used to test colocalization [131] . Gene-level analyses used MetaXcan to impute expression levels based on GTEx tissues and Depression and Genes and Networks ( DGN ) whole blood [132] . GIGSEA , which is designed to work with MetaXcan output , was used for pathway analyses using the whole blood results ( queried due to improved power from increased sample size ) [133] . We used the weighted linear regression model with 10 , 000 permutations . | Variation in oxyhemoglobin saturation , the proportion of oxygen-saturated to total hemoglobin in the blood , is associated with numerous disorders and is a predictor of health outcomes including mortality , incident heart failure , and dementia . Despite the fundamental role of oxygen saturation in normal and abnormal physiology , there are few large-scale genetic studies of oxygen saturation performed across populations . Overnight measurements provide more variability than daytime levels due to the “stresses” associated with normal and disordered breathing , and also provide an important measure of sleep apnea severity , a common disorder in the population that is associated with considerable morbidity . In this study , for the first time , we identified multiple replicated genome-significant associations based on up to 22 , 736 individuals from 10 cohort studies . Our findings suggest a contribution of inflammatory genes such as the Interleukin 18 receptor subunit genes to the genetic architecture of sleep-disordered breathing . These results extend our understanding of the genetics of oxyhemoglobin saturation and sleep-disordered breathing and may provide further insight into the biology of associated diseases . | [
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] | [] | 2019 | Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep |
Although a standard reinforcement learning model can capture many aspects of reward-seeking behaviors , it may not be practical for modeling human natural behaviors because of the richness of dynamic environments and limitations in cognitive resources . We propose a modular reinforcement learning model that addresses these factors . Based on this model , a modular inverse reinforcement learning algorithm is developed to estimate both the rewards and discount factors from human behavioral data , which allows predictions of human navigation behaviors in virtual reality with high accuracy across different subjects and with different tasks . Complex human navigation trajectories in novel environments can be reproduced by an artificial agent that is based on the modular model . This model provides a strategy for estimating the subjective value of actions and how they influence sensory-motor decisions in natural behavior .
The primary focus of reinforcement learning has been on forward models that , given reward signals , can learn to produce policies , which specify action choices when immersed in an environment state . A state refers to information about the environment that is needed for decision making . An important breakthrough of RL in behavior modeling is inverse reinforcement learning ( IRL ) , which aims to estimate the underlying subjective reward of decision makers given behavioral data [18] . IRL is an appealing tool for modeling human behavior: A behavioral model can be quantitatively evaluated by comparing human behaviors with reproduced behaviors by an artificial agent trained using the RL model with the estimated reward function . An important factor that makes standard RL difficult in modeling natural behaviors is its sophistication and resulting computational burden as a model for general reward-seeking behaviors . The natural environment has at least two features that could make RL/IRL algorithms computationally intractable . First , a large number of task-relevant objects may be present , hence the decision state space is likely to be high-dimensional . Standard RL suffers from the curse of dimensionality with high-dimensional state space , where the computational burden grows exponentially with the number of state variables [5 , 19] . Second , the natural environment is ever-changing such that humans must make decisions under different situations although these situations might have similar components . Living in a natural environment requires a decision maker to be able to transfer knowledge learned from previous experience to a new situation . In contrast an RL agent is often trained and tested repeatedly in a fixed environment . The optimal behavior is obtained through either a model-based dynamic programming approach that requires full knowledge of the environment , or a model-free learning approach that requires a large amount of experience . Both approaches generally put a heavy burden on memory storage or computation in order to calculate the optimal behavior . Consequently both of them may not be suitable for the real-time decision-making strategy in natural conditions since decision makers encounter new environment all the time and need to make decisions with reasonable cognitive load . For these reasons , standard RL must be extended to make computation tractable . An extension of standard RL named modular reinforcement learning utilizes divide-and-conquer as an approximation strategy [19–21] . The modular RL takes the statistical structure present in the environment , decomposes a task into modules where each module solves a subgoal of the original task . Generally an arbitrator is required to synthesize module policies and make final decisions . Modularization alleviates the problem of curse of dimensionality since each module only concerns a subset of state variables . Introducing a new state variable may not affect the entire state space and cause its size to grow exponentially . Additionally , the decomposition naturally allows the decision maker to learn a behavior specifically for a module and reuse it later in a new environment . Under the modular RL framework , a more sample-efficient IRL algorithm is possible [19] , which matters for modeling natural human behaviors since such behavioral data is often expensive to collect . Recent studies have explored the plausibility of a modular architecture for natural visually guided behavior where complex tasks can be broken down into concurrent execution of modules , or microbehaviors [4 , 9 , 22 , 23] . Thus in the example of walking across the street , each particular behavioral subgoal such as avoiding obstacles can be treated as an independent module . This leads to a view of the human brain as the centralized arbitrator that divides and coordinates these modules in a hierarchical manner . The current investigation explores the modular architecture in more detail . A frequently overlooked variable in RL is the discount factor that determines how much a decision-maker weighs future reward compared to immediate reward . In the agent-environment interaction paradigm , a standard RL model typically treats the discount factor as a part of the environment and as fixed . The alternative approach is to view the discount factor as a subjective decision-making variable that is part of the agent and may vary . Behavioral neuroscience studies suggest that the magnitude of the discount factor is correlated with serotonin level in human subjects [24] . As a consequence decision-makers may exhibit between-subject variations [25] . At the same time , between-task variation may also exist , i . e . , the same decision maker may use different discount factors for various tasks . An fMRI study by [16] suggests that different cortico-basal ganglia loops are responsible for reward prediction at different time scales , allowing multiple discount factors to be implemented . Hence it is necessary to extend the standard RL model to adapt discount factors to different human subjects and tasks . A modular approach is ideal for this modeling effort . Allowing different modules to have their own discount factors makes the model flexible in modeling potential variations in human data . Spatial navigation has been used as a canonical benchmark task for standard RL/IRL algorithms in machine learning , and therefore is selected as the experimental domain for testing our model . The task is an ideal testbed for modular RL since it is convenient for introducing multiple ( sub- ) tasks . In following sections of this paper , computer simulations are conducted first to validate the correctness of the proposed algorithm and to compare with existing methods . We then use human behavioral data previously collected in an immersive virtual environment [4] to show that the proposed sparse modular IRL algorithm allows prediction of human walking trajectories by estimating the subjective reward values and discount factors of different modules . By demonstrating the ability to model naturalistic human sensory-motor behavior we lay the ground work for future analysis of similar behaviors .
Virtual reality ( VR ) and motion tracking were employed to create a naturalistic environment with a rich stimulus array , while maintaining experimental control . Fig 1 shows the basic setup . The subject wore a binocular head-mounted display ( the nVisor SX111 by NVIS ) that showed a virtual room ( 8 . 5 × 7 . 3 meters ) . The subject’s eye , head , and body motion were tracked while walking through the virtual room . Subjects were recruited from a subject pool of undergraduates at the University of Texas at Austin , and were naive to the nature of the experiment . The human subject research is approved by the University of Texas at Austin Institutional Review Board with approval number 2006-06-0085 [4] . Although we do not know the set of normal subtasks involved in walking through a room like this , three plausible candidates might be following a path across the room , avoiding obstacles , and perhaps heading towards target objects . To capture some of this natural behavior we asked subjects to collect the targets ( blue spheres ) by intercepting them , follow the path ( the gray line ) , and/or avoid the obstacles ( red cubes ) . Objects disappeared after collision . This type of state transition function encourages subjects to navigate through the virtual room instead of sticking at a single target . The global task has at least three modules: following the path , collecting targets , and avoiding obstacles . We gave subjects four types of instructions that attempt to manipulate their reward functions ( and potentially the discount factors ) , resulting in four experimental task conditions: There were no monetary rewards in the task . Since following paths , avoiding obstacles , and heading towards targets are frequent natural behaviors , we assume that subjects have some learned , and perhaps context-specific subjective values associated with the three task components , and our goal was to modulate these intrinsic values using the instructions . The instructions were to walk normally , but to give some priority to the particular task components in the different conditions . To encourage such prioritization , Subjects received auditory feedback when colliding with obstacles or targets . When objects were task-relevant , this feedback was positive ( a fanfare ) or negative ( a buzzer ) , while collisions to task-irrelevant objects resulted in a neutral sound ( a soft bubble pop ) [4] . The color of the targets and obstacles was counterbalanced in another version of the experiment and was found not to affect task performance or the distribution of eye fixations so the control was not repeated in the present experiment [26] . The order of the task was Task 1 , 2 , 3 , and 4 . This order was chosen so as not to influence the single task conditions by doing the double task . Thus it is possible there are some order effects . In another experiment in the environment the order of the conditions was counterbalanced and no obvious order effects were observed [26] . We analyze data collected from 25 human subjects . A single experimental trial consisted of a subject traversing the room , with the trial ending when the goal at the end of the path is reached . Objects’ positions and the path’s shape differed on every trial . Each subject performed four trials for each task condition . While reinforcement learning aims at finding the optimal policy given a reward function , inverse reinforcement learning ( IRL ) attempts to infer the unknown reward function given the agent behavioral data in the form of state-action pairs ( st , at ) [18 , 34–36] . Our work is largely based on the modular IRL algorithm by [19] which pioneered the first modular IRL algorithm . Given the modular RL formulation in the previous section , the goal of modular IRL is to estimate the underlying reward and discount factor for each module to recover the value function , given a sequence of observed state-action pairs , i . e . , a trajectory that traverses through the state space , as shown in Fig 3A . We follow the Bayesian formulation of IRL [36 , 37] , Maximum Likelihood IRL [38] , and improve the modular IRL algorithm in [19] . These approaches assume that the higher the Q-value for an action at in state st , the more likely action at is observed in behavioral data . Let η denote the confidence level in optimality ( the extent to which an agent selects actions greedily , default to be 1 ) , and let exp ( ⋅ ) denote the exponential function . The likelihood of observing a certain state-action pair is modeled by the softmax function with Gibbs ( Boltzmann ) distribution , as illustrated in Fig 3B: P ( a t | s t , Q , η ) = exp ( η Q ( s t , a t ) ) ∑ a ∈ A exp ( η Q ( s t , a ) ) ( 5 ) Let T denote the total length of the trajectory . The overall likelihood L for observed data D = { ( s1 , a1 ) , ⋯ , ( sT , aT ) } is the product of the likelihood of individual state-action pairs , given the states are Markovian and action decisions are independent: L = P ( D | Q , η ) = ∏ t = 1 T exp ( η Q ( s t , a t ) ) ∑ a ∈ Aexp ( η Q ( s t , a ) ) ( 6 ) Next , the global action-value function Q ( st , at ) is decomposed using Eq ( 3 ) with module Q functions Q ( 1:N ) , therefore the likelihood becomes: L = P ( D | Q ( 1 : N ) , η ) = ∏ t = 1 T ∏ n = 1 N ∏ m = 1 M t ( n ) exp ( η Q ( n ) ( s t ( n , m ) , a t ) ) ∑ a ∈ A ∏ n = 1 N ∏ m = 1 M t ( n ) exp ( η Q ( n ) ( s t ( n , m ) , a ) ) ( 7 ) Take the log of the likelihood function: logL = ∑ t = 1 T ( ∑ n = 1 N ∑ m = 1 M t ( n ) η Q ( n ) ( s t ( n , m ) , a t ) - log ∑ a ∈ A ∏ n = 1 N ∏ m = 1 M t ( n ) exp ( η Q ( n ) ( s t ( n , m ) , a ) ) ) ( 8 ) Substituting Eq ( 4 ) into Eq ( 8 ) : logL = ∑ t = 1 T ( ∑ n = 1 N ∑ m = 1 M t ( n ) η r ( n ) ( γ ( n ) ) d ( s t ( n , m ) , a t ) - log ∑ a ∈ A ∏ n = 1 N ∏ m = 1 M t ( n ) exp ( η r ( n ) ( γ ( n ) ) d ( s t ( n , m ) , a ) ) ) ( 9 ) The variables to be estimated from the data are module rewards r ( 1: N ) and discount factors γ ( 1: N ) . The number of modules N , the number of objects for each module Mt ( 1 ) , … , Mt ( N ) , and distances d ( s t ( n , m ) , a t ) for each object are all state information and can be observed from the environment . This formulation follows closely the work by [19] , extending it to use the new formulation of modular RL , handle multiple objects of each module , estimate the discount factors , and derive a slightly different objective function .
The most intuitive way to evaluate the modular RL model is to see whether the model can accurately reproduce human navigation trajectories . The Q-value function of a modular RL agent is calculated using r and γ estimated from human data . Next , the modular RL agent is placed at the same starting position as the human subject and starts to navigate the environment until it reaches the end of the path . The agent chooses an action probabilistically based on the Q-value of the current state , using a softmax action selection function as in Eq ( 5 ) . The reason to let the agent choose actions with a certain degree of randomness is that the Q-values for multiple actions can be very close , e . g . , turning left or turning right to avoid an obstacle , consequently a human subject may choose either . Therefore , a single greedy trajectory may not overlap with the actual human trajectory . The softmax action selection function generates a distribution of hypothetical trajectories , i . e . , a trajectory cloud , by running an agent many times in the same environment . The actual human trajectory can be visualized in the context of this distribution . Fig 4 shows generated trajectory clouds together with actual human trajectories , along with estimated rewards and discount factors . The agent trajectories are shown in semi-transparent green hence darker area represents trajectories with higher likelihood , and the human trajectory on that trial is shown in black . Each row of figures presents experimental trials from one experimental condition ( Task 1-4 ) , and three trials within each row are from different subjects but the same environment , i . e . , the same arrangement of objects . The figures demonstrate that the model’s generated trajectory clouds align well with observed human trajectories . When a local trajectory distribution is multi-modal , e . g . , in Fig 4D , 4F , 4J , 4K , and 4L , the human trajectories align with one of the means . The next important observation is the between-subject variation . Trials within each row are from the same environment under the same task instruction . However , human trajectories can sometimes exhibit drastically different choices , e . g . , Fig 4E versus 4F and 4J versus 4K . These differences are modeled by the underlying r and γ , and accurately reproduced by the distributions generated . This means that we can compactly model naturalistic , diverse human navigation behaviors using only a reward and a discount factor per module . The modeling power of modular RL is demonstrated by the observation that varying these two variables can produce a rich class of human-like navigation trajectories . We then look at the way average reward estimates vary between different tasks when aggregating data from all subjects . The results are shown in Fig 5A . Overall , the estimated r values vary in an appropriate manner with task instructions . Thus obstacles are valued higher when the instructions prioritize this task , and targets are valued higher when that task is prioritized . Note that the obstacle avoidance module is given some weight even when it is not explicitly prioritized—this is consistent with the observation that subjects deviates from the path to avoid obstacles even when obstacles are task-irrelevant . This may reflect a bias which is carried over from natural behavior with real obstacles . The relatively high value for the path may indicate that subjects see staying near the path as the primary goal . The between-subject differences in reward are shown in S2 Appendix for all 25 subjects . At each individual subject’s level , changing in the relative reward between the modules is also consistent with task instructions . An one-way ANOVA test suggests that individual differences are evident across subjects under the same task instruction ( see S2 Appendix for details ) . Fig 5B shows average discount factor estimates for different tasks . Although the reward evidently reflects and agrees with task instructions , the interpretation of the discount factor is more complicated . The discount factors vary across tasks for target and obstacle modules but are close to 1 . 0 and stable for the path module . This may also reflect the primacy of the task of getting across the room , and the need to plan ahead . Although the instructions do not directly manipulate discount factors , we will later show that estimating discount factors from data instead of holding them fixed is important for modeling accuracy . An important observation from Fig 5 is that task-relevant module rewards and discount factors are stable across task conditions . To show this quantitatively , for each subject , we combine module rewards from Task 2 ( path + obstacle ) and Task 3 ( path + target ) to synthesize the rewards for Task 4 ( path + obstacle + target ) in the following way: r t a s k 4 _ t a r g e t = r t a s k 3 _ t a r g e t ( 11 ) r t a s k 4 _ o b s t a c l e = r t a s k 2 _ o b s t a c l e ( 12 ) r t a s k 4 _ p a t h = ( r t a s k 2 _ p a t h + r t a s k 3 _ p a t h ) / 2 ( 13 ) Then the discount factors are synthesized in the similar way . The synthesized rewards ( re-normalized ) and discount factors from Task 2 and 3 are found to be very close to those estimated from Task 4 , as shown in Table 1 . However , task-irrelevant rewards and discount factors are not stable . This result indicates that task-relevant module rewards and discount factors generalize to a different task condition . Thus modules are independent and transferable in this particular scenario . Next we compare our model with several alternative hypotheses . The full modular IRL model chooses the action greedily that maximizes the Q-value function of each state using both estimated r and γ . An ablation study is conducted to demonstrate the relative importance of the variables in the model . The binary reward agent estimates γ only , and uses a unit reward of 1 for the module that is task-relevant , e . g . , in Task 2 the path and the obstacle modules would have rewards of +1 and -1 respectively , and the target module would have a reward of 0 . The fixed γ agents estimate r only , and use fixed γ = 0 . 1 , 0 . 5 , 0 . 99 . A Bayesian IRL agent without modularization and assumes a fixed discount factor [36] is also implemented where the implementation details can be found in S3 Appendix . We choose two performance metrics to evaluate these models . The first one is the number of objects intercepted by the agent’s entire trajectory under different task conditions . Fig 6 shows the performance of different models ( ( A ) targets and ( B ) obstacles ) . Overall , the modular IRL model has the closest performance to the human data across task conditions . Note that the number of targets collected is only a little affected by the avoid instruction and obstacles avoided do not change very much with the target instruction , supporting the previous claim that the modules in this experiment are independent hence task-relevant module values are stable . Bayesian IRL and fixed γ = 0 . 99 models perform poorly—the number of objects hit does not vary accordingly with task instructions . The binary reward model , γ = 0 . 1 , 0 . 5 reflect task instructions correctly but are less accurate than the full modular IRL model . The second quantitative evaluation metric would be the angular difference , i . e . , policy agreement , which is obtained by placing an agent in the same state as a human and measuring the angular difference between the agent’s action and the human subject’s action . This metric differs from the previous one because it emphasizes more on the accuracy of local decisions instead of the whole trajectory . Thus this angular difference is a local metric instead of a holistic one . The comparison results are shown in Table 2 . All modular RL agents are more accurate in predicting human actions comparing to the traditional Bayesian IRL algorithm . Again the full modular IRL model results in higher accuracy comparing to the alternative models . The binary reward model has comparable performance and is in general better than the models that have the discount factor fixed . This supports our claim that module-specific discount factor plays an important role in modeling human behaviors and should be estimated from data . To summarize , we are able to predict human novel trajectories in different environments on the basis of rewards and discount factors estimated from behavioral data . Since we do not know the actual set of visual operations involved in walking through a cluttered room like this , the fact that we can reproduce the trajectories suggests that the three chosen modules can account for a substantial fraction of the behavior while vision may be used for other tasks . In fact , close to half the fixations made by the subject are on regions of the environment other than the path or objects [4] . This suggests that there may be other visual computations going on but that they do not have much influence on the behavior . Thus the modular RL agents generate reasonable hypotheses about underlying human decision-making mechanism . These results provides a strong support for using modular RL as the model for explaining such multitask navigation behaviors , and modular IRL as a sample efficient algorithm to estimate rewards and discount factors . Bayesian IRL has to deal with a complex high-dimensional state space and settle for its approximations for a dynamic multi-task problem with limited data , while modular RL can easily reduce the dimensionality of the state-space by factoring out sub-tasks . Therefore the algorithm significantly outperforms the previous standard IRL method in terms of the accuracy in reproducing human behaviors . The proposed modular IRL algorithm is an extension and refinement of [19] which introduced the first modular IRL and demonstrated its effectiveness using an simulated avatar . The navigation tasks are similar but we use data from actual human subjects . While they use a simulated human avatar and moving from the straight path , our curved path proves quite different in practice , as well , being significantly more challenging for both humans and virtual agents . We then generalize the state space to let the agent consider multiple objects for each module , while the original work assumes the agent considers one nearest object of each module . Bayesian IRL was first introduced by [36] as a principled way of approaching an ill-posed reward learning problem . Existing works using Bayesian IRL usually experiment in discretized gridworlds with no more than 1000 states with an exception being the work of [39] which was able to test on a goal-oriented MDP with 20 , 518 states using hierarchical Bayesian IRL . The modular RL architecture proposed in this work is most similar to a recent work in [40] , in which they decompose the reward function in the same way as the modular reinforcement learning . Their focus is not on modeling human behavior , but rather on using deep reinforcement learning to learn a separate value function for each subtask and combining them to obtain a good policy . Other examples of divide-and-conquer approach in RL include factored MDP [41] and co-articulation [42] . Hierarchical RL [43 , 44] utilizes the idea of temporal abstraction to allow more efficient computation of the policy . [45] analyzes human decision data in spatial navigation tasks and the Tower of Hanoi; they suggest that human subjects learn to decompose tasks and construct action hierarchy in an optimal way . In contrast with that approach , modular RL assumes parallel decomposition of the task . The difference can be visualized in Fig 7 . These two approaches are complementary , and are both important for understanding and reproducing natural behaviors . For example , a hierarchical RL agent could have multiple concurrent options [43 , 44] executing at a given time for different behavioral objectives . Another possibility is to extend the modular RL to a two-level hierarchical system . Learned module policies are stored and a higher-level scheduler or arbitrator decides which modules to activate or deactivate given the current context and the protocol to synthesize module policies . An example of this type of architecture can be found in [2] .
Although modular RL/IRL is able to produce trajectories that are similar to human behavior , the match was imperfect as demonstrated by the angular difference . One difficulty with modeling human behavior is that we defined the state space and a set of modules by hand without knowing the actual state representation or task decomposition that the human uses . This may account for the discrepancy between the human and agent policies . Ideally , we could learn state representation from data , but this involves the challenging task of combining representation learning and IRL . The work in [54] provides a potential method for inferencing goals and states for the modules . Recent development in deep reinforcement learning [55] may possibly lead to a data-driven approach to IRL that can learn state representation from data . An important assumption about the centralized arbitrator of the modules needs to be examined more carefully in the future: In our model , an agent forms global Q-values by summing up module Q-values [21 , 29] . There has been work examining more sophisticated mechanisms for global decision making [56 , 57] . For example , one could schedule modules according to an attention mechanism [56 , 58] . Whether these mechanisms can better explain human behaviors remains an open question that should be explored . An important consequence of being able to get a quantitatively estimated subjective reward and discount factor of a module is that it is possible to test whether these values are stable across contexts . For example , the value of avoiding an obstacle should be stable across moderate variations in the environment such as the changes in obstacle density or changes in the visual appearance of the environment . If this is true , then it is possible to make predictions about behavior in other contexts using learned modules . And it would also be possible to use the prediction error to indicate that other factors need to be considered . Estimates of the value of the underlying behaviors will also allow prediction of the gaze patterns subjects make in the environment . It has been suggested that gaze patterns reflect both the subjective value of a target and uncertainty about task-relevant state [2 , 4 , 59 , 60] . For example , gaze should be frequently deployed to look at pedestrians in a crowded environment since it is important to avoid collisions and there is high uncertainty about their location . Also gaze is deployed very differently depending on the terrain and the need to locate stable footholds , reflecting the increased uncertainty of rocky terrain [61] . Estimates of the subjective value might thus allow inferences about uncertainty as well . In conclusion , we have demonstrated that modular reinforcement learning can plausibly account for sequences of sensory-motor decisions in a natural context , and it is possible to estimate the internal reward value of behavioral components such as path following , target collection , and obstacle avoidance . The estimated reward values and discount factors enabled us to predict long walking trajectories in a novel environment . This framework provides a potentially useful tool for exploring the task structure of natural behavior , and investigating how momentary decisions are modulated by internal rewards and discount factors . | It is generally agreed that human actions can be formalized within the framework of statistical decision theory , which specifies a cost function for actions choices , and that the intrinsic value of actions is controlled by the brain’s dopaminergic reward machinery . Given behavioral data , the underlying subjective reward value for an action can be estimated through a machine learning technique called inverse reinforcement learning . Hence it is an attractive method for studying human reward-seeking behaviors . Standard reinforcement learning methods were developed for artificial intelligence agents , and incur too much computation to be a viable model for real-time human decision making . We propose an approach called modular reinforcement learning that decomposes a complex task into independent decision modules . This model includes a frequently overlooked variable called the discount factor , which controls the degree of impulsiveness in seeking future reward . We develop an algorithm called modular inverse reinforcement learning that estimates both the reward and the discount factor . We show that modular reinforcement learning may be a useful model for natural navigation behaviors . The estimated rewards and discount factors explain human walking direction decisions in a virtual-reality environment , and can be used to train an artificial agent that can accurately reproduce human navigation trajectories . | [
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] | 2018 | Modeling sensory-motor decisions in natural behavior |
The high rate of leprosy cases among children under 15 years of age in Brazil indicates ongoing transmission within the community . The identification of the new leprosy cases among contacts can help identify the source of infection and interrupt the transmission chain . This study aims to determine the detection rate of previously undiagnosed cases of leprosy among schoolchildren who are under 15 years of age living in Manaus , Amazonas , Brazil , and their possible source of infection by contact tracing . This was a school-based , cross-sectional study in which the identification of active leprosy cases was conducted in 277 out of 622 randomly selected public schools in Manaus , Amazonas , Brazil . Suspected cases of leprosy were referred to the Alfredo da Matta Foundation , a reference center for leprosy in Manaus . A total of 34 , 547 schoolchildren were examined , and 40 new leprosy cases were diagnosed . Among new cases , 57 . 5% were males , and 80 . 0% demonstrated paucibacillary leprosy . A total of 196 of 206 registered contacts were screened , and 52 . 5% of the newly diagnosed children’s cases had at least one positive household contact . In these contacts , grandparents ( 52 . 4% ) were the most common co-prevalent cases , while 14 . 3% were uncles , 9 . 5% were parents and 9 . 5% were granduncles . Seven contacts ( 5 . 0% ) , including four siblings of child patients were newly diagnosed . Our data indicate that the prevalence is 11 . 58 per 10 , 000 , which is 17 times higher than the registered rate . This study suggests that the detection rate of leprosy among schoolchildren may have remained unchanged over the past thirty years . It also indicates that that active case finding is necessary for reaching the World Health Organization’s goals of zero detection among children , especially in endemic areas where the prevalence of leprosy is obscure . Moreover , we assert that all children must have their household contacts examined in order to identify the possible source of infection and interrupt the disease’s transmission . Novel strategies to reinforce contact tracing associated with large-scale strategies of chemo- and immune-prophylaxis should be expanded to prevent the perpetuation of the disease cycle .
Mycobacterium leprae , the causative agent of leprosy , is primarily transmitted person-to-person and through the air . People living in leprosy-endemic regions are at greater risk of being exposed to the infection . The risk of developing the disease among paucibacillary ( PB ) contacts is 2–3 times higher than that of the general population , while the risk increases to 5–10 times among multibacillary ( MB ) contacts[1–3] . Therefore , contact tracing not only results in the detection of additional cases but further offers several indirect advantages such as early diagnosis and reduced risk of transmission[4] . Familial leprosy distribution indicates a relationship between the clinical forms of the disease and kinship degree . Consanguineous relatives belonging to families whose fathers or mothers had lepromatous leprosy showed a higher risk of developing the same type of disease . On the other hand , non-consanguineous relatives were at a higher risk of contracting other clinical forms of the disease [5] . A study conducted in the Philippines showed that the risk of developing lepromatous leprosy was three times higher when one of the parents presented with this clinical form of the disease [6] . In leprosy hyperendemic areas , the risk of developing the disease may be elevated not only for household contacts but also for the residents in neighboring homes [7 , 8] . Recently , a survey conducted in a hyperendemic Brazilian region demonstrated no significant difference in detection rates between household contacts and neighbors [8] . According to the World Health Organization ( WHO ) , Brazil accounts for more than 80% of leprosy cases diagnosed in the Americas[9] . In 2016 , 25 , 218 new leprosy cases were diagnosed in Brazil , and 1 , 696 ( 6 . 7% ) of those individuals were children , which corresponds to a diagnosis rate of 3 . 63 per 10 , 000 people . In the same year , Amazonas State reported 443 new cases of leprosy; the diagnosis rate was 1 . 10/10 , 000 inhabitants , and this was considered highly endemic by the Brazilian Ministry of Health ( BMH ) [10] . Although the introduction of multidrug therapy ( MDT ) in the beginning of the 1980s drastically influenced the total number of cases , there has been stagnation and a slight decrease in incidence over the past 10 years . This data suggests that it is likely that MDT has little impact on incidence because transmission occurs prior to diagnosis . Thus , strategies to prevent leprosy transmission indicate that contact tracing and post-exposure prophylactic protocols using rifampicin and/or BCG[11–13] should be successful . In this regard , the diagnosis of leprosy cases among children under 15 years of age can help provide estimates of ongoing transmission [14 , 15] and the presence of active disease foci in the community[16] . In the early 1980s , an active case finding in Manaus indicated a detection rate of 10 . 6 cases of leprosy per 10 , 000 children [17] . This study was carried out to identify previously undiagnosed cases of leprosy among schoolchildren and their possible source of infection by contact tracing . Patterns of family contact with leprosy are demonstrated through genograms .
This was a school-based , cross-sectional study . Active case finding of leprosy in children under 15 years of age was conducted from March 2014 to December 2016 in 277 of the 626 public schools in Manaus , Amazonas , Brazil . Manaus is one of the major cities in the north of Brazil and has approximately 2 , 800 , 000 inhabitants [18] . The metropolitan area of Manaus has 626 public schools that enroll approximately 250 , 000 children [19] . Target schools were randomly chosen through a lottery method using Open Source Epidemiologic Statistics for Public Health software to obtain the study population . The probabilistic sample of 30 , 352 students was calculated based on the target population of students; the sampling error was 0 . 03% , and the confidence interval was 95% . Children from randomly selected public schools in Manaus , Amazonas , were eligible to participate in the study . The recruitment process started with an open seminar on leprosy and the purpose of the study . After written informed consent was obtained from parents or legal guardians , children received an initial physical examination conducted by trained and experienced leprosy and skin nursing technicians . The initial physical examination took place at school . Suspected cases of leprosy and other skin diseases , along with their legal guardians , were referred to the Alfredo da Matta Foundation ( AMF ) , a referral center for leprosy and other skin diseases in Manaus . Three dermatologists and laboratory tests confirmed the diagnosis of leprosy , which was initially based on the presence of leprosy’s cardinal signs , i . e . , if the patient had one or more lesions with a definite loss of sensation and/or peripheral nerve thickening . If these signs were evident , diagnosis was confirmed by histopathological changes and analysis of bacillary loads in a slit skin smear test ( SSS ) . Classification was performed according to Ridley and Jopling [20 , 21] . In cases in which there was no confirmation through the previously mentioned routine tests , a polymerase chain reaction ( PCR ) was performed to detect M . leprae DNA , as previously described [22] . This technique has been used in patients who have clinical signs of leprosy but no confirmation through routine tests and histopathology , in difficult-to-diagnose cases , and in early detection in household contacts [22] . For confirmed cases of leprosy , a standardized questionnaire was administered to gather past medical history and social and demographic information , such as BCG scar status , data on household and dwelling contacts , race—white , black , yellow , brown or indigenous - , etc . ) was applied . For treatment purposes , leprosy cases were classified as PB or MB , as recommended by the Brazilian Ministry of Health ( BMZ ) [14] and the WHO [23] . Household contacts were defined as a group of people who lives or have lived with a leprosy patient within the past five years . Direct and next-door neighbors , when indicated by legal guardians , were also considered contacts . All contacts were initially examined by the nursing technicians for clinical evidence of leprosy; the diagnosis of leprosy was also confirmed by three dermatologists and the aforementioned laboratory tests . Data were analyzed using Epi Info 7 software . Initial descriptive studies were performed through frequency tables , position measurements and variability . Pearson's chi-square test or Fisher's exact tests were used to analyze the categorical variables . The significance level was 0 . 05 , and the confidence interval was 95% . The GenoPro version 3 . 0 . 0 . 7 software was used to create genograms in order to identify the probable source of infection of new leprosy cases . Ethical approval was granted by the AMF Research and Ethics Committee . Written informed consent was obtained from parents or guardians of children enrolled in the study . Parents or guardians disclosed the diagnosis of leprosy to the respective contacts .
This study was conducted in 277 randomly selected public schools located in various districts of Manaus . In total , 34 , 547 children under 15 years of age were enrolled in the study . Overall , 18 , 770 ( 54 . 3% ) were females and 15 , 777 ( 45 . 7% ) were males . The mean age was 9 . 6 years ( standard deviation [SD] = 2 . 58 ) . Regarding the distribution by self-reported ethnicity , the majority ( 90 . 0% ) of schoolchildren examined were brown with similar results obtained for both sexes . According to the Brazilian Institute of Geography and Census , 69% of the Amazonas State’s population is brown [19] . The analysis for different proportions between sex and ethnicity did not show a statistical significance between browns and whites ( p = 0 . 16 ) . Overall , 8 . 2% of the 34 , 547 schoolchildren examined had skin diseases . The most common skin disease was fungal ( n = 955; 33 . 8% ) , followed by eczema/dermatitis ( n = 725 , 25 . 6% ) , viral diseases ( n = 153 , 5 . 4% ) , and leprosy ( n = 40 , 1 . 4% ) . A total of 40 leprosy cases were identified out of the total number of schoolchildren that were examined , resulting in a prevalence of 11 . 58 per 10 , 000 people . Among them , 23 ( 57 . 5% ) patients were males , and 17 ( 42 . 5% ) were females . Regarding leprosy classification , 32 ( 80% ) and 8 ( 20% ) patients had PB and MB forms of leprosy , respectively; among the PB patients , 24 ( 60% ) presented with one lesion . The analysis for different proportions between sex and leprosy classification did not show a statistical significance between PB and MB leprosy ( p = 0 . 43 ) . The mean age was 10 . 6 years ( range 4–13 ) ( Table 1 ) . Among the total cases of leprosy , 23 ( 59 . 0% ) were 11 to 14 years of age; a similar pattern was found in both genders . According to data from the Municipal and State Education Departments of the State of Amazonas , 334 , 228 ( 68% ) of the students are within this age range [19] . The analysis of the distribution among these three age groups showed statistically significant differences ( p < 0 . 01 ) . Notably , the majority of MB leprosy cases ( n = 7 ) were less than 11 years of age . There was a predominance of the brown race among the cases ( 90 . 0% ) , and a similar result was obtained for both genders . An overview of the tests performed to support diagnosis is presented in Fig 1 . Of the 40 leprosy cases , 32 ( 80 . 0% ) were PB , and 8 ( 20 . 0% ) were MB . A SSS was performed in 37 ( 92 . 5% ) of the leprosy cases , histopathological examination was performed in 34 ( 84 . 6% ) cases , and PCR was performed in 26 ( 65 . 0% ) cases . Six had a negative SSS test , but did not have either a skin biopsy nor PCR examination . Because these patients had skin lesions that fulfilled WHO clinical criteria for leprosy ( four had up to five lesions and two had more than five lesions ) , they were diagnosed and treated for PB and MB leprosy , respectively . Of the 37 patients who received a SSS , 33 ( 89 . 2% ) were negative , and four ( 10 . 8% ) were positive . Three patients did not undergo SSS , but these patients had a skin biopsy taken and presented a negative result for PCR . Histopathological features of leprosy were seen in two cases , and the result was inconclusive in one case . Because the latter patient had one lesion in which leprosy was clinically confirmed , he was given PB treatment . Leprosy was confirmed by histopathological examination in 14 children from the 34 histopathological slides analyzed . The results were as follows: indeterminate ( three cases ) , tuberculoid-tuberculoid ( four cases ) , borderline-tuberculoid ( three cases ) , borderline-lepromatous ( two cases ) and lepromatous-lepromatous ( two cases ) . In 20 patients , the histopathological examination yielded results that were inconclusive but did not exclude the diagnosis of leprosy . In this group , nine patients had a positive PCR result , as they exhibited fewer than five lesions that were being treated for PB leprosy , and 11 patients were negative for PCR examination . One out of the 11 had a positive skin smear , and 10 were clinically diagnosed as leprosy cases . The patient with the positive skin smear was treated for MB leprosy , and the other 10 who presented with fewer than three lesions , received PB treatment . In total , M . leprae DNA was detected in 12 ( 46 . 2% ) out of 26 patients . BCG scar status was recorded as positive in the majority ( n = 37 , 92 . 5% ) of the patients . Thirty-eight ( 95 . 0% ) children demonstrated a zero incapacity grade; one case of paresthesia ( grade one disability ) and one case of ulnar claw ( grade two disability ) were detected . Both patients had MB leprosy . A total of 206 people were registered as household contacts of the schoolchildren diagnosed with leprosy; only two direct neighbors , both with a past medical history of MB leprosy , were indicated as contacts by the legal guardians . Overall , 196 ( 95 . 1% ) of the contacts were clinically examined . Among these contacts , we diagnosed seven new leprosy cases: five siblings , an uncle , and an aunt were detected as index case patients . Two of these contacts were also under 15 years of age . Three contacts had PB leprosy , and four , including the two children who were under 15 years of age , presented with MB leprosy . Regarding the households , 21 ( 52 . 5% ) patients lived with three to four people , whereas nine ( 22 . 5% ) lived with more than seven people . More than 50% of the children lived with their families in households with up to four rooms , whereas 10 ( 25 . 0% ) children lived in households with five or more rooms . Among 40 schoolchildren diagnosed with leprosy , we were able to identify 21 ( 52 . 5% ) who had or continued to have contact with patients within their household , familiar or not , who had previously been treated for leprosy or were still under leprosy treatment . Of these , six ( 28 . 6% ) children had contact with grandparents with a past medical history of leprosy . Three ( 14 . 3% ) had contact with uncles; two ( 9 . 5% ) had contact with parents; two ( 9 . 5% ) had contact with their granduncles; one ( 4 . 8% ) had contact with an aunt; one ( 4 . 8% ) had contact with a great-grandfather; one ( 4 . 8% ) had contact with a grandmother and two cousins; and one ( 4 . 8% ) had close contact with a neighbor who was receiving leprosy treatment . Notably , the father of four sibling schoolchildren ( 19 . 0% ) was receiving leprosy treatment , while a grandmother and a great-grandfather had already been treated for leprosy . All of them , including the recently diagnosed siblings , presented with MB leprosy . Nevertheless , we understand that we did not design the study to test the familial/genetic nature of the susceptibility . However , we were able to observe important clusters where the physical distance and familial distance were detected . This description reinforces the need for contact tracing to stop leprosy transmission . As for the other 19 schoolchildren diagnosed with leprosy during this survey , we were not able to identify the possible source of infection . Fig 2 shows genograms of nine out of 40 schoolchildren with leprosy and their possible sources of infection . Children #1 , #2 , #3 and #4 belonged to the same family; during the investigation , it was found that the father , the maternal grandmother and the great-grandfather had been treated for leprosy , and the first two relatives were MB . Children #5 , #6 , #7 , and #21 had a history of grandfathers treated for MB leprosy ( Fig 2 ) . The parents of children #8 and #20 were receiving treatment for MB and PB leprosy , respectively ( Fig 2 ) .
This school-based , cross-sectional study found a higher leprosy prevalence among children than that registered in the official data . This result suggests that contact tracing is an important epidemiological tool in diagnosing new cases of the disease and possible sources of leprosy infection . In 2013 , one year before we began enrolling children in our study , the prevalence of leprosy in this population in Manaus was 0 . 68 cases per 10 , 000 children ( 0 . 68/100 , 000 in Amazonas State and 0 . 50/100 , 000 in Brazil ) [10 , 24] . Our study cannot estimate prevalence exactly . However , our data clearly indicate a hidden prevalence , since our data suggests that 11 . 58 per 10 , 000 , which would be 17 times higher than that in the registered data . We detected 40 new cases of leprosy out of a total of 34 , 547 examined schoolchildren . New cases of leprosy diagnosed among screened contacts under 15 years of age were not included in the aforementioned prevalence . Overall , this data suggests the existence , in the city of Manaus , of a hidden prevalence of significant magnitude . From 1979 to 1982 , Talhari and co-authors performed an active case finding in Manaus and found a prevalence of 10 . 6 cases of leprosy per 10 , 000 children [17] . From 1991 to 2016 , the birth rate decreased in Amazonas State , from 32 . 4 to 19 . 7 per 1 , 000 , respectively [25 , 26] . Accordingly , official data from BMH show that the leprosy prevalence among children has been declining for the past 25 years in Amazonas State and also in Brazil [10] . However , our data , if confirmed in a design to estimate the prevalence , it would likely to be even higher than that found over 30 years ago . Recently , high rates of clinical[27] and subclinical leprosy have been reported in Brazil [28] . In both studies , the diagnosis of leprosy was based on clinical and serological results . In our study , the vast majority ( 85 . 0% ) of new cases of leprosy were confirmed by at least one diagnostic method that combines classical and novel tools: SSS and/or skin biopsy and/or PCR test . Accurate diagnosis and careful description of previously undiagnosed leprosy cases are important to address the true prevalence of the disease in endemic countries . In this study , 54 . 3% of screened schoolchildren were female , but the leprosy cases were male ( 57 . 5% ) ; this data is in accordance to the official data from the BMZ [19 , 24] . The majority of the leprosy cases were diagnosed in older children . This reinforces the need for active case finding and suggests that instituting an approach to contact tracing is probably a valuable policy . The majority ( 80 . 0% ) of the newly diagnosed cases of leprosy were PB with the presentation of a single lesion; this is similar to the rate found in other studies [27 , 29 , 30] . However , eight schoolchildren in addition to four contacts who were less than 15 years of age demonstrated MB leprosy . In endemic areas , the early exposure to M . leprae and the presence of familial cases of the disease facilitate the greater frequency of contamination of children [17 , 31–33] . Of the 21 schoolchildren with leprosy whose possible source of infection was identified among household contacts , 95 . 2% had contact with family members who previously had or were still receiving treatment for the disease . Contact with infected grandparents was found to be the most probable source of infection in our study . Notably , we found a cluster in which three generations had been diagnosed and treated for leprosy . High rates of consanguinity were found in other studies [30 , 34] , wherein parents and grandparents were the most likely source of infection [35–37] . Although household contact with an MB case is the strongest known determinant of leprosy risk , the vast majority of such contacts never manifest disease , which indicates the crucial role of genetic and/or environmental factors in the transmission of the M . leprae infection and/or the pathogenesis of clinical leprosy[31] . It is worth highlighting that patients and families are frequently not aware of any contact they have had with the disease , and they are often unaware of leprosy patients in the family or in the nearby neighborhood . Patients with active disease and higher bacillary loads are considered the most important actors in transmitting and perpetuating the disease in a way that household contacts exhibit the highest risk of developing the disease . Therefore , screening family and non-family members in leprosy-affected households is mandatory . Also , chemo or immuno-prophylaxis has been shown to reduce the risk among the household contact population [11– 13] . In addition to current leprosy cases in the family , housing in endemic areas , agglomerations of people living in a single household , family and social aggregation habits , household features , unfavorable conditions in the population and low educational level [35] are known risk factors for leprosy . In our study , conducted in an endemic area , more than 70% of the families lived in households with up to four rooms , and approximately 18 ( 45% ) of the cases cohabited with more than five people . Although controversial [13 , 38] , the administration of an additional dose of BCG to all healthy contacts is still recommended [11 , 14] . Besides reducing clinical leprosy among vaccinees , mainly of the MB type , recent data suggested that BCG vaccination of household contacts of MB leprosy patients may induce activation of T cell clones that recognize M . leprae specific antigens not shared with BCG [39] . The majority ( 92 . 5% ) of schoolchildren diagnosed with leprosy in this study had one positive BCG scar and the PB form of the disease ( 80 . 0% ) . Perhaps , if these children had been examined and vaccinated when their relatives were diagnosed with leprosy , we would not have had them as patients . Furthermore , early diagnosis could have prevented the occurrence of disability as found in two of the newly diagnosed cases of leprosy in this study . The frequency of leprosy occurrence in children is an important epidemiological indicator in determining the level of transmission of the disease . Recently , the WHO has published goals for the year 2020 suggesting that , among health control issues , leprosy should have zero cases in children and zero cases with incapacities [40] . Officially , a trend towards the decrease of leprosy among children under 15 years of age has been suggested . However , our data indicates that the true prevalence of leprosy in this particular population may be slightly higher than that found over 30 years ago in the city of Manaus . To stop transmission , programs for the screening of household contacts should be improved and expanded , as screening has proven to be efficient for detecting early cases of leprosy [4] . These approaches associated with BCG vaccination and/or single dose rifampicin ( SDR ) reduce new cases in this household contact group [11 , 41] . However , complementary approaches to improve surveillance and , thus , uncover hidden undiagnosed infectious cases that are actively transmitting leprosy are crucial to break the chain of transmission . Here , we provide evidence that screening of schoolchildren could be a valuable strategy to support leprosy control and achieve the goal of zero transmission . This study shows that living with or in close proximity to leprosy patients and large family agglomerations in households with few rooms may be important risk factors for leprosy transmission among children . Moreover , this study highlights the value of contact screening of leprosy patients . There is a high level of family contact with leprosy in these cases , which gives support to the strategy of screening children in leprosy-affected households . | Leprosy is a disease that has long since been eradicated in the developed world , but it still affects poor people in developing countries , such as India , Brazil , and Indonesia . Because the causative agent of the disease may involve the skin and peripheral nerves , the disease can cause physical disabilities and deformities . Although leprosy affects all ages , children under 15 years of age are an important epidemiological marker because infection in that age group indicates active transmission within the community . In our work , we examined 34 , 547 children from public schools in Manaus , a city in the north of Brazil . In this population , we found 40 new cases of leprosy that were further confirmed by clinical and laboratorial tests . We also examined 196 people who had familiar or close non-familiar contact with the affected children . Among them , we identified the possible source of infection of 21 affected children and found seven new cases of leprosy . Overall , our findings revealed a detection rate of leprosy cases that was 17 times higher than the registered number . This indicates the necessity of identifying active cases of leprosy in order to improve case detection and effectively control the disease . | [
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] | 2018 | Leprosy among schoolchildren in the Amazon region: A cross-sectional study of active search and possible source of infection by contact tracing |
Subsets and Splits